Wireless Merged.doc

7/29/2019 Wireless Merged.doc

1/148

Proceedings of TEQIP-II sponsored National Conference on Wireless Communication, Signal Processing, Embedded Systems-WiSE

2013

157

H-shaped Coaxial Fed Microstrip Patch Antenna for BluetoothApplications

Nidhi Raj R1, Nithin Sethumadhavan2, Rakesh V3, Sharaz K M4, Srijith K514

Student, Department of ECE, Federal Institute of Science and Technology

Angamaly, Ernakulam 683 577, Kerala, India

[email protected], [email protected], [email protected], [email protected] Professor, Department of ECE, Federal Institute of Science and Technology


AbstractA patch antenna is a type of radio antenna with a low

profile, which can be mounted on a flat surface. It consists of a

flat rectangular sheet or "patch" of metal, mounted over a

larger sheet of metal called a ground plane. Microstrip patch

antenna is used in many applications such as Bluetoothtechnology, mobile phones and other short range applications

due to their properties like low weight, easy to integrate,

compactness etc. This paper includes the study of an H shapedcoaxial fed microstrip patch antenna which is proposed forBluetooth applications at 2.4GHz frequency. The effect of

different physical parameters of antenna on frequency of

operation, bandwidth, return loss and the effect of addition of

slots on those parameters has been included in the study. Acompact size patch antenna with dielectric substrate FR4 with

r=4.4 is used. The simulations are done on HFSS 13.0

simulation software.

KeywordsMicrostri p patch antenna, FR4, H shaped patch, u-slot

I. INTRODUCTIONThe BLUETOOTH technology provides short

range of wireless connections between electronicdevices like computers, mobile phones and manyothers thereby exchanging voice, data and video.The rapid increase in communication standards hasled to great demand for antennas with low realestate, low profile and size, low cost of fabricationand ease of integration with feeding network [1].

Microstrip patch antennas are widely usedbecause they are of light weight, compact, easy tointegrate and cost effective. The radiationmechanism arises from discontinuities at each

truncated edge of the microstrip transmissionline. The radiation at the edges causes the antennato act slightly larger electrically than its physicaldimensions, so in order for the antenna to

be resonant, a length of microstrip transmission lineslightly shorter than one-half a wavelength at thefrequency is used[2]. A patch antenna is usuallyconstructed on a dielectric substrate, using the samematerials and lithography processes used tomake printed circuit boards. However, the serious

problem of patch antennas is their narrowbandwidth due to surface wave losses and large sizeof patch for better performance[3].

In this paper, a compact size patch antenna isproposed with dielectric substrate as FR4 withr=4.4 and dimensions of the patch are adjusted toimprove the parameters like return loss and

bandwith.

The effect of addition of slot on bandwidth hasbeen carefully analyzed. An optimum position for

feed to get maximum bandwidth for the H shapedpatch antenna with U-slot is proposed in this study.

The simulations are performed using HFSS 13.0

which is a high performance full wave EM field

simulator for arbitarary 3D volumetric passive device

modelling that takes advantage of the familiar

Microsoft Windows graphical user interface. It

integrates simulation, visualization, solid modelling,

and automation in an easy to learn environment where

solutions to 3D EM problems are quickly and

accurately obtained.

II.DESIGNCONSIDERATIONS
mailto:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]


2/148

Proceedings of National Conference on Wireless Communication, Signal Processing, Embedded Systems-WISE 2013

158

A. H-shaped patch without slotA. The proposed structure[1] of the antenna is

shown in Fig 1. The antenna is simulated on anFR4 substrate with a dielectric constant of 4.4. The

thickness of the substrate is 6.7 mm. The size ofthe antenna is 80 80 mm2 , which is suitable for

most Bluetooth devices. Rectangle shaped patchesare cut at middle to form shaped patch antennaand width of each arm is 25mm.

Fig. 1: Geometry of Patch antenna without slot

B.H-shaped patch with single U-Shaped slotNow a U shaped slot is created on antenna with

suitable dimensions as shown in Fig. 2. The slotcontains no conductive material like other parts ofantenna. Initially a patch antenna is created with the

dimensions previously discussed i.e. an H shapedstructure with 80 mm length, width of each leg 20mmand a gap of 20 mm is created on a FR4 substratehaving a thickness of 6.7 mm. The size of substrate andground plane is selected as 100mm 80mm. The Hshape is made at the centre part of substrate in order tosimplify the calculation.

Fig. 2: Patch antenna with U-Shaped slot

C.H shaped patch with dual U-Shaped slotsHere one slot is the mirror image of other so that

design complications can be avoided (Fig.3). The size

of each slot is made same as discussed in the previous

section.

Fig. 3: H-shaped patch antenna with dual slots

III.SIMULATIONRESULTSA. Without slot

The antenna has minimum reflected power at the

designed frequency i.e. at 2.4GHz. The bandwidth

obtained is small, around 30 MHz.


3/148


159

Fig. 4: Return loss

B. With single slotUpon introducing a slot bandwidth is found to

increase. A study is conducted by varying the feed

position, width and position of slot and the effect of

variation of these parameters on bandwidth is tabulated

in Table 1 and is shown in Fig.5.

TABLE 1:VARIATION OF PARAMETER AGAINST WIDTH OF SLOT

Fig. 5: Effect of width of slot on bandwidth

A maximum bandwidth of 252.4MHz is attained for

slot width of 05mm.

C. With dual slotInitially in this part of study, the length of slot is

varied. Each value of length has two different

bandwidths, say BW1 and BW2. The BW1 value

decreases slightly as length increases from 27mm, but

after certain value it increases so it reaches a maximum

value at 58mm. In case of BW2, it decreases from the

beginning itself at length = 45mm, the value of return

loss decreases below 10dB results in zero bandwidth.

But there after it increases and reaches a value of

80MHz.

Width

(mm)

Freq

(GHz)

Return

Loss(db)

Impedance

( )

Bandwidth

(GHz)

0.1 2.33 -15.6224 37.33-7.014j 0.0879

0.2 2.301 -15.2942 35.72-3.69j 0.0814

0.5 2.301 -14.34 36.14-9.14j 0.2524

1 2.301 -13.93 35.2-11.6j 0.1198

1.5 2.317 -14.21 37.5-15.1j 0.0916

1.8 2.269 -14.13 38.42-16.7j 0.0887

2 2.33 -14.3 34.3-5.98j 0.0939


4/148


160

Hence it is possible to attain a maximum value of 345.3

MHz (for BW2) at length = 50mm if we use two slots

of equal dimension. But the frequency of operation isshifted to 4.77 GHz. Fig. 6 shows the variation of BW2

against the variation of length. It clearly indicates a

sudden increase in bandwidth (BW2) to a value of

345.3MHz which is well above the bandwidth of

ordinary patch antenna.

TABLE 2:VARIATION OF PARAMETERS AGAINST LENGTHOF SLOT

Fig. 6: Effect of length of slot on bandwidth

IV.CONCLUSIONSThe performance parameters are analyzed for the

optimized dimensions and the proposed antenna workswell at the required 2.4GHz BLUETOOTH frequency

band. The effect on bandwidth upon introduction of slot

is noted down carefully in the study. The bandwidth

significantly improves when slots are added. For a

normal H shaped patch antenna the observed bandwidth

was 30MHz. The bandwidth was increased to 252.4

MHz when a single slot is introduced. The bandwidth

further increased to 345.3 MHz with the introduction of

two slots. For the dual slotted patch antennas, two

frequencies of operation were observed. Both were

shifted slightly from the designed operating frequency.

ACKNOWLEDGMENT

The authors wish to acknowledge the Chairman,FISAT and the Principal, FISAT for providing the

necessary laboratory facilities. We would also liketo thank Mrs. P R Mini, HOD, ECE, FISAT for herconstant support and encouragement.

REFERENCES

[1] Design of coaxial fed microstrip patch antenna for 2.4 Ghz Bluetoothapplications (Govardhani Immadi, Nanilbabu, G.Anupama, M.Mani,2009-11 CIS journal volume 2,No.12 Dec 2012)

[2] The Basics of Patch AntennasBy D. Orban and G.J.K. Moernaut[3] Balanis, C. A., Antenna Theory Analysis and Design, John Wiley &

Sons, 3rd edition, 2005.

