Research India PublicationsInternational Journal of Applied Engineering Research

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Zaki Ahmad, Department of Mechanical Engineering, KFUPM,Box # 1748,Dhaharan 31261 Saudi Arabia Area of research/interest: Advanced Materials, Corrosion and Corrosionprotection of materials, Surface Engineering. Rajeev Ahuja, Physics Department,Uppsala University,Box 530, 751 21 UppsalaSwedenArea of research/interest: Computational Materials Science, ElectronicMaterials,Spintronics, High pressure, Dynamics, Melting. Shigeru Aoki, Department of Mechancial Engineering, Tokyo Metropolitan Collegeof Technology, 1­10­40 Higashi­Ohi, Shinagawa­ku, Tokyo 140­0011, JapanArea of research/interest: Random vibration, Seismic response of mechanicalsystem,Approximate analysis of nonlinear vibration, Utilization of vibraion. Osama Badr, Mechanical Engineering Department, Qatar University, P.O. Box2713, Doha,Qatar Sayavur I. Bakhtiyarov, New Mexico Institute of Mining and Technology,MechanicalEngineering Department, 122 Weir Hall, 801 Leroy Place, Socorro, NM87801­4796, USAArea of research/interest: non­Newtonian fluid mechanics, heat and masstransfer,rheology, metalcasting, materials processing, multiphase flows. Fatma Abou­Chadi, Head of the Dept. of Electronics and CommunicationsEngineering,Faculty of Engineering, Mansoura University, Egypt Ching­Yao Chen, Dept. of Mechanical Engineering, National Yunlin University ofScience & Technology,University Road, Touliu, Yunlin, Taiwan, 640 R.O.C. Area of research/interest: Biofluid mechanics, thermo­fluid mechanics,Magnetic fluids, Computational fluid dynamics. G.Q. Chen, Department of Mechanics and Engineering science, PekingUniversity,Beijing 100871,China CFD(Computational fluid dynamics),energy andresources engineering, and systems ecology. B.T.F. Chung, Department of Mechanical Engineering, University of Akron, Akron,

Ohio 44325, USAArea of research/interest: Heat Transfer with Phase Changes, Optimum Designof Extended Surfaces, Radiative Heat Transfer System, Heat Transfer in Polymers. Tariq Darabseh, Mechanical Engineering Department, JUST P.O. Box 3030 Irbid­22110 Jordan Nihad Dib, Electrical Engineering Department JUSTP. O. Boc 3030, Irbid 22110JordanArea of research/interest: Computational Electromagnetics, Microwave Circuits,Antennas. Marcelo J.S. De Lemos, Departamento de Energia ­ IEME, Instituto TecnologicodeAeronautica ­ ITA, 12228­900 Sao Jose dos Campos ­ S.P. ­ Brazil .Area of research/interest: Turbulence Modeling, Porous Media, Combustion inPorous Media, Numerical Methods, Finite Volume. Mohammed Salifu, Associate Professor of Transport Engineering & HeadDepartment of Civil Engineering Faculty of Civil and Geomatic Engineering Collegeof Engineering Kwame Nkrumah University of Science and Technology (KNUST)University, Post Office Kumasi, GHANA Dimitris Drikakis, Head of Aerospace Sciences Department, Cranfield University,School of Engineering, Cranfield, Befordshire, MK43 0AL, United KingdomArea of research/interest: Computational Fluid Dynamics, Aerodynamics,Turbulence Gas dynamics, omputational Nanotechnology, Microflows BiofluidMechanics, Transport Phenomena. M.R. Eslami, Department of Mechanical Engineering, Amirkabir University ofTechnology, Hafez Ave. Tehran, 15914 IranArea of research/interest: thermoelasticity, plasticity, cyclic loading, structuralinstability, buckling. A.S. Al­Harthy, Department of Civil, Surveying and Environmental Engineering,University of Newcastle, Callaghan, NSW 2308 Australia.Area of research/interest: Concrete material and durability, Recyclingconstruction materials, reliability assessment of structures. F. Hayati, Dean, Faculty of engineering, Ajman university of Science &Technology Network, Ajman, UAE Annette Bussmann­Holder, Max­Planck­Institute for Solid State Research,Heisenbergstr. 1, D­70569 Stuttgart, GermanyArea of research/interest: general solid state physics theory and experiment,Emphasis, Superconductivity, ferroelectricity, nonlinear phenomena, organics Naser S. Al­Huniti, Mechanical Engineering Department, University of Jordan,Amman 11942, JORDAN