Length

(mm)

Freq

GHz

Return

Loss(db)Impedance

Bandwith

GHz

271.755 -12.333 33.86-7.53j 0.0552

3.056 -16.27 34.9+11.69j 0.1087

321.755 -12.0478 33.88-7.54j 0.0531

3.0402 -13.096 35.6+5.3j 0.0687

38

1.771 -11.7128 30.3+2j 0.0514

3.04 -11.305 35.6+5.3j 0.04

45 1.755 -12.184 33.9-7.9j 0.0577

3.008 -9.47 33.43+22.8j -

501.7711 -13.8711 30+2.8j 0.0679

4.7751 -14.0782 73.67-53.8j 0.3453

58

1.739 -28.0354 38.92-18.9j 0.0704

3.9076 -22.1353 120.3-166j 0.08


5/148


161

[4] Users guide High Frequency Structure Simulator, ANSOFTCORPORATION

[5] D.M. Pozar, D.H. Schaubert, 'Microstrip Antenna, The Analysis andDesign of Microstrip Antennas andArray'. New York, IEEE Press,

1995.[6] Dr. Otman El Mrabet, High Frequency Structure Simulator (HFSS)

Tutorial


6/148


162

A Survey on Contributing Entities for SeamlessStreaming

Namitha Murugesh and Gowri Shankar

Dept of Computer Science and EngineeringB M S College of Engineering

Bangalore, India

Abstract A growing number of mobile users require

uninterrupted audio/video streaming while they are moving

through the heterogeneous networks. They expect seamless

mobility as they move with their devices equipped with multiple

interfaces across different wireless infrastructures, spanning

from Bluetooth, IEEE 802.11 (WiFi) to cellular 3G or 4G

networks. The provisioning of mobile multimedia services in this

novel scenario is still a very challenging task due to the diversenature of the different networks and end user devices. One of the

most challenging problems is supporting the continuous

provisioning of multimedia flows i.e., service continuity during

handoffs when a wireless device disconnects from one network

and re-connects to a new one. In particular vertical handoff

situations that occur when mobile devices dynamically change

not only their access points but also the wireless access

technology/infrastructure they are using, e.g., from WiFi to 3G

possibly requiring dynamic content adaptation. This survey

concentrates on various dynamic content adapting techniques,

protocols that aid in streaming, handoff procedures that affect

continuity in streaming and proxy nodes that are used tomaximize the QoS and experience of user.

Keywords- content adaptation; ubiquitous; heterogeneous

networks; streaming; verti cal handoff

I. IntroductionAn evolving trend is that the customer is equipped with a

mobile device (e.g. laptop, smart phone, tablet pc etc.) which isused to stream videos from the internet as the user wanders.Innovations in wireless technology dramatically improved theway people communicate untethered and on the move. Thepresent 4G technology promises faster data rates. The user willnot only have to use a single device anywhere, anytime toaccess seamlessly all types of media existing in the internet. Toensure this process to be a pleasant experience from the user's

side an important intermediate technology has to be developedthat will adapt and formulate the content according to thetransmission characteristics of the end-to-end communicationpath and to the capabilities of the displaying device. Themassive heterogeneity in terms of terminal/network capabilitiesand user expectations requires efficient solutions for theadaptation and transport of modern media in an interoperableand universal fashion. The Hypertext Transfer Protocol(HTTP) is widely used on the internet and it has also become aprimary protocol for the delivery of multimedia content.Additionally, Standards Developing Organizations (SDOs)

such as MPEG have developed various technologies formultimedia transport and encapsulation, e.g., MPEG2-TS(Transport Stream) and MPEG4 file format. MPEG-DASHDynamic Adaptive Streaming over HTTP (DASH), also knownas MPEG-DASH, enables high quality streaming of mediacontent over the Internet delivered from conventional HTTPweb servers is in the process of standardization. At the same

time, many other SDOs such as the IETF, IEEE and 3GPPhave provided various protocols to deliver multimedia content.

Adaptation is a process which repackages the content beingstreamed according to the present eco-system characteristics.Here the eco-system consists of the end-user device, networkcharacteristics, content requested for streaming and theintermediate nodes like proxy. Different combinations of theseentities would affect the QoE (Quality of Experience) of theuser. The end user's device's screen size, computationalcapacity, battery power, available bandwidth, loss due towireless network play an important role in deciding the finalversion of the content viewed by the user. In an ongoingstreaming application when a user roams from one network to

another network the network parameters change and thesession has to be transferred seamlessly. When the userwanders through heterogeneous networks vertical handofftakes place. The transfer of session must be done seamlesslysuch that the user does not experience an interruption with theservice. The efficiency of the adaptation system is many waysrelated to the handoff procedures. The combinations of bothactivities play a vital role in the QoE of the user. Researchers inRef. [1] explain how QoE could be improved by both networkQoS and application QoS management.

The survey focuses on the different technologies,mechanisms and protocols that help to adapt the content beingstreamed from the source to the client in a seamless way as the

client roams around in a heterogeneous network. Section IIdescribes the codecs and video formats that aid in contentadaptation. Section III describes the different transportprotocols that are used for streaming. Section IV explores thedifferent handoff procedures. Section V explores the role ofproxy in content adaptation


7/148


163

II.Content Formats and their impacton adaptation

The major issues to be addressed when adapting the contentare the diversity of the multimedia content coupled with the

variety of internet connections utilized to access it. Adaptationis the process that would bridge the gap between the content atthe source and the client's expected content. Instead of havingeach medium stored in multiple representations, each matchingthe characteristics of a probable end-device and the bandwidthavailable, the source can provide only one or a fewrepresentations and rely on the adaptation functionality todeliver the content in the appropriate form at the receiver.Thus, users gain access to a great variety of media, virtuallywith any possible combination of connection and device type.The adaptation process is flexible enough to both hide theadaptation details from the typical user and give the power userthe means to customize the adaptation process according to the

users needs, through an explicit adaptation policy.Transcoding is a process where the content is re-coded into

a new format. The transcoded video streams can have a lowerspatial resolution, a lower temporal resolution, a lower quality,or even a different compression standard [2]. The new formatis decided based on the target devices capability and constraintsthat are present in the network connection. In transcoding thecontent is decompressed completely or to an intermediate formand again recoded into a form that is decodable by the clientsdevice. A single source sequence is kept in the video storageand different versions are created on-the-fly upon request usingtranscoding methods. An intermediate solution in [3] providingtranscoding at a low complexity by the aid of control streams isproposed.

The Scalable Video Coding (SVC) in H.264 [4],[5] wasdeveloped in response to the growing need for highercompression of moving pictures for various applications suchas videoconferencing, digital storage media, televisionbroadcasting, Internet streaming, and communication. It is alsodesigned to enable the use of the coded video representation ina flexible manner for a wide variety of network environments.Here in SVC the content is encoded once and can be decodedin several layers to suit the requirements of the target deviceand network conditions. It is a coding standard in which thevideo is coded with a base layer video stream meant forconnections with basic terminal capabilities or low bandwidthnetwork conditions. The residual information between the baselayer and the original content is then encoded to form one ormore enhancement layers. Additional enhancement layers canbe integrated with the base layer for scaling up the quality ofstream. Thus giving the user the flexibility to choose thequality of stream that can be received. SVC extension of theH.264/AVC standard has achieved significant improvements incoding efficiency with an increased degree of supportedscalability relative to the scalable profiles of prior video codingstandards. MPEG-4/AVC outperformed MPEG-2 in terms ofthroughput, packet delays, packet loss and jitter. Performanceof mobile video streaming in different scenarios depending on

the users movement speeds and video coding standards werepresented in [6]. The authors in [7] propose a dynamicadaptation scheme of SVC to optimally adapt video streamover heterogeneous networks using the MPEG-21 Digital ItemAdaptation (DIA) tool. MPEG-21 DIA framework provides

systematic solutions in choosing the optimal adaptationoperation to given conditions and supports interoperable videoadaptation. Their experiment results showed that the proposedadaptation scheme provides QoS-enabled delivery andconsumption of SVC with time-varying constraints of network,terminal, and user preference, in a robust and efficient way. In[8] Razib Iqbal and Shervin S show that the adaptationoperations can be quicker, when adaptation systems aredesigned to adapt contents according to the encoding structurebut in an intermediary node following a codec-independenttechnique. The adaptation is performed on-demand based on itsgeneric Bit stream Syntax Description (gBSD). Their approachwas to avoid conventional cascaded or multiple pre-coded bitstream adaptations.

To sum it all up, the major downside of transcoding is theadditional complexity needed to re-encode the video sequencein its new form. Scalable coding is less efficient compared tosingle layer coding when one fidelity version of the videostream should be transmitted. The layering is an unnecessaryoverhead. On the other hand layered coding gives flexibility inchoosing the quality of content dynamically which plays animportant role in seamless continuous streaming.

III. TRANSPORT PROTOCOLSThe content requested for can reach the client by different

transport protocols. The popular protocols are RTSP, RTMP

and HTTP. RTSP is specifically designed to be used fordelivering streaming media. Trick-play modes such as fast-forward or rewind, using VCR-like controls are supported withRTSP unlike HTTP which works best when segments are sentin sequential order. Viewing can also begin the moment thefirst bits reach the RTSP player; meaning that a 2- or 10-second segment delay doesnt affect RTSP delivery. Adobeuses a proprietary messaging protocol called RTMP (Real-Time Messaging Protocol) for its delivery from Flash MediaServer (FMS) to users Flash Player in-browser playback. It isa variant of RTSP. In multicasting scenarios RTSP can supportmulticasting by delivering a single feed to many users, withouthaving to provide a separate stream for each of them. HTTP isa true one-to-one delivery system. RTMP like RTSP is defined

as a protocol that saves the state of session. From the first timea client player connects until the time it disconnects, thestreaming server keeps track of the clients actions or statesfor commands such as play or pause. When a session betweenthe client and the server is established, the server beginssending video and audio content as a steady stream. Thisbehaviour continues and repeats until the server or player clientcloses the session. Recent advancements also accommodate forpotential brief interruptions in the server-client connection,allowing for a small amount of content to be played back froma local buffer. Encryption is another hallmark of RTMP, as


8/148


164

RTMP encrypted (RTMPE) protects packets on an individualbasis (more on this later). Some HTTP-based solutions arebeginning to address integrated digital rights management(DRM), but the majority of HTTP delivery cannot supportencryption at a packet level. The tunnelling feature in RTMP

called RTMPT allows RTMP to be encapsulated within HTTPrequests. This allows RTMP to traverse firewalls by appearingto be HTTP traffic on Port 80. HTTP streaming has gainedpopularity in recent years for the following reasons. Largersegments of multimedia can now be delivered efficiently usingHTTP. Support for HTTP in the present Internet infrastructureis favourable. CDNs have evolved to serve multimediaservices. HTTP is firewall friendly because almost all firewallsare configured to support its outgoing connections. HTTPstreaming is light on the server since the client manages thestreaming without having to maintain a session state on theserver. The popular streaming platforms that use HTTPstreaming as their underlying delivery method are ApplesHTTP Live Streaming[9], Microsofts Smooth Streaming[10]

and Adobes HTTP Dynamic Streaming[11]. However, eachimplementation uses different manifest and segment formatsand therefore to receive the content from each server, a devicemust support its corresponding proprietary client protocol. Astandard for HTTP streaming of multimedia content wouldallow a standard-based client to stream content from anystandard-based server, thereby enabling interoperabilitybetween servers and clients of different vendors. MPEG-Dynamic Adaptive Streaming (DASH) [12] is being developedto facilitate the idea of a common ecosystem of content andservices that will be able to provision a broad range of devicessuch as PCs, TVs, laptops, set-top boxes, game consoles,tablets, and mobiles phones. The multimedia content is

captured and stored on an HTTP server and is delivered usingHTTP. The content exists on the server in two parts: MediaPresentation Description (MPD), which describes a manifest ofthe available content, its various alternatives, their URLaddresses, and other characteristics; and segments, whichcontain the actual multimedia bitstreams in the form of chunks,in single or multiple files. To play the content, the DASH clientfirst obtains the MPD. The MPD can be delivered using HTTP,email, thumb drive, broadcast, or other transports. By parsingthe MPD, the DASH client learns about the program timing,media-content availability, media types, resolutions, minimumand maximum bandwidths, and the existence of variousencoded alternatives of multimedia components, accessibilityfeatures and required DRM, media-component locations on the

network, and other content characteristics. Using thisinformation, the DASH client selects the appropriate encodedalternative and starts streaming the content by fetching thesegments using HTTP GET requests. After appropriatebuffering to allow for network throughput variations, the clientcontinues fetching the subsequent segments and also monitorsthe network bandwidth fluctuations. Depending on itsmeasurements, the client decides how to adapt to the availablebandwidth by fetching segments of different alternatives (withlower or higher bitrates) to maintain an adequate buffer. TheMPEG-DASH specification only defines the MPD and the

segment formats. The delivery of the MPD and the media-encoding formats containing the segments, as well as the clientbehaviour for fetching, adaptation heuristics, and playingcontent, are outside of MPEG-DASHs scope. Streaming pathsin heterogeneous networks include IEEE 802.11 wireless as

well as 3G/4G mobile networks. TCPs shortcomings onwireless paths degrade the performance and QoS for highdefinition media streaming while the actual bandwidthprovisioning on those networks is no longer the limiting factor.Due to physical packet loss and large propagation delay thetransport protocol suffers from significant underutilization ofthe available bandwidth. For dynamic HTTP streaming thisunderutilization translates directly into unnecessary qualityreduction. In order to improve the quality of dynamicstreaming on wireless networks, Manuel Gorius, YongtaoShuai and Thorsten Herfet [13] implement a novel transportprotocol - Predictably Reliable Realtime Transport (PRRT), aprotocol layer that efficiently supports the reliability requiredby multimedia services under their specific time constraint. The

dynamic adaptive streaming also will be benefited with thisapproach.

IV.HANDOFF-PROCEDURESWhen the mobile user wanders out of the coverage area of

the present network and into coverage area of a differentwireless network a handoff has to take place between thenetworks. The handoff can be a homogeneous also known ashorizontal handoff if the two networks have similarcharacteristics e.g. between two Wi-Fi spots. If thecharacteristics of the networks are different it is called aheterogeneous or vertical handover e.g. form Wi-Fi to 4Gcellular network. The techniques used for managing handover

can be classified depending on the layer of the network stack atwhich the handover is done. The possible classes are handoverat network, transport or application layer. Mobility at thenetwork layer is provided by Mobile IP [14]. This class ofhandoff is efficient regarding the period the stream isinterrupted on down side the multimedia session cannot beadapted to the parameters of the new access network. Also MIPpresents poor scalability and high packet loss. The transportlayer handoff continues the transport connection during thenetwork switch while changing the associated IP address.Transport layer mobility management is achieved through theMobile Stream Control Transmission Protocol (mSCTP) [15].mSCTP resolved the problem of packet loss encountered at

network layer mobility by pausing the transmission duringmobility induced disconnections. mSCTP offers an efficienthandover management by using optimization of the path-transition and failover mechanism. The disadvantage ofmSCTP is that it does not address context aware quality ofservice. Several mechanisms for mobility support at applicationlayer have also been defined. If the handover is triggeredbefore losing connectivity, the application layer mobilityperforms better than the other two solutions. This approachoffers another important advantage, because the multimediasession parameters can be adapted to the available resourcesfrom the connected network. The specifications for application


9/148


165

layer mobility were defined by 3GPP working group. Theydeveloped a multimedia session continuity (MMSC) [14]framework for session transfer between packet switchednetworks (PS) in conjunction with the session transfer betweenpacket switched networks and circuit switched network (CS),

standardized already as Voice Call Continuity (VCC). ElenaApostol and Valentin Cristea [15] propose architecture thathandles multimedia streaming adaptation, session managementand takes into consideration user profiles and a set of quality ofservice criteria. To ensure session continuity when a usermoves from one network to another this architecture supportshandover at the application layer which offers a better qualitycontrol than the majority of mobility solutions. Sessioncontinuity during handover by integrating mSCTP into the3GPP IMS [18] architecture is presented in [19]. IMS is theservice control layer to add QoS control and context-awarefunctions.

V.PROXYAn intermediate node between the server and the client

identified as appropriate for performing the content adaptation,store and forward is called the proxy. The proxy or gateway,receives instructions from the receiver prior to the streamsinitiation, regarding the parameters of the adaptation process.For the mobile devices featured with lower bandwidth networkconnectivity, transcoding can be used to reduce the object sizeby lowering the quality of a multimedia object. In view of themonolithic transcoders which only provide transcodingservices and have limited performances due to the unknowndata types and protocols in the prior research the authors of[20] propose the architecture of versatile transcoding proxy(VTP). Based on the concept of the agent system, the VTP

architecture can accept and execute the transcoding preferencescript provided by the client or the server to transform thecorresponding data or protocol according to the user'sspecification. Media cloud services offer a unique opportunityfor alleviating many of the technical challenges faced bymobile media streaming, especially for applications withstringent latency requirements. A novel cloud-assistedarchitecture is proposed in [21] for supporting low-latencymobile media streaming applications such as online gamingand video conferencing. A media proxy at the cloud isenvisioned to calculate the optimal media adaptation decisionson behalf of the mobile sender, based on past observations ofpacket delivery delays of each stream. The proxy-based

intelligent frame skipping problem is formulated within theMarkov Decision Process (MDP) framework, which capturesboth the time-varying nature of video contents as well as burstyfluctuations in wireless channel conditions. The optimal frameskipping policy is calculated using the stochastic dynamicprograming (SDP) approach, and is shown to consistentlyoutperform greedy heuristic schemes. In general, the sizes ofmultimedia files are much larger than those of regularwebpages. It is unlikely that a steaming proxy server canconstantly store entire contents of multimedia files in itsmemory. As a result, the streaming proxy server needs to splitindividual multimedia files into segments and only store

popular segments in its memory. Researchers had proposedvarious ways to do the segmentation. However, the sizes ofindividual segments are often fixed once the segmentation isdone. Tsozen Yeh and Zongwei Yang [22] argue that the sizesof individual segments should vary according to their

popularity. A popular segment can have a longer length so theoverall performance can be increased accordingly. A noveldesign, Dynamic Segment Size (DSS), which dynamicallyadjusts the length of segments by their popularity, is proposed.The design is applied to a sophisticated algorithm, Adaptiveand Lazy Segmentation (ALS), which performs the work ofsplitting multimedia files into segments and handling memoryreplacement in a streaming proxy server. The advantages thatcome with the adoption of the proxy solution is that it can belocated at the most critical position in the end-to-end path. Thecomplexity of the proxy architecture is significantly higher andrequires gateways with powerful CPUs and a lot of memory.The degree of the receivers participation in the adaptationprocess can dictate the applicability and the effectiveness of the

proxy adaptation scheme.