M.A.K. Jaradat, Department of Mechanical Engineering, JordanUniversity of Science &Technology, Irbid 22110, Jordan S.Z. Kassab, Mechanical Engineering Department, Faculty of Engineering,Alexandria University, Alexandria, 21544 Egypt,Area of Interest : Experimental Fluid Mechanics,Lubrication, Energy,Environment and Pollution. M.Y. Khalil, Nuclear Engineering Department, Faculty of Engineering, AlexandriaUniversity, Alexandria 21544 EgyptArea of research/interest: Radiation measurements and applications, Nuclearmaterials,Nuclear waste management, and radiation damage. Bashar El­Khasawneh, Chairman, Industrial Engineering Department, JUST, P.O. Box 3030, Irbid 22110 Jordan Area of research/interest: Design process and manufacturing­related sciencesand processes, advanced and parallel kinematics machine tools and mechanisms. Y.A. Khulief, Department of Mechanical Engineering, KFUPM Box 1767, Dhahran,31261, KSA Area of research/interest: Dynamic modeling and analysis of multibodysystems with interconnected rigid and elastic Components, Dynamics of impactand intermittent motion, FEM dynamic response analysis of rotating beams &shafts. Kazuhiko Kudo, Laboratory of Micro­Energy Systems, Division of HumanMechanical Systems and Design, Graduate School of Engineering, HokkaidoUniversity, JapanArea of research/interest: Radiative heat transfer analysis, transient analysison surface tension. A. A. Mohamad, Director of Graduate Studies, Dept. of Mechanical andManufacturing Engineering,Area of research/interest: Fluid Flow, Heat and Mass Transfer, Computationalfluid dynamics, computational methods, Porous media, Lattice Botlzmann Method,Molecular Dynamics simulations, Modeling. Multi­phase flows. A. A. Mowlavi, Physics Department, School of Sciences,Tarbiat MoallemUniversity of Sabzever;P.O. box 397,Sabzevar, Iran.Area of research/interest: Nuclear and Medical Physics. Ihab Obaidat, Department of Physics, UAE University, PO Box 17551, Al­Ain,UAE Area of research/interest: semiconductor band engineering andsemiconductor interfaces. H.M. Omar, Department of Aerospace Engineering, KFUPM, P.O. Box # 1794,Dhahran, 31261 Saudi Arabia Area of research/interest: Dynamics and Control of Flight Vehicles, Guidance,

Industrial and Applied Control, Active Vibration Control, Intelligent ControlSystems, and Flight Structure. K.K. Pathak, Scientist & Advisor, Computer Simulation & Design Group,AdvancedMaterials and Processes Research Institute (CSIR), Bhopal 462026 (MP) INDIAArea of research/interest: Computational solid mechanics, metal formingand casting simulations, structural shape optimization, artificial intelligencetechniques. Huihe QIU, Department of Mechanical Engineering,The Hong Kong University ofScience and Technology, Clear Water Bay, Kowloon Hong KongArea of research/Interest: Transport phenomena in microscale multiphaseflows,mciro sensors and actuators, optical diagnostics and instrumentation. K. R. Rajagopal, Forsyth Chair Professor, Department of MechanicalEngineering,Texas A&M University, 3123 TAMU, College Station TX 77843­3123,U.S.A D. Ramkrishna, Associate Head School of Chemical Engineering, PurdueUniversity, IN 47907­2100 USAArea of research/Interest: application of mathematics to solving problems inchemical and biochemical reaction engineering. Allan Runstedtler, Natural Resources Canada, CANMET Energy TechnologyCentre­ Ottawa, 1 Haanel Drive Ottawa, Ontario K1A 1M1 Canada Thermal radiation heattransfer, Computational Fluid Dynamics modeling of combustion, Design ofcombustion and heat transfer systems. Ismail Shahin, Electrical and Computer Engineering Department, University ofSharjah, P. O. Box 27272, Sharjah, United Arab EmiratesArea of research/Interest: Ashraf Shikdar, Department of Mechanical & Industrial Engineering, S.Q.University,P.O Box 33, Al­Khod 123 Oman Area of research/Interest: Ergonomics/ Human Factors, Worker performance,Occupational Health and Safety. S.A. Soliman, Electrical Engineering Department, University of Qatar, P. O. Box2713 Doha QatarArea of research/Interest: Applications of State Estimation to Electric PowerSystems, Fuzzy and Neural System Applications to Electric Power Systems,Reactive Power Control. Jinho Song, Thermal­hydraulics and Reactor Safety Research Division, KoreaAtomic Energy Research Institute, P.O. Box, 105, Yusong, Taejon , 305­600,KoreaArea of research/Interest: Multi­phase fluid mechanics and heat transfer,nuclear reactor safety, and power plant operation and design.

H.H. El­Tamaly, Chairman of electrical engineering Dept.,Faculty of Engineering,Elminia University, Egypt.Area of research/Interest: Electrical power engineering, Photovoltaic systems,wind energy systems, power electronics. Bassam A. Abu­Nabah, Department of Aerospace Engineering and EngineeringMechanics, College of Engineering, The University of Cincinnati, USAArea of interest: Applied Mechanics, Non­Destructive Testing Techniques, Residual Stresses. B.M. Vaglieco, Istituto Motori, via G.Marconi, 8­80125­ NaplesItalyArea of research/Interest: Combustion process and pollutant formation ininternal combustion engines and combustion diagnostics by optical techniques Dimitri V. Val, Dept. of Structural Engineering and Const. Manag., Faculty of Civiland Environmental Engineering, Technion ­ Israel Institute of Technology, Haifa32000, IsraelArea of research/Interest: structural safety and reliability; analysis, design,and assessment of reinforced concrete and steel structures; probabilistic riskassessment and management. Guo­Xiang Wang, Department of Mechanical Engineering, The University ofAkron, AkronOH 44325­3903 USAArea of research/Interest: Heat and Mass Transfer, MaterialsProcessing,Solidification Theory and Application. Huimin Xie, Dept. of Engineering Mechanics, Tsinghua University, 100084Beijing, ChinaArea of research/Interest: Experimental Mechanics, optical metrology. Mohamed Younes, Mechanical Engineering Department, Faculty of Engineering,UAE University, P.O. Box 17555, Al­Ain, UAE Area of research/Interest: Internal Combustion Engines Fuels, InternalCombustion Engines Cooling, CFD Simulation of Internal Combustion Engines. Ahmed Sahin, Professor of Mechanical Engineering King Fahd University ofPetroleum and Minerals Dhahran 31261, Saudi Arabia Samir Medik, Associate Professor Mechanical Engineering Department King FahdUniversity of Petroleum and Minerals PO Box 155, Dhahran, 31261, Saudi ArabiaMeamer El Nakla, Mechanical Engineering Department King Fahd University ofPetroleum and Minerals P.O. Box 323, Dhahran 31261, KSA Adel Taha Mohamed Abbas, Associate Professor of Computer Aided Design &Manufacturing Mechanical Engineering Department, College of Engineering KingSaud University Riyadh, Saudi Arabia, 11421, Wan Aizan Wan Abd Rahman, Associate Prof. Department of PolymerEngineering , Universiti Teknologi Malaysia , Skudai, Johor, Malaysia