VI.CONCLUSIONThough there are numerous research efforts in adapting

streaming media according to the network characteristics andend-user equipment. Seamless transfer of the on-going sessionas the client wanders through heterogeneous networks is still achallenging process. Here we have surveyed the differentcomponents of the framework required to achieve a seamlesscontent adaptation during a streaming service

(1) References[1] Ricky K. P. Mok, Edmond W. W. Chan, and Rocky K. C. Chang,

Measuring the Quality of Experience of HTTP Video Streaming,IEEE International Symposium on Integrated Network Management(IM), 2011 IFIP, 2011,pp. 485-592.

[2] Amon. P, Haoyu Li, Hutter. A, Renzi. D ans Battista. S, ScalableVideo Coding and Transcoding, IEEE International Conference onAutomation, Quality and Testing, Robotics, pp. 336-341, May 2008.

[3] Glenn Van Wallendael, Jan De Cock, and Rik Van de Walle, FastTranscoding For Video Delivery By Means Of A Control Stream,Conference on Image Processing (ICIP), 2012 19th IEEE International,pp. 733-736, 2012.

[4] Advanced video coding for generic audiovisual services, ITU-T-REC-H.264, ITU-T,Jan-2012.

[5]

Heiko Schwarz, Detlev Marpe and Thomas Wiegand, Overview of theScalable Video Coding Extension of the H.264/AVC Standard, IEEETrans. on Circuits and Systems for Video Technology, vol. 17, no. 9,September -2007.

[6] Saleh Abdallah-Saleh, Qi Wang and Christos Grecos, Evaluation ofMobile Video Streaming in Heterogeneous Wireless Networks,Telecommunications Forum (TELFOR), 2011 19th, pp. 262-265,November-2011.

[7] Haechul Choi, Jung Won Kang and Jae-Gon Kim, Dynamic andinteroperable adaptation of SVC for QoS-enabled streaming, IEEETrans. on Consumer Electronics, vol.53, pp. 384-389, May 2007.

[8] Iqbal, R. and Shirmohammadi, S, MPEG-21 based temporal videoadaptation for heterogeneous devices and mobile environments, IEEE


10/148


166

International Conf. on Multimedia and Expo, 2009. ICME 2009, pp.1845-1846, 2009.

[9] R. Pantos and E.W. May, HTTP Live Streaming, IETF Internet draft,work in progress, Mar. 2011.

[10] Microsoft, IIS Smooth Streaming Transport Protocol, Sept. 2009;http://www.iis.net/community/files/media/smoothspecs/[MS-

SMTH].pdf.

[11] http://www.adobe.com/products/httpdynamicstreaming[12] Sodagar, I, The MPEG-DASH Standard for Multimedia Streaming

Over the Internet, MultiMedia, IEEE, vol. 18, pp. 62 67, April-2011.

[13] Gorius. M, Yongtao Shuai and Herfet. T, Dynamic media streamingover wireless and mobile IP networks, IEEE International Conferenceon Consumer Electronics - Berlin (ICCE-Berlin), pp. 158-162,September 2011.

[14] Xinyi Wu and Gang Nie, Design and Simulation of an EnhancedHandover Scheme in Heterogeneous Mobile IPv6 Networks,Conference on Information Processing, pp. 448-451, July 2009.

[15] ukasz Budzisz, Ramon Ferrus and Ferran Casadevall, Designprinciples and performance evaluation of mSCTP-CMT for transport-layer based handover, Vehicular Technology Conference,pp. 1-5, 2009.

[16] The Third Generation Partnership Project, Feasibility Study onMultimedia Session Continuity. VCC Release 8, June 2008,

[17] Elena Apostol and Valentin Cristea, Multimedia Mobility Serviceacross Heterogeneous Environments, International Conference onEmerging Intelligent Data and Web Technologies, pp. 172-177,September 2011.

[18] TS 23.328, IP Multimedia Subsystem, 3GPP, Release 6.[19]Nguyen Huu Thanh, Le Thi Hang, Ngo Quynh Thu, Vu Van Yem,

Nguyen Xuan Dung, Multimedia Session Continuity with Context-Aware Capability in IMS-based Network, International Symposium. onWireless Communication Systems, pp. 383-387, September-2009.

[20] Jung-Lee Hsiao, Hao-Ping Hung and Ming-Syan Chen, VersatileTranscoding Proxy for Internet Content Adaptation, IEEE Transactionson Multimedia, pp. 646- 658, 2008.

[21] Xiaoqing Zhu, Jiang Zhu, Rong Pan, Prabhu, M.S and Bonomi. F,Cloud-assisted streaming for low-latency applications, InternationalConference on Computing, Networking and Communications (ICNC),pp: 949- 953, 2012.

[22] Tsozen Yeh and Zongwei Yang, Using dynamic segmentationadjustment to improve the performance of streaming proxyservers,IEEE International Symposium on Broadband MultimediaSystems and Broadcasting (BMSB), pp. 15, 2012.


11/148

Proceedings of TEQIP II sponsored National Conference on Wireless Communication, Signal Processing, Embedded Systems-WiSE

2013

167

CPW Fed Slot Antenna for Wideband ApplicationsDeepthi V1, Gayathri N2, Meeranath R3, Merin Alexander4, Srijith K514

Student, Department of ECE, Federal Institute of Science and TechnologyAngamaly, Ernakulam 683 577, Kerala, India

[email protected], [email protected]

2, [email protected]

3,[email protected]

4

5Assistant Professor, Department of ECE, Federal Institute of Science and Technology


,[email protected]

AbstractA Coplanar Waveguide (CPW) fed slot antenna for

wideband applications is presented. The simulations were

performed for S11 and the radiation patterns. The structure was

modified for increasing the bandwidth and then the parameterswere measured. In order to examine the performances of this

antenna, a prototype was designed at frequency 2.4 GHz and

simulated with various widths of slots on both sides by HFSS

software package. The simulation result of bandwidth is 1.98GHz which covers the standard frequency of IEEE 802.11 b/g

and WiMAX.

KeywordsCoplanar waveguide, Return loss, radiation pattern,slot antenna.

I. INTRODUCTIONMicrostrip slot antennas are used in satellite and

communication application because of its lightweight

and ease of integration with monolithic microwave

integrated circuits. Microstrip antennas can be divided

into two basic types by structure, namely microstrip

patch antenna and microstrip slot antenna [1,2]. The

slot antennas can be fed by microstrip line, slot line and

CPW [3,4]. The CPW is the feeding which side-plane

conductor is ground and center strip carries the signal.

In this paper, we proposed the slot antenna fed by CPW

at a designed frequency of 2.4 GHz and for the

frequency range from 1.96-3.94GHz which covers the

standard frequency of IEEE 802.11 b/g (2.4-2.4835

GHz) and WiMAX (2.3-3.6 GHz).

II.ANTENNASTRUCTUREThe antenna is designed at 2.4GHz with the

symmetric structure, as shown in Fig 1. This

antenna is designed on RT/Duroid 5880, the

substrate with thickness (h) of 1.575mm and

dielectric constant r of 2.2. The coplanarwaveguide (CPW) is designed to be 50 ohms inorder to match the characteristic impedance of

transmission line. The dimension of the slotantenna is referred to the guide wavelength gwhich given by,

reff

g

fc

(2.1)where reff is the effective dielectric constant.

2

1rreff

(2.2)In this case, g at frequency 2.4 GHz is 98.81

mm. The total length of slot antenna (L1+L2+W2)is 0.81 g(80.0mm) and width of slot (H1; H2) is0.1 g (10.5 mm). For matching impedance with

characteristic impedance of transmission line 50ohms, the gap (W1), width of the center strip (W2)and length of CPW line (H3) are 0.5 mm, 2.4mm

and 23 mm, respectively.

III.DESIGNPROCEDUREThe design procedure for the proposed CPW fed

slot antenna is described here. This slot antenna

composed of two small slots on the ground planethat are left and right slots. For each case, the gap
mailto:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]


12/148


2013

169

(W1), width of the center strip (W2) and length ofCPW line (H3) are fixed to 0.5 mm, 2.4mm and 23

mm, respectively.

A.Design ITwo slots (left and right slot) with equal length and

width:

The parameters of this structure are as following:

L1 = L2 = 38.8mm

H1 = H2 = 10.5mm

Fig 1.Structure of CPW fed slot antenna for Design1.

B.Design IITwo slots with equal width and unequal length (Fig. 2).

The parameters of this structure are as follows:

L1 = 43.8mm; L2 = 33.8mm

H1 = H2 = 10.5mm

Fig 2. Structure of CPW fed slot antenna for Design2.

C.Design IIITwo slots with unequal length and width (Fig.3):

The parameters of this structure are as following:

L1 = 43:8mm; L2 = 33:8mm

H1 = 7:8; H2 = 4:1mm


D.Design IVThree slots of length (L3) 10mm and width (H3)

5mm are introduced to increase the bandwidth ofthe slot antenna. Three slots are introduced adjacentto the left slot as shown in fig 4.


13/148


2013

170


IV.SIMULATIONRESULTSThe simulated return losses for various designs are

shown in Fig 5 (a) to (d). While varying the length the

variation in bandwidth is as shown in Fig 5 (b).

(a)

(b)

(c)

(d)

Fig. 5. Simulated return loss S11 of the four designs (a) (d)

The decrease in width of the slots changes bandwidth as

shown in Fig. 5 (c). The addition of slots adjacent to the

left slots increases the bandwidth as shown in Fig 5 (d).

The simulation results are listed in table 1.

TABLE 1

SIMULATION RESULTS OF CPW-FED SLOT ANTENNA FOR DIFFERENT

DESIGNS.


14/148


2013

171

L1

(mm)

L2

(mm)

H1

(mm)

H2

(mm)

Bandwidth

(-10dB)

GHz

Return

Loss

(dB)

Before introducing slots adjacent to the left slot

38.8 38.8 10.5 10.5 1.00 -80.0

43.8 33.8 10.5 10.5 0.95 -23.5

43.8 33.8 07.8 04.1 1.60 -22.0

After introducing slots adjacent to the left slot

43.8 33.8 07.8 4.1 1.96 -25.5

The radiation patterns in the x-z plane for the differentdesigns are shown in Fig 6 and 7.

Fig 6. Radiation pattern for design 1,2,3 for different values of at 2.4GHz.

Fig 7. Radiation pattern for design 4 for different values of at 2.4 GHz.

V. CONCLUSIONSThe design of slot antenna fed by CPW is

considered on the basic structure. It is proved by

varying the length and the width of the slot forachieving the wideband for use in WLANapplications. This paper shows the maximum

bandwidth of 1.65 GHz at design frequency of 2.4GHz. The wideband is created with the differentlength and the different width of the slot antenna.

ACKNOWLEDGMENT

The authors wish to acknowledge the Chairman,FISAT and the Principal, FISAT for providing the

necessary laboratory facilities. We would also liketo thank Mrs. P R Mini, HOD, ECE, FISAT for herconstant support and encouragement.

REFERENCES[7] Benson, F. A. and T. M. Benson, Fields Waves and Transmission

Lines, Chaman and Hall,1991.[8] Balanis, C. A., Antenna Theory Analysis and Design, John Wiley &

Sons, Inc., 1997.


15/148


2013

172

[9] Giauffret, L., J.-M. Laheurte, and A. Papiernik,Study of variousshapes of the coupling slot in CPW-fed microstrip antenna, IEEETrans. Antennas Propagation, Vol. 45, No. 4, 642-647,1997.

[10] Bhobe, A. U. and C. L. Holloway, Wide-band slot antennas withCPW- feed line: hybride and log-periodic design, IEEE Trans.

Antennas Propagation ,Vol. 52, No. 10, 2545-2554, 2004.[11] Wang, C.-J., Member, IEEE, J.-J. Lee, and R.-B. Huang, Member,

IEEE, Experimental studies of a miniaturized CPW-fed slot antennawith the dual-frequency operation, IEEE Antennas and Wireless

Propagation Letters,Vol.2,2003.

Abstract In mobile ad hoc networks (MANETs), nodesmove freely and link/node failures are common, which leadsto frequent network partitions. When a network partitionoccurs, mobile nodes in one partition are not able to accessdata hosted by nodes in other partitions, and hencesignificantly degrade the performance of data access. To dealwith this problem, we apply data replication techniques.Existing data replication solutions in both wired or wirelessnetworks aim at either reducing the query delay or improvingthe data availability, but not both. As both metrics areimportant for mobile nodes, we propose schemes to balance

the trade-offs between data availability and query delay underdifferent system settings and requirements. Extensivesimulation results show that the proposed schemes canachieve a balance between these two metrics and providesatisfying system performance.

I ndex TermsData replication, data availability, datamodification, network monitoring, query delay, mobile ad hocnetwork (MANET).

Architecture

.

1. INTRODUCTION IN mobile ad hoc networks (MANETs), since mobile

nodes move freely, network partition may occur, wherenodes in one partition cannot access data held by nodesin other partitions. Thus, data availability (i.e., the

number of successful data accesses over the total

number of data accesses) in MANETs is lower than thatin conventional wired networks. Data replication has

been widely used to improve data availability indistributed systems, and we will apply this technique toMANETs By replicating data at mobile nodes whichare not the owners of the original data, data availabilitycan be improved because there are multiple replicas inthe network and the probability of finding one copy ofthe data is higher. Also, data replication can reduce thequery delay since mobile nodes can obtain the datafrom some nearby replicas. However, most mobile

nodes only have limited storage space, bandwidth, andpower, and hence it is impossible for one node tocollect and hold all the data considering theseconstraints.

By taking these issues into consideration, we expectthat mobile nodes should not be able (or willing) toreplicate all data items in the network (more discussionsin Appendix A, which can be found on the ComputerSociety Digital Libraryhttp://doi.ieeecomputersociety.org/10.1109/TPDS.2011.222)

B. One solution to improve the data accessperformance considering the resource constraints ofmobile nodes is to let them cooperate with each other;That is, contribute part of their storage space to hold

Dr.M.Jayaprasad, Sunita.T.N, Jyothi.B.K

Principal , RGIT College, Bangalore, M.Tech Student, Dept of Computer Science, RGIT, Bangalore,[email protected],[email protected]

Balancing the Query Delay In Mobile ad-hocNetworks With High DataAvailability


16/148


2013

173

data of others When a node only replicates part of thedata, there will be a trade-off between query delay anddata availability. For example, replicating most datalocally can reduce the query delay, but it reduces thedata availability since many nodes may end upreplicating the same data locally, while other data itemsare not replicated by anyone. To increase the dataavailability, nodes should not replicate the same datathat neighboring nodes already have. However, thissolution may increase the query delay since some nodesmay not be able to replicate the most frequentlyaccessed data, and have to access it from neighbors.Although the delay of accessing the data fromneighbors is shorter than that from the data owner, it ismuch longer than accessing it locally.

In this paper, we propose new data replication

techniques to address query delay and data availability

issues. As both metrics are important for mobile nodes,

we propose techniques to balance the trade-offsbetween data availability and query delay under

different system settings and requirements. Simulation

results show that the proposed schemes can achieve a

balance between these two metrics and provide

satisfying system performance.

The rest of the paper is organized as follows: The

next section presents some preliminaries of data

replication. In Section 3, we describe the proposed

schemes in detail. Section 4 evaluates the proposed

schemes through extensive simulations and Section 5

concludes the paper.

2. DATA REPLICATIONData replication has been extensively studied in the

web environment and distributed database systems (See

Appendix B, available in the online supplemental

material, for detailed literature review). However, most

of them either do not consider the storage constraint or

ignore the link failure issue. Before addressing these

issues by proposing new data replication schemes, we

first introduce our system model.

In a MANET, mobile nodes collaboratively share

data. Multiple nodes exist in the network and they send

query requests to other nodes for some specified data

items. Each node creates replicas of the data items and

maintains the replicas in its memory (or disk) space.

During data replication, there is no central server that

determines the allocation of replicas, and mobile nodes

determine the data allocation in a distributed manner.

The MANET studied in this paper can be represented

as an undirected graph G(V,E) where the set of vertices

V represent the mobile nodes in the network, and E V

V is the set of edges in the graph, which represents

the physical or logical links between the mobile nodes.

Two nodes that can communicate directly with each

other are connected by an edge in the graph. Let N

denote a network of m mobile nodes, N,N, ...Nm and

let D denote a collection of n data items d,d, ... ,dn

distributed in the network. For each pair of mobile

nodes Ni and Nj, let tij denote the delay of transmitting

a data item of unit-size between these two nodes.