Prof Dr Zulkifli Yusop, Dean of Research Water Research Alliance UTM, Skudai,Johor, Malaysia Tachtouch Bourhan, Department of Thermofluid Science. King Fahd University ofPetroleum and Minerals. Dhahran 31261, Saudi Arabia Abdul Razak Rehmat, Associate Prof. Department of Polymer Engineering ,Universiti Teknologi Malaysia ,Skudai, Johor, Malaysia M. A. Habib, Professor, Mechanical Engineering Department,King Fahd Universityof Petroleum and Minerals.Dhahran 31261, Saudi Arabia. Fahd A. Alturki, Dean of College of Engineering (Majmaah University) AssociateProfessor of Intelligent Systems And Control Engineering King Saud University P.O. Box 800, Riyadh 11421, Saudi Arabia Prof. Abdullah M. Al­Shaalan, EE department College of Engineering P.O. Box800 King Saud University Riyadh­11421 Kingdom of Saudi Arabia Mir Iqbal Faheem , Professor & Head Dept. of Civil Engineering Deccan Collegeof Engineering & Technology Darussalam, Near Nampally Hyderabad (AP)500001IndiaM. Venkata Ramana , Microscopy and Nano Tech Laboratory Dept. ofMetallurgical and Materials Engineering Indian Institute of Technology MadrasChennai 600 036, India Srinivas ManthaDean ­ School of Engineering & Technology and Professor ­ ECEDepartment, Centurion University of Technology and Management, R. Sitapur,Uppalada, Paralakhemundi, Gajapati Dist, Orissa. 761 211 India. Damodar Maity, Civil Engineering Department Indian Institute of TechnologyAssociate Professor, Civil Engineering Department Indian Institute of Technology,Kharagpur, West Bengal, India ­ 721302. West Bengal Kharagpur 721302 India Area of research/Interest:Damage Assessment of Structures; SeismicResistant of Structures; Fluid­Structure Interaction; Sloshing; Concrete GravityDam. Sellakkutti Rajendran, School of Mechanical and Aerospace Engineering,Nanyang Technological University Nanyang Avenue, SingaporeArea of Interest: Finite Element Method, Meshless Method, FE­MeshreeMethods,Mechanical Vibrations Giriprasath Gururajan, Bartlesville Technology Center,ConocoPhillips CompanyOklahoma, Bartlesville, USA.Area of Interest: Polymer, Vibrational Spectroscopy, Electrospinning, Polymer characterization. Ram Shanmugam, School of Health Administration Texas State University ­San

Marcos University Drive, San marcos, TX 78666, USA. Mohammad Luqman, Chemical Engineering Department King Saud UniversityChemical Engineering Department, Riyadh, Saudi ArabiaArea of Interest: Polymer Nanocomposites ,Polymer/Plastic, Ionomers,Nanocomposites, Blends, Water Treatment, Plasticizers, Additives, ElectroactiveMaterials, Smart Materials, Fuel Cell, Lithium Ion Battery, Sensors, Actuators,Artificial Muscles, Membranes, Conducting Polymer, Biocompatible,Drug Delivery. Assoc. Prof. Dr. Chee­Ming Chan, Faculty of Engineering Technology, UniversitiTun Hussein Onn Malaysia, 86400 Batu Pahat, Johor, MalaysiaArea of Interest: Sustainable Development, Soils, Foundations, Geomaterials,Ground Improvement, Engineering Education, Leadership, Higher Education Dr. P. Rathish Kumar, Civil Engineering Department, National Institute ofTechnology (NIT) Warangal­506 004, Andhra Pradesh, IndiaArea of Interest: Alternate/New Building Materials, Recycling of concrete, SelfCompacting Concrete, Structural Dynamics, Earthquake Engineering, StructuralHealth Monitoring, Ferrocement and Fibrous Concretes. Mohammad Valipour, Department of Irrigation and Drainage Engineering,College of Abureyhan, University of Tehran, Pakdasht, Tehran, Iran­1675755936Area of Interest: Surface and pressurized irrigation, Drainage engineering,Relationship between energy and environment Agricultural water management,Mathematical and computer modeling and optimization Water resources,Hydrology, Hydrogeology, Hydrometeorology, Hydro informatics, HydrodynamicHydraulic, Fluid mechanics, Heat transfer in soil media Prof. Swapnadip De, Department of Electronics and Communication Engineering(ECE), Meghnad Saha Institute of Technology, Nazirabad, East Kolkata Township,West Bengal, India.Area of Interest: VLSI,Microelectronics,Device Physics. Dr. K.B. Jayarraman, Computer science & engineering Deptt., Professor / headof the Deparment, Manakula Vinayagar Institute of Technology,Kalitheerthalkuppam, Madagadipet, Puducherry, IndiaArea of Interest: Neural Networks, Image Processing, Artificial Intelligence, DataMining & Data Warehousing, Computer Networks Dr. Kishorereddy, Associate Prof. Electrical Engineering, Adama Science &Technology University, Narayanapuram (v&p), Sathupally (MD), Khammam (DT),Andhra Pradesh, IndiaArea of Interest: electronics and communication, vlsi design, signal processing Dr. Najm Obaid Salim Alghazali, Department of Civil Engineering, BabylonUniversity, Hilla, Babylon, IraqArea of Interest: Hydraulic Structures, Hydraulics, Engineering Hydrology,Groundwater Hydrology, Dams Engineering (Concrete, Earth, etc.), WaterResources Statistics, Dimensional Analysis, Hydraulics Modeling, Seepage underHydraulic Structures, Water Storage Tanks, Simulation and Modeling, Irrigation,Optimization, General Water Resources Engineering, Numerical Methods and FiniteElements in Civil Engineering. Dr. Shrikant Tiwari, Department of Computer Science & Engineering, Faculty ofEngineering & Technology (FET), Shri Shankaracharya Technical Campus, BlockNo. 15/B, Street No. 29, Sector­07, Bhilai Nagar, City: Bhilai, District: Durg,Chattisgrah, IndiaArea of Interest: Biometrics, Image Processing, Computer Vision, ComputerGraphics, Pattern Recognition R. Manikandan, Department of ICT, School of Computing, SASTRA Universtiy,