Similar to [4], we assume that the delay function

defines a metric space; that is, they are nonnegative,

symmetric, and satisfy the triangle inequality. Links

between mobile nodes may fail and the link failure

probability between Ni and Nj is denoted as fij, which

is equal to fji as we assume symmetric links. The failed

links may cause network partitions. Queries generatedduring network partition may fail because the requested

data items are not available in the partition to which the

requester belongs.

Each node maintains some amount of data locally

and the node is called the original owner of the data.

Each data item has one and only one original owner.

For simplicity, we assume that data items are not

updated and can be used to extend the proposed scheme

to handle data update or data consistency issues. To

improve the data availability, these data items may be

replicated to other nodes. Because of limited memory

size, each node can only host C(C< n) replicas besides

its original data. The data replication problem, either


17/148


2013

174

optimizing the query delay or optimizing the

availability, has been proved to be a reduction from the

metric incapacitated facility location problem, which is

known to be NP-hard (see Appendix C, available in the

online supplemental material). Therefore, instead of

trying to find a complex algorithm that is not practical

to solve or approximate the problem, we use heuristics

that can provide satisfying performance with much less

computation overhead.

The following notations are used in this paper.

N: the set of mobile nodes in the network.

m: the total number of mobile nodes.

D: the set of available data items in thenetwork.

n: the total number of data items.

s i: the size of d i.

3. THE PROPOSED DATAREPLICATION SCHEMES

In this section, we propose several schemes to

address the data replication problem based on

heuristics. Before presenting these heuristics, we first

use an example to illustrate the basic ideas.

3.1A Motivating ExampleSuppose a network has only two nodes N1 and N2.

These two nodes may access four data items d1, ... ,d4with equal size, and each node only has enough space

to host two data items. we assume that the access

probability of a mobile node to a data item is available.

According to the Dynamic Access Frequency and

Neighborhood (DAFN) scheme proposed by Hara

neighboring nodes should try to remove duplicated data

items to save storage space and increase data

availability. In the first replication step, nodes replicate

the data that they are interested in, and hence both

nodes replicate d1 and d2 locally. In the second step of

DAFN, when two neighboring nodes have the same

data item di, the node that has a lower access

probability should replace di with the next most

frequently accessed data. Therefore, N1 replaces d2 with

d3 and N2 replaces d1 with d4. The final replication

result is: N1 hosts d1 and d3 whereas N2 hosts d2 and d4.

From this example and verified by simulations in

DAFN is a good scheme because duplicated data can be

removed from neighboring nodes and the memory sizecan be used effectively. However, the data availability

may be affected when the link failure probability is

high.DAFN scheme because DAFN does not consider

two important factors: the link stability between mobile

nodes and the query delay. Due to the complexity of the

data replication problem shown in Appendix C,

available in the online supplemental material, we

propose some heuristics.

Heuristics. Because mobile nodes have limited

memory, it is impossible for them to hold all their

interested data items. As a result, they have to rely on

other nodes to get some data. If mobile nodes only host

their interested data, it is possible that some data items

are replicated by every node while some other data

items are not replicated by anyone. Therefore, it is

important for mobile nodes to cooperate with each other

and contribute part of their memory to hold data for

other nodes. The problem is to determine the memory

space that a mobile node should contribute because bad

cooperation may actually degrade the performance, asshown in the above example.

We have the following heuristics: For a mobile node,

if its communication links to other nodes are stable,

more cooperation with these nodes can improve the

data availability; if the links to other nodes are not very

stable it is better for the node to host most of the

interested data locally. The above heuristic mainly

addresses the issue of data availability. For query delay,

it is better to allocate data near the interested nodes.

The degree of cooperation affects both the dataavailability and the query delay. In the following, we

propose various schemes to achieve various

performance goals.


18/148


2013

175

3.2The Greedy Data Replication SchemeOne naive greedy data replication scheme is to

allocate the most frequently accessed data items until

the memory is full. However, this naive scheme,

referred to as Greedy, does not consider the data size

difference between different data items. The data size

should be considered because smaller data require less

memory space, and hence replicating them can save

some memory space for other data items. Therefore, a

better greedy scheme is to calculate the data access

frequency of a data item dkby normalizing it against the

data size, i.e., aik/sk.

This greedy scheme, referred to as Greedy-S, lets

node Ni repeatedly pick the data item with the largest

aik/sk value from the data set that has not yet been

replicated at Ni until no more data can be replicated in

the memory. One drawback of the greedy scheme is

that it does not consider the cooperation between the

neighboring nodes and hence its performance may be

limited. We present the performance analysis and

numerical results in Appendix D, available in the online

supplemental material. The following sections present

schemes that apply different levels of cooperation

between neighboring nodes following our heuristics.

3.3The One-To-One Optimization (OTOO) SchemeIn this scheme, each mobile node only cooperates with

at most one neighbor to decide which data to replicate.

Suppose node Ni and Nj are neighboring nodes. Ni

calculates the combined access frequency value of N i

and Nj to data item dk at Ni, denoted as CAFij, by

using the following function:

CAFk ij = (aik+ ajk(1-fij))/si

(1)

Similarly Nj calculates its combined access frequency

to dkwith the following function:

CAFk ji = (ajk+ aik(1-fij))/si

(2)

We also need to consider the increased data

availability due to neighboring nodes. If the neighboring

node Nj of Ni has already replicated the data and the link

failure probability between Ni and Nj is low, Ni is less

likely to replicate this data because it can always get the

data from Nj. However, if the link failure probability is

high, Ni may like to replicate the data locally. Therefore,

we define a priority value for node N i to replicate data dk

given its neighboring node Nj, denoted as Pij, by using

the following function:

Pij= CAFk ij wij

(3)

where wij indicates the impact on data availability by

the neighboring node and the link failure probability.

The value ofwij is calculated as follows:

wij = {

Each node sorts the data according to the priority

value P and picks data items with the highest P to

replicate in its memory until no more data items can be

replicated. The P value function is designed so that

1. it considers the access frequency from aneighboring node to improve data availability;2. it considers the data size. If other criteria are

the same, the data item with smaller size isgiven higher priority for replicating because thiscan improve the performance while reducingmemory space;

3. it gives high priority to local data access, andhence the interested data should be replicatedlocally to improve data availability and reducequery delay;

4. it considers the impact of data availability fromthe neighboring node and link quality.

Thus, if the links between two neighboring nodes are

stable, they can have more cooperations in data

1

if data dk is not replicated at Nj.

if data dk is replicated at Nj,


19/148


2013

176

replication.

It is possible that according to OTOO, node Ni should

host dj but Ni is separated from nodes that have dj

because of network partitions. In this situation, Ni

selects the next best candidate (data item) according to

the replication scheme. This rule is also applied to otherreplication schemes proposed in the following. The

detailed pseudo-code and descriptions of the OTOO

scheme and the following schemes are provided in

Appendix E, available in the online supplemental

material.

3.4The Reliable Neighbor (RN) Scheme.OTOO considers neighboring nodes when making data

replication choices. However, it still considers its ownaccess frequency as the most important factor because

the access frequency from a neighboring node is

reduced by a factor of the link failure probability. To

further increase the degree of cooperation, we propose

the Reliable Neighbor scheme which contributes more

memory to replicate data for neighboring nodes. In this

scheme, part of the nodes memory is used to hold datafor its Reliable Neighbors. For node Ni, a neighboring

node Nj is considered to be Nis reliable neighbor if

1-fij > T,

where T is a threshold value. Let nb(i) be the set of

Nis reliable neighbors. The total contributed memorysize of Ni, denoted as Cc(i), is set to be

Cc(i) = Cmin(1, (1-fij)/) (4)

Where is a system tuning factor which affects the

memory allocated to itself and its neighbors.

Intuitively, Ni contributes more memory if its links with

neighboring nodes are more stable. The two extreme

cases are: 1) when Cc(i) = C, N i contributes all its

memory to hold data for neighboring nodes;

2) when fij= 1, Njnb(i), Ni does not contribute any

memory. The reason behind the RN scheme is that when

links to neighboring nodes of Ni are stable, Ni can hold

more data for neighboring nodes as they also hold data

for Ni. Because links are stable, such cooperation can

improve the data availability. If links are not stable, data

on neighboring nodes have low availability and may

incur high-query delay. Thus, cooperation in this case

cannot improve data availability and nodes should be

more selfish in order to achieve better performance.

The data replication process works as follows: Node

Ni first allocates its most interested data to its memory,

up to C-Cc(i) memory space. Then all the rest of the

data are sorted according to P to a list called theneighbors interest list. The P value of Ni to dkis definedas

(5)

The memory space of Cc(i) is used to allocate data with

the highest P values. There may be some overlap

between Nis interested data and the allocated datainterested by Nis neighbors. If during the allocation, adata item is already in the memory, this data item will

not be allocated again and the next data item on the

neighbors interest list is chosen instead.

3.5Reliable Grouping (RG) SchemeOTOO only considers one neighboring node when

making data replication decisions. RN further considers

all one-hop neighbors. However, the cooperations inboth OTOO and RN are not fully exploited. To further

increase the degree of cooperation, we propose the

reliable grouping scheme which shares replicas in large


20/148


2013

177

and reliable groups of nodes, whereas OTOO and RN

only share replicas among neighboring nodes. The basic

idea of the RG scheme is that it always picks the most

suitable data items to replicate on the most suitable

nodes in the group to maximize the data availability and

minimize the data access delay within the group.

In the RG scheme, there is no redundant replication

until every data item is replicated at least once.

Therefore, the maximum degree of cooperation within

the reliable group can be achieved. Because the function

for selecting the best node to place each data replica

considers the access delay between the query node and

the nearest replication node in the group, the RG scheme

can reduce the number of hops that the data need to be

transferred to serve the query.

Due to the page limitation, the detailed protocol

description and a comprehensive performance

complexity and bound analysis of the proposed schemes

are presented in Appendices E and F, available in the

online supplemental material.

4. PERFORMANCE EVALUATIONS

In this section, we evaluate the performance of the

proposed schemes: OTOO, RN2 (RN with =2), RN8(RN with =8), RN16 (RN with =16), and RG by

comparing them with the DAFN scheme and theGreedy scheme through extensive simulations.

4.1Simulation SetupWe have developed a simulator based on CSIM 19 to

evaluate the performance of the data replication

schemes. At the beginning of the simulation, m nodes

are placed randomly in a 2500 m 2500 m area. The

radio range is set to be D. If two nodes Ni and Nj are

within the radio range (i.e., D(i,j)


21/148


2013

178

can also be used as a metric of system power

consumption. This is because in wireless

communication, data transmission is the key factor

affecting the system power consumption compared to

other factors such as disk or CPU operations Therefore,

if there is more query traffic, more energy consumption

is expected. If one replication scheme generates less

traffic, it is more power efficient.

When a query for data dk is generated by node Ni, if

dk can be found locally, or at a node that is reachable

through single or multi-hops, this access is considered

successful. The query delay is the number of hops from

Ni to the nearest node that has dk multiplied by the data

size, and query traffic is defined as all messages

involved to serve the query. If dkis in the local memory

of Ni, the query delay and query traffic are both 0. Most

system parameters are listed in Table 2.

4.2Simulation ResultsExperiments were run using different workloads and

system settings. The performance analysis presented

here is designed to compare the effects of different

workload parameters such as Zipf parameter, network

size, radio range, memory size, and node mobility (due

to the space limitation, the effects of different mobility

models are provided in Appendix G, available in the

online supplemental material). For each workload

parameter (e.g., the mean update arrival time or the

mean query generate time), the mean value of the

measured data is obtained by collecting a large number

of samples such that the confidence interval is

reasonably small. In most cases, the

4.2.1 F ine-Tuning TrIn Fig. 2, we evaluate the effects of T r, which affects

the number of cooperative neighbors in the RN scheme

and the RG scheme. Larger Trresults in smaller number

of cooperative neighbors, and vice versa. We can seethat Tr has more significant effects on the performance

of RN2 (RN with = 2) than RN8 and RN16, becauseRN2 contributes the largest portion of the memory size

to neighbors. The performance of the RG scheme is

also affected by Tr, because the change of Tr affects the

number of nodes in a reliable group. From Fig. 2a, we

can see that when Tr < 0.4, as long as Tr increases, the

data availability of RG, RN8, and RN16 are decreasing

while the data availability of RN2 is increasing; when

0.4 < Tr < 0.6, all schemes have a decreasing trend in

data availability as Tr increases; similar trend can be

found when Tr > 0.6. In Fig. 2b, when T r changes from

0.2 to 0.4, RG and RN2 have a large decrease in query

delay; however, when Tr becomes larger than 0.4, all

four schemes have stable and small delay decrease.

When Tr is around 0.6, all schemes have relatively

stable performance, which means the change of T r does

not have significant effect on the relative performance

of different data replication schemes. Thus, we use T r =

0.6 in the following

4.2.2 Fine-Tuning By controlling the link failure probability can be

adjusted. When the link failure probability deceases,

data availability increases as shown in Fig. 3. We

choose = 0.95 to achieve a balance among allreplication schemes.

As can be seen from the figure, DAFN has high-

query delay because it tries to avoid duplicated data

among neighboring nodes. Even if a data item is

popular among two neighboring nodes, it is still

allocated at only one of the neighboring nodes.

Therefore, many accesses have to be satisfied by the

querying neighboring nodes, which increase the query

delay. For similar reasons, the query delay of RG is also

high. However, RG considers all nodes in a reliable

group during data replication. It organizes data better

within each reliable group, which helps RG achieve

higher data availability

4.2.3 Effects of the Zipf Parameter ()In this section, we evaluate the effects of the Z ipf

parameter on the system performance. As


22/148


2013

179

increases, more accesses focus on hot data items and

data availability is expected to increase.

Fig. 4 demonstrates the effects of the Z ipf parameter

on the system performance when nodes have

different access pattern. Fig. 4a shows that the proposed

schemes outperform the DAFN scheme in terms of dataavailability in most cases. The reasons are as follows:

first, our schemes consider the link failure probability

when replicating data (for OTOO and RN) or

organizing groups (for RG); second, the OTOO and RN

schemes avoid replicating data items that are not

frequently accessed by using the P value. On the other

hand, the DAFN scheme does not consider the link

failure probability and it sometimes replicates data

items with low-access frequency instead of frequently

accessed data items, as shown in the example in Section

3.1.

Fig. 4b shows the query delay of different schemes. The

DAFN scheme is outperformed by the proposed

schemes in all situations. This shows that our schemes

can achieve better performance in terms of data

availability and query delay. From Fig. 4b, we can also

find that the relation of query delay is RG > RN2 >

RN8RN16 > OTOO. This shows that when nodeshave different interests, to achieve a low-query delay, it

is better for them to host the data that they areinterested in, and cooperation among them does not

show significant advantage.

Fig. 5 shows the effects of the Zipf parameter on

the system performance when nodes have the same

access pattern. We can see from Fig. 5 that all the

proposed schemes perform much better than the DAFN

scheme in terms of data availability and all the

proposed schemes in most situations perform better

than DAFN in terms of query delay. Greedy-S performs

better than Greedy because it gives higher priority todata items with smaller size, and thus more important

data can be replicated and the performance is improved.

Comparing RN2, RN8, RN16, OTOO, and RG, we find

that the relation of their data availability is RG > RN2 >

RN8 > RN16 OTOO (RG performs the best asexpected) while the relations of their query delay is RG

> RN2 > RN8 > RN16 > OTOO (OTOO performs the

best). This clearly shows the trade-offs between these

two performance metrics. Higher degree of cooperation

improves the data availability, but it also increases the

query delay because more data items need to be

retrieved from neighboring nodes. This figure also

gives us directions on how to achieve certain

performance goals. If high data availability is required,

nodes should be more cooperative with neighboring

nodes so that more data can be replicated in the

network. If low-query delay is more important, nodes

should be more selfish so that requests can be servedlocally instead of by neighboring nodes.

Since RN2, RN8, and RN16 exhibit similar

performance when other parameters change, to make

the simulation figures clear, we will only use RN8 to

represent the RN schemes.

Fig:Tranferring the Files From One to Another node


23/148


2013

180

4.2.4 Effects of the Number of Nodes in theNetwork (m)

The number of nodes in the network indicates the

node density of the network. When the number of nodes

increases, the density of the network increases and itbecomes better connected and the data availability

increases. Fig. 6 shows the effects of the number of

nodes on the system performance. In Fig. 6a, we can

see that when there are only 100 nodes in the network,

all schemes have relatively lower data availability due

to the sparse network connectivity. As the number of

nodes increases, nodes have more opportunities to get

the data from their neighboring nodes, and all schemes

have performance improvements in terms of data

availability as expected. When the network density

further increases, e.g., in a 500-nodes scenario, the data

availability of all schemes approaches to 0.9. Similar

observations can be found in Fig. 6b. Therefore, we

choose m =300 as the default setting to see the effects of

different schemes on the system performance.

4.2.5 Effects of the Radio Range (D)Fig. 7 shows the effects of the radio range on the system

performance under different access pattern. When the

radio range increases, the network is better connectedand the data availability is expected to increase. Fig. 7a

shows that all schemes perform as expected. The

proposed schemes perform much better than DAFN

when the radio range is small. When the radio range is

very large, different schemes have similar data

availability. This is because the network partition is very

rare in this situation and most data can be found in a

reachable node.