Thanjavur, Tamil Nadu, IndiaArea of Interest: Data Mining,VLSI Physical Design,Computer Networks,Embedded systems. Sushant K. Singh, Doctoral Assistant, Earth and Environmental StudiesDepartment, Montclair State University, New Jersey, USA, 1 Normal Avenue,Montclair State University , 358N ML, Montclair, 07043, New Jersey, USAArea of Interest: Environmental pollution, Environmental management,Environmental toxicology, Environmental decision­making, Environmental policy,Waste management, and Sustainability Science. Dr Umashankar S, School of Electrical Engineering, VIT University, Vellore,Tamilnadu, IndiaArea of Interest: Power electronics applications in wind and solar energy,electrical drives and control, smart grid and power quality R. Manikandan, ICT Department, School of Computing,SASTRA Universtiy,Thanjavur, Tamil Nadu, IndiaArea of Interest: Data Mining,VLSI Physical Design,Computer Networks,Embedded systems

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International Journal of Applied EngineeringResearch (IJAER)

Volume 9, Number 23 (2014) CONTENTS CBACCN: Constraint Based Community discovery Complex Networkspp. 18115­18127Soumita Seth , Debnath Bhattacharyya, Tai­hoon Kim

Association Itemsets Discovery Considering Strategic Importance: WAARMpp. 18129­18139Jin Gyu Shin, Doug Won Choi

Electronic Resource Management using Cloud Computing for Librariespp. 18141­18147R.S.M. Lakshmi Patibandla and K. Santhi Sri

The Effect of Creativity Education in Korean ‘Model Schools’ on Creativitypp. 18149­18158Kyung­hwa Lee, Kyoung­hoon Lew

A Study on Optimization Algorithm for Data Driven Architectural Designpp. 18159­18166Jin Ho Park And Woo­Hyoung Lee

Development of Standard Work Process Model for Defect Consulting onKorea ApartmentHousingpp. 18167­18174Junmo Park Woo­Hyoung Lee

Study on the bearing capacity of waveform Micropile using jet grouting methodpp. 18175­18182Young­Eun Jang

A Study on the Maintenance Direction of Waterfront for Urban Regeneration: Focused onUrban­Rehabilitation Strategies and Planning Factorpp. 18183­18190Won Chul Lee

Analysis of the current state in order to maintain the function of the communicationbuildings for maintaining function in emergencypp. 18191­18198Gyeongmok Nam

Explicit Reanalysis Approach due to Modification of Structural Memberspp. 18199­18206Hee­Chang Eun,Young­Jun Ahn,Seung­Guk Lee,In­Baik Lee

Comparison of Ultrasonographic Architectural Properties of Muscles and Balance AbilityBased on the Spasticity of Chronic Stroke Patients

pp. 18207­18214Tae­Gon Kim,Gi­Do Kim,Chan­Hun Choi,Kyung­Yoon Kim

Applicable Natural Staining by Sophora japonica L.and Phellodendron amurense Ruprecht pp. 18215­18222Suk­Yul Jung and Su­Youn Park

Algorithm for Reduction of System Order using Fast Rationalized Haar Transforms in TimeDomainpp. 18223­18230Joon­Hoon Park

Simplification of High Order Transfer Function using General Block Pulse FunctionsandTransforms in Frequency Domainpp. 18231­18239Joon­Hoon Park,Ryum­DuckOh

The Effect of Theme Based STEAM Activity Programs on Self Efficacy,Scientific Attitude,and Interest in Scientific Learningpp. 18241­18246Young­Tae Kong, Sun­Chen Huh, Hui­Ju Hwang

The Implementation of STEAM Program about Pollution in Senior High Schoolpp. 18247­18254Young­Tae Kong

Structural Analysis of Class Satisfaction by Internet Protocol TVpp. 18255­18261Hyunwook Kim and Joungmin Km

Acoustic Echo Cancellation Techniques for Far­End Telephony Speech Recognition inBarge­In Situationspp. 18263­18271JongHanJoo,Jung Hoon Lee,Young Sun Kim, Seung Ho Choi(Corresponding author),Se JinChang

Constructing an Advanced Selection Mechanism in Evolutionary Optimizationpp. 18273­18280Don­Kyu Lee, Chang­Wook Han

Study on Finding Hidden Pet Game for Children Using Motion Cognition Technologypp. 18281­18288Hyun Yi Jung,Hyunggi Kim

Farming related Symptoms among Korean Farmers and their Quality of Lifepp. 18289­18294Myoung­Hee Kim

One­hand texting usability with iPhone 5 Touch­screen keyboard vertical positionpp. 18295­18302Calvin Jeongheon Lee,Hye Jin Kum,Hyoung­taek Lim,Frank Biocca

A Study of the Antenna Design for a 2.4Ghz/5Ghz Dual Band Wireless Communicationpp. 18303­18308Sun­Yeob Kim, Jae­Wan Park, and Jung­Chul Lee

PSO Based Automatic Tuning of Relevant Tuning Parameters For Model Predictive Controlpp. 22313­22324S.Sivananaithaperumal,S.Sivananaithaperumal

Modified Firefly Algorithm For Selective Harmonic Elimination In Single Phase MatrixConverterpp. 22325­22336P.Subha Karuvelam, Dr.M.Rajaram

An Efficient Method To Automatic Intelligent Based Search Engine In Health Care CloudData Using C­Means With Neuro Fuzzy Systempp. 22337­22350R.Kavitha, R.Nedunchelian

Ethical Reckoning Among Teen Populacepp. 22351­22360Dr. K. Vasanthi Kumari,Ms. P. Suganthi,Ms. E. Sharanya

Spot Selection Technique Based Adhoc on Demand Distance Vector Routing (SSRP) ForQos Improvement In MANET Using Mobility Tracespp. 22361­22372G.Kavitha,Dr.J.Sundararajan,

Network Performance Improvement Using Fuzzy Genetic Based Aodvpp. 22373­22383N.K. Kuppuchamy R.Manimegalai

Implementation of Power Restoration Using Q­Algorithm In JADEpp. 22385­22393Anisha. K, Rathina Kumar.K

Cooperative Diversity Pathsselection Protocol Withmulti­Objective Criterion In WirelessAd­Hoc Networkspp. 22395­22407Nyoman Gunantara, Nyoman Putra Sastra, Gamantyo Hendrantoro

Implementation of a Sensor Web Service for Environmental Pollution Monitoring usingWireless Sensor Networks –A Test Bed Approachpp. 22409­22422M. Bhargava Rama and K. Raghava Rao

Study of Tool Wear and Chip Morphology in Turning Ti­6Al­4V Alloy under CryogenicCoolingpp. 22423­22434M. Dhananchezian , M. Pradeep kumar, S. Rajesh

A Detailed Study of Data Replication Techniques in MANETpp. 22435­22445S.Senthilkumar and J.William

Enhancing Security of Modified RSA Algorithmpp. 22447­11455Akashkumar Shushilkumar Goel, Dhananjay Puglia, Salpesh Lunawat,Yaswanthkopparthi, P.M.Durai Raj Vincent

Design of TEDS using IEEE 1451.0 standard for Sensor characterization and application,and implemented in VLSI using Verilog Modelpp. 22457­22469D. JamunaRani

Modeling of Photovoltaic Switched Inductor Z Source Multilevel Inverter Effective OfPower Factor Controlpp. 22471­22488Sam Alaric, Caroline and Suresh Manic

A Survey On Test Case Generation From UML State Chart Diagramspp. 22489­22499Priya. T and Dr. M. Prasanna

A Security Framework For Fault Node Detection In Wireless Sensor Networkpp. 22501­22510K. Rajasekaran and Dr. Kannan Balasubramaian

Real and Reactive Power Optimization by effective placement of various FACTScontrollerspp. 22511­22521Dr. E. Nandakumar and Dr. R. Dhanasekaran

Detection and Prevention of Malicious Nodes ON and OFF the Route in Wireless SensorNetworkspp. 22523­22538Muthumayil K,Manikandan S,Rajamani V

Performance Improvement of Combined Cycle (Dual pressure HRSG) Using MechanicalRefrigeration Systempp. 22539­22550Lord Jaykishan Nayak and Dhaneshwar Mahto

Comparative Analysis On MPPT Algorithms For Standalone PV Systempp. 22551­22564M .Muthuramalingam and P.S.Manoharan

Routing in Delay Tolerant Network using Ant Colony Optimizationpp. 22565­22573K. Sabeetha and A. Vincent Antony Kumar

Design, Implementation and Optimisation of HInfinity Controller for a Microgridpp. 22575­22596A.Sheela and Dr. S.Vijayachitra

Cloud point extraction of Congo red dye from water sample using Triton X­114 asNonionic surfactant by batch and continuous processpp. 22597­22612M.D.Duraimurugan alias Saravanana and Appusamy Arunagiri

Compression of Hyperspectral Images Using Maco With Radon Transformationpp. 22613­22628S.Thiyagarajan, Dr D.Gnanadurai, S.Malathi

International Journal of Applied Engineering Research ISSN 0973-4562 Volume 9, Number 23 (2014) pp. 22395-22407 © Research India Publications http://www.ripublication.com

Cooperative Diversity Pathsselection Protocol Withmulti-Objective Criterion In Wireless Ad-Hoc Networks

1Nyoman Gunantara, 1Nyoman Putra Sastra, 2Gamantyo Hendrantoro

1Department of Electrical Engineering Universitas Udayana, Bali

2Department of Electrical Engineering Institut Teknologi Sepuluh Nopember, Surabaya

Abstract

Relay selection plays a very important role in wireless ad hoc networks. Wepropose a cooperative diversity protocol as simple and easy to understand with multi-objective cross-layer criterion by considering the condition of source-to-destination (S-D) linkand employing amplify-and-forward (AF) relays. The proposed protocol guarantees full diversity based on scalarization of the two-objective criterion with root mean square (rms) normalizationto gain fairness. The two objectivesinclude signal-to-noise power ratio (SNR) and load variance. Simulation results show that the proposed protocol giveshigher SNR than a single-objective protocol that does not consider the S-D link conditions. The proposed protocol results in an improvement of 3.03 dB in SNR and is likely to result in cooperative diversity configuration involving two parallel relays. In addition, the load variance achieved by applying the proposed algorithmindicates more evenly distributed traffic load. Keywords: relay selection, algorithm protocol, full diversity, amplify and forward, multi-objective criterio, rms, scalarization, SNR, load variance.