Figs. 7b and 7c show that the query delay and query

traffic increase as the radio range increases. This is

because when the network is better connected, some

previously unavailable data can be found at faraway

nodes. The proposed schemes always result in lower

query delay and traffic than the DAFN scheme. When

the radio range is extremely small, the query delay of all

schemes reduces to near zero, since it is hard to find a

neighbor with such small radio range and almost all

requests are served locally.

4.2.6 Effects of Memory Size (C)In this section, we evaluate the system performance

when the memory size (C) changes. As C increases,

more data can be hosted by a node and the data

availability increases. Similarly, more data can be found

locally as C increases and the query delay and query

traffic decrease.

Fig. 8 shows that when nodes have different access

patterns, the proposed schemes increase the dataavailability while providing lower query delay and

query traffic compared to the DAFN scheme. The

difference of data availability for OTOO, RN8, Greedy,

Greedy-S, and DAFN is not very large because when

nodes have different access pattern, they can simply

replicate their interested data locally to achieve a high

data availability. Thus, the room for improvement is

small. RG, however, organizes data replications within

each reliable group. It can provide more different data

items in each group. Thus, its data availability is much

higher than other schemes.


24/148


2013

181

Fig:Replicating The data items

5. CONCLUSIONS

In MANETs, due to link failure, network partitions are

common. As a result, data saved at other nodes may not

be accessible. One way to improve data availability isthrough data replication. In this paper, we proposed

several data replication schemes to improve the data

availability and reduce the query delay. The basic idea is

to replicate the most frequently accessed data locally

and only rely on neighbors memory when thecommunication link to them is reliable.

Extensive performance evaluations demonstrate that

the proposed schemes outperform the existing solutions

in terms of data availability and query delay. Results

also show that there is a fundamental trade-off betweendata availability and query delay. Higher degree of

cooperation improves the data availability, but it also

increases the query delay because more data need to be

retrieved from neighboring nodes.

REFERENCES

[1]Data Replication for Improving Data Accessibilityin Ad Hoc Networks, IEEE Trans. MobileComputing,vol. 5, no. 11, pp. 1515-1532, Nov. 2006

[2] Supporting Cooperative Caching in Ad HocNetworks, IEEE Trans. Mobile Computing, vol. 5, no.1pp. 77-89,Jan. 2006.

[3] Benefit-Based Data Caching in Ad Hoc Networks,IEEE Trans. Mobile Computing, vol. 7, no. 3, pp. 289-

304, Mar. 2008

[4] Approximation Algorithms for Data Placement inArbitrary Networks, Proc. 12th Ann.ACM-SIAMSymp. Discrete Algorithms (ACM-SIAM)

[5] Consistency Management Strategies for DataReplication in Mobile Ad Hoc Networks, IEEE Trans.Mobile Computing, vol. 8, no. 7, pp. 950-967

[6] Replica Allocation in Ad Hoc Networks withPeriodic Data Update, Proc. Intl Conf. MobileData Management (MDM),2002.

[7] Data Consistency for Cooperative Caching inMobile Environments, Computer vol. 40,no. 4, pp. 60-

66, Apr. 2007.

[8] Effective Replica Allocation in Ad Hoc Networks

for Improving Data Accessibility, Proc. IEEEINFOCOM,

[9] A Powerful Tool for Building System Models,Proc. 33rd Conf. Winter Simulation


25/148


2013

182

Securing the Wireless Sensor Network Communication

Thaseen Taj1, Shambhu Prasad Sah 2,1

Assistant Professor,Dept of CSE,Don Bosco Institute of Technology,Bangalore ,Karnataka,India

2Assistant Professor, Dept of CSE, Graphics Era Hill University

Bhimtal,Nainital,Uttarkhand,India

[email protected]

[email protected]

Abstract: Wireless sensor networks are a new type of networked

systems, characterized by severely constrained computational

and energy resources, and an ad hoc operational environment.

When wireless sensor networks are deployed in a hostile terrain,

security becomes extremely important, as they are prone to

different types of malicious attacks. Due to the inherent

resource limitations of sensor nodes, existing network securitymethods, including those developed for Mobile Ad-Hoc

Networks, are not well suitable for wireless sensor networks. As

a crucial issue security in wireless sensor networks has attracted

a lot of attention in the recent year. This paper made a thoroughanalysis of the major security issue and implemented the most

secure AES-256 algorithm for effectively securing the network

and hence encrypting and decrypting data transferred between

the nodes in a wireless sensor network.

Keywords: Wireless sensor network; AES; Decryption

Encryption; Initialization Vector; security; threat; attack;

benchmark

I. INTRODUCTION

A. WIRELESS SENSOR NETWORKWireless Sensor Network (WSN) consists of

hundreds or thousands of self organizing, low-power, low cost wireless nodes and is used in avariety of applications such as military sensing and

tracking, environmental monitoring, disastermanagement, etc. But when WSN is deployed inopen, un-monitored, hostile environment [1], or

operated on an unattended mode, sensor nodes will

be exposed to the risk of being captured by anactive adversary. So with the demandingconstraints of nodes limited capability, the keyissue for WSN is designing viable security

mechanisms for the protection of confidentiality,integrity and authentication to prevent maliciousattacks, involved. Besides the inherent limitations

in communication and computing, the deploymentnature of sensor networks makes them morevulnerable to various attacks. Largely deployed

sensor nodes may cover a huge area further

exposing them to attackers who may capture andreprogram the individual nodesas shown in

Fig.1. The adversary may use its own formula of

attacking and induce the network to accept them aslegitimate nodes. Falsification of original data,extraction of private sensed data, hacking of

collected network readings and denial of serviceare also certain possible threats to the security andthe privacy of the sensor networks. Though

hardware and software improvements may addressmany of such security issues, but development of

new supporting technologies and securityprinciples are challenging research issues inWSNs.
mailto:[email protected]:[email protected]


26/148


Fig 1. Scenario of wireless sensor nodes deployment

B. AES SYSTEMAn AES system is a symmetric-key system in

which the sender and receiver of a message sharea single, common key, which is used to encryptand decrypt the message. The data length of a key

or message may be chosen to be any of 128 or 256

bits.The AES encryption/decryption algorithmsare shown in Table AES operates on a 4x4 array

of bytes (referred to as state). The algorithmconsists of performing four different simpleoperations. Those are as follows:

SubBytesShiftRowsMixColumnsAddRoundKey

SubBytes perform byte substitution which isderived from a multiplicative inverse of a finitefield. ShiftRows shifts elements from a given row

by an offset equal to the row number. TheMixColumns step transforms each column usingan invertible linear transformation. Finally, the

AddRoundKey step takes a 4x4 block from aexpanded key (derived from the key), and XORsit with the state.

AES is composed of four high-level steps. Theseare:

1.Key Expansion2.Initial Round

3.Rounds

4.Final Round

The Key Expansion step is performed using

Rijndaels key schedule. The Initial Roundconsists only of an AddRoundKey operation. TheRounds step consists of a SubBytes, ShiftRows,

MixColumns, and an AddRoundKey operation.The number of rounds in the Rounds step variesfrom 10 to 14 depending on the key size. Finally,

the FinalRound performs a SubBytes, ShiftRows,and an AddRoundKey operations.

Decryption in AES is done by performing theinverse operations of the simple operations inreverse order.

The structure of AES is as shown in the figure-2.Hence for the AES algorithm, the length of the

input block and the output block is same. It is apoint to be noted here that no weak or semi-weakkeys have been identified for the AES algorithmand there is no restriction on key selection, only

the Key Expansion routine for 256-bit CipherKeys is slightly different than for 128- and 192-bitCipher Keys. Here in this application we are using

256 bit key AES, in which there are 14 iterationscalled the round key- for being used in the laststage of AES. First three stages are Sub Bytes,Shift Rows and Shift Columns. The design and

strength of all key lengths of the AES algorithm(i.e., 128, 192 and 256) are sufficient to protect

classified information up to the SECRET level.TOP SECRET information will require use ofeither 192 or 256 key lengths.Design of AES is

highly conservative that enables us to demonstrateits security against all known types of active and

passive attacks


27/148


Figure 2. Structure of AES

II. SENSOR NETWORK SECURITY ISSUE

Two of the most security-oriented applications ofwireless sensor networks are military and medicalsolutions. Due to the nature of the military, it is

obvious that the data (sensed or disseminated) is ofa private nature and is required to remain this wayto ensure the success of the application. Enemy

tracking and targeting are among the most usefulapplications of wireless sensor networks in militaryterms. The most up to date work can be found on

the Defense Advanced Research Projects Agency(DARPA) website [2, 3]. The choice of which

security services to implement on a given sensormainly depends on the type of application and itssecurity requirements. Amongst these weexamined:

Authenticity - it makes possible that the messagereceiver is capable of verifying the identity themessage sender, hence preventing that likely

intruder n

Date post:	14-Apr-2018
Category:	Documents
Upload:	karthik-sharma
View:	212 times
Download:	0 times

Wireless Merged.doc

Documents