Introduction Nodes in ad hoc networks having no infrastructure have limitations in terms of transmission range and battery capacity[1]. To overcome these limitations, cooperative technique can be adopted. Cooperative communication is a system where the source nodes cooperate and coordinate with other nodes serving as relays toreach the destination node. Cooperative communication using a single antenna in multi-node scenarios can take benefit of the transceiver and antenna system of each node so that it can create cooperative diversity system, and in a way,adopting the advantages of

22396 Nyoman Gunantara

multi-input multi-output (MIMO) [2] systems. Consequently, cooperative diversity can improve the transmission quality. To implement cooperative diversity in wireless ad-hoc networks, it needs protocol and criteria that must be met in communication from source to destination. For example, the authors in [3] propose a simple protocol of cooperative diversity for configuration consisting of source-to-destination and source-relay-destination paths. With this protocol, problems arise when the signal from the source to destination can not be received well due to bad quality of the radio link so that the direct transmission fails. In this case, full diversity can not be achieved and the cooperative system performance degrades. This problem can be mitigated by checking the performance of the source-to-destination link prior to the cooperative diversity phase, so that the system can be enhanced to achieve full diversity, which is explored in our paper. Relay or path selection in cooperative diversity can be done depending on various criteria. For instance, path selection in cooperative diversity can be done based on SNR [4] - [7], outage probability [8] - [10], mutual information [11], and symbol error rate [12]. However, these papersimplement cooperative diversity using single-objective criterion. It is thought thatpath selection in cooperative diversity needs to consider a combination of multiple criteria to achieve multiple goals simultaneously. Our paper proposes a cooperative diversity protocol with cross-layer multi-objective criterion involving prediction of the performance from the source to the destination in advance so that the right decision on the configuration taken can be made and full diversity can be achieved. Multi-objective criterion used areSNRand load variance. The first are related to the physical layer, while the second is a network layer problem [13]. Path selection in multi-objective can be achieved by using Pareto and scalarization methods. Based on the computation time, scalarization method takes less time to perform simulation compared with Pareto method[14]. Therefore, the completion of a multi-objective criterion in the protocol of cooperative diversity in this research appliesscalarization method. In thescalarization method, each objective is weighted and normalized. Normalization with priorityscale tends to separatethe primary objects and ignore other objects[15]. In this paper, normalization is made to the root mean square (rms) to provide fairness among theobjectives. As previously stated, the best path pair in our study is obtained based on a criterion consisting of twoobjectives, namely SNRand load variance. SNR values obtained with proposed algorithm is found to provide improvement of 3.03 dB over the single-objective protocol proposed in [3]. Our algorithm also guarantees full diversity of the proposed protocol. Section II of this paper describes the formulation of the three-objective problem. Section III describes model of the ad-hoc network and protocols used in our study. Section IV describes theparameters and simulation results and closed with conclusions in SectionV. Formulation of Multi-Objective Criterion The relay selection isbased on combination of two criteria, namely SNRand traffic load variances for each possibility of cooperative configurations. The formulation of those

Cooperative Diversity Pathsselection Protocol Withmulti-Objective et.al. 22397

two criteria and scalarization for the combinationis explained below. There are five possible outcomes of path selection, namely S-D only, S-R-D only, S-D and S-R-D, S-R1-D and S-R2-D, and no connection. The possibilities of path selection results can be seen in Fig. 1. SNR If transmission rate푟 is desired, channel capacity of 2푟is required for packets sent by S to be successfully received in D. The requirement can be expressed as follows [16]:

2푟 ≤ 푙표푔 (1 + 훾 , ) (1) Equation (1) can also be written as follows:

훾 , > 2 − 1 (2)

Figure 1: Possibilities of Path Selection Results If this condition is not fulfilled then the direct path of S-D is deemed not eligible, or 훾 , < 2 − 1 (3)

The success of communication with S-D and S-R-D configuration with AF relay channel capacity is determined by the value of the spectral efficiency 푟. Channel capacity of the AF method can be calculated by the following equation:

퐶 = log(1 + 훾) (4)

22398 Nyoman Gunantara

= log 1 + 훾 , + 훾 ,

= log 1 + 훾 , + , ,

, ,

Based on equation (4), the channel capacity can reach the optimal value if the value훾 , is also optimal. It can be concluded that to reach a value 훾 , , it requiresthe selected relay to provide the optimal value. The best relay is given by the optimal value 훾 . Mathematically, it can be written as [3]:

훾∗ =arg max , ,

, , (5)

where the sign *denotes the optimal value. Load Variance Load variance isthe variance of traffic loads of all nodes, which isinversely proportional to the load balance or fairness [17].In ad-hoc wireless networks, load balance is very important because some nodes may have a greater chance to become a relay. In a path pair where node 푖 is used as a relay thenthe traffic load of node 푖becomes:

퐵 = 퐵 + 퐵 (6)

where퐵 and퐵 arethe own traffic load of and the traffic cominginto node 푖 , respectively. After the load of each node is known then the load variance caused by the selection of a pair ofdiversity pathscan be reviewed for all nodes in the path pair. The load variance value can be determined by following equation [17]

푉 =1푁 퐵 − 1

푁 퐵 (7)

Scalarization Inscalarization method, all criteria are combined into a scalar form by givinga weight to each objective. Minimizedfunction is given a negative sign, while the maximized function is given a positive sign. In this research,every objectiveis normalized to their own rms value to gain fairness. Scalarization of the above twoobjectivesbecomes:

퐹 =푤 훾

퐸(훾 )− 푤 푉

퐸 푉 (8)

where퐹denotes the fitness function, 훾 , 푉 are the objective functions, and 푤 , 푤 denote their respective weights. The values of훾 , 푉 are respectively calculated by equation(5) and(7). Weights 푤 ,푤 can berandomly determined, selected,or changed gradually and periodically[18]. In our study, 푤 and 푤 areset 1/2.

Cooperative Diversity Pathsselection Protocol Withmulti-Objective et.al. 22399

So, theoptimalrelaycan be calculatedby the following equation: 푅 = arg max 퐹 (9)

System Model and Protocol In this study, each node can act as a source (S), relay (R), and destination (D). Properties of the system model are:

• Each node uses a single antenna with omni-directional radiation. • AF relaysare used in cooperative communication. • The packet delivery is half-duplex. • Transmission isdivided into direct transmission phase and one or more phases

of cooperative transmission. • Source and relayshave equal transmit power P. • Distance power law is used for the path loss model with influence of

lognormal shadowing [14]. • Thenoise is AWGN with 푁 variance.

We assume that in this protocol each node alternately broadcasts information on the received powersfrom other nodes and traffic load so that everyone knowsthe received powers of each other in the form of a table. Communication protocol is startedby the source broadcasting initiation packets. Decisions on the quality of S-D is determined by equation (2),whereas the best relay selection is done through equation (5). The protocol is the result of one of three possibilities, namely diversity, no diversity, and no connection. The cooperative diversity protocol can be explained by the flowchart in Fig. 2. Pseudocodefor the flow chart can be divided into three parts: the mainprogram, the one dual-hop procedure, and the two dual-hop procedure. Starting withthe packet broadcast by S,the S-D performance is checked. If훾 , > 2 − 1,then the one dual-hopprocedure isexecuted. Otherwise, if훾 , < 2 − 1then the two dual-hop procedure is selected. This process can be seen in AlgorithmI. If the decision is made that the S-D link quality is good, i.e.,훾 , > 2 − 1, the route of direct transmission and cooperative is formedthroug 푟표푢푡푒1 = [푆,퐷] and

Algorithm I: Main program Begin S transmit If 훾 , > 2 − 1Then Procedure one dual-hop Else If 훾 , < 2 − 1 Then Procedure two dual-hop End End End

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푟표푢푡푒(푖, : ) = [푆, 푖,퐷] for 푖 = 1:푁, 푖 ≠ 푆, 푖 ≠ 퐷 . After that, relay selection is done based on multi-objective criterion in equation (10). The result is either diversity through 푝푎푡ℎ_푝푎푖푟푠or no diversity through 푟표푢푡푒1. This process can be seen in Algorithm II. If the decision is made thatthe S-D quality is not sufficiently good, i.e., 훾 , <2 − 1 , then the cooperative route is formed through 푟표푢푡푒(푖, : ) = [푆, 푖,퐷] for 푖 = 1:푁, 푖 ≠ 푆, 푖 ≠ 퐷. After that,the second relay selection is done based on multi-objective criterion in equation (10). The result can be diversity through 푝푎푡ℎ_푝푎푖푟, or no diversity through 푠푒푙푒푐푡푒푑_푟푒푙푎푦1, or no connection. This process can be seen in Algorithm III.

Algorithm II: Procedure one dual-hop Begin //decision by 훾 , > 2 − 1 //direct route route1=[S,D] //cooperative route For i=1:N, i≠S, i≠D route(i,:)=[S,I,D]; End //multi-objective criterion

훾 =훾 , 훾 ,

훾 , + 훾 , + 1

푉 =1푁 퐵 − 1

푁 퐵

//scalarization of multi-objective criterion

푟푒푙푎푦 = arg max

⎝

⎛ 푤 훾

퐸(훾 )− 푤 푉

퐸 푉 ⎠

⎞

//best 1 relay If best1relay =1 Then diversity Else no_diversity End End //diversity [y,I]=sort(relay,’descend’) selected_relay=relay(I(1),:) path_pairs=[SD] selected_relay1 //no diversity route1 End

Cooperative Diversity Pathsselection Protocol Withmulti-Objective et.al. 22401

Algorithm III: Procedure two dual-hop Begin //decision by 훾 , < 2 − 1 //cooperative route Fori=1:N, i≠S, i≠D route(i,:)=[S,i,D]; End //multi-objective criterion

훾 =훾 , 훾 ,

훾 , + 훾 , + 1

푉 =1푁 퐵 − 1

푁 퐵

//scalarization of multi-objective criterion

푟푒푙푎푦 = arg max

⎝

⎛ 푤 훾

퐸(훾 )− 푤 푉

퐸 푉 ⎠

⎞

//best 2 relays If best2relays = 2 Then diversity Else If best2relay=1 Then no_diversity Else no_connection End End End //diversity [y,I]=sort(relay,’descend’) selected_relay1=relay(I(1),:) selected_ relay2=relay(I(2),:) path_pairs=selected_relay1selected_relay2 //no diversity selected_relay1 End

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Numerical Results Simulation parameters are adopted from the application of WLAN in ad-hoc wireless networks as shown in Table I. The ad-hoc network model used consists of one source, one destination, and multiple other nodes that are possible relays. All nodes are in an open space with an area of 100m×100m. S broadcasts a data packet to D assisted by other nodes. In this study, 30 nodes are defined each having the same opportunity tobe a relay. To simulate load variance calculation, it is assumed that besides the source sending data to the destination there are five other nodes simultaneously transmit data to theirrespectivedestinations. As a result, there are some nodes having a better chance to be a relay because they have relatively lower traffic load. In our example, five pairs of source and destination nodes use paths 4-12-31, 7-11-25, 10-19-23, 16-12-2, and 25-20-6. It is assumed that the sources, namely, node 4, 7, 10, 16, and 25 transmit data respectively at 3, 8, 7, 2, and 11Mbps. While the other nodes are assumed to have random load of 2, 7, 12, or 17.

*) : Power receivedby Dfrom S is calculated by D and then fed

back to S **) : Computed by each possible relay R and further checked by

S. ***) : Computed from (9). ߛ௦, is calculated by each R and

checked by S, whileߛ,ௗis calculated by D and checked by each R.

Figure 2: Flow Chart of Cooperative Diversity Protocol

Fig. 3 illustrates one example of the simulation results. The 'square' signs markthe source S and destination D under consideration, whereas 'star' indicates that the node is active or in communication with other nodes, and a 'circle' marks a node.

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The optimal relay pair selected in this simulation are (1-19-32) and (1-21-32) with SNR of 29.47 dB obtained using the proposed protocol was. The SNR obtained from the single-objective protocolas in the paper [3], which does not consider the condition of SD,is 27.53 dB, whereas the SNR for S-R-D configuration only is 25.03dB, and that for S-D only is 13.27dB.Whereasthe load variance is 48.36 Mbps2.The selectedpath pair can be seen in Fig. 4.

Table 1: Parameters of Simulation

Parameter : Value Path loss exponent , ∝ : 4 Standard deviation of shadowing, 휑

: 8 dB

Power Transmit, 푃 : 1 W Transmit antenna gain, 퐺 : 2 dB Receive antenna gain, 퐺 : 2 dB Frequency, 푓 : 2.5 GHz Noise, 푁 : - 101 dBm Spectral Efficiency, 푟 : 4

Mbps/Hz

Figure 3: Ad Hoc Network Model Simulationis performed 1000 times with a random position and load to every node to determine the distribution of each objective and compareit to the single-objective algorithm, the direct transmission (S-D) and the dual-hop (S-R-D). Simulation results are shown in Fig. 5 - 6. The CDF (cumulative distribution function) of SNR obtained through the cooperative diversity protocol can be seen in

0 10 20 30 40 50 60 70 80 90 1000

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node

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Fig. 5. From Fig. 5, it can be explained that the SNR value from the proposed method (marked "MO" in the figure) ranges from 21.01 to 47.05 dB.For comparison, the SNR for the single objective protocol not considering to the S-D condition (marked "SO") ranges from 18.09 to 40 dB.The median difference of SNR between the proposedmulti-objective and the single-objective algorithm is 3.03 dB.For the S-R-D path onlyconfiguration, the SNR ranges from10 to 34.01 dB.While for S-D path only, the SNR ranges from-10 to 23.06 dB with the probability of SNR value above 0 dB being 88.0 %.These results suggest that the proposed protocol produces the largest SNR values among the others.

Figure 4: Best Path Pairs

The CDF of load variance from the simulation is given in Fig. 6. The load variance from the use of the proposed protocol ranges from39.23 to 51.17 Mbps2. As a comparison, load variancesare also shown for the single-objective protocol and for the S-D path only configuration. Load variance produced by the single-objective rangesbetween 38.52and 51.74 Mbps2. While the value of load variance for the case of S-D path only is fixeddue to the absence of changes in the traffic load on each node. Fig. 6 shows the value of load variance with the proposed protocol issmaller than that with the single-objective. It is because the traffic load resulting from the proposed protocol is more evenlydistributed with the application of multi-objective criterion than the traffic load of the nodes with a single objective protocol.

0 10 20 30 40 50 60 70 80 90 1000

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Cooperative Diversity Pathsselection Protocol Withmulti-Objective et.al. 22405

Figure 5: CDF of SNR

Figure 6: CDF of Load Variance Conclusions Based on the analysis of simulation results of the proposed cooperative diversity protocol, several conclusions can be drawn. Firstly, the selection of the best path pair can be done based on a multi-objective cross-layercriterion. In our case, there are two objectives involved, namely, SNRand load variance by applying multi-objective optimization with scalarization. Secondly, the SNR with the proposed algorithm that considers the condition of the direct S-D link is higher than that resulting from the single-objective algorithm that does not consider the condition of S-D. In this case, SNR improvement of 3.03 dB is obtained. Lastly, load variance that results from the proposed protocol is smaller than that resulting from the single objective protocol.

-20 -10 0 10 20 30 40 50 6010

-3

10-2

10-1

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Pro

b[S

NR

<=

absc

issa

]

MOSOSRD onlySD only

38 40 42 44 46 48 50 520

0.1

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Pro

b[Lo

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<= a

bsci

ssa]

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Itindicates that communication with the proposed protocol results in traffic load that is more evenly distributed. Acknowledgement The research work of N. Gunantara has been supported by a HibahBersaing 2014Contract No. 103.63/UN14.2/PNL.01.03.00/2014from the Indonesian Ministry of Education and Culture. References

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