Using Peer-to-Peer Data Routing for Infrastructure-Based Wireless NetworksSethuram Balaji Kodeswaran, Olga Ratsimor,Anupam Joshi, Tim Finin, Yelena Yesha ebiquity.umbc.edu

Using Peer-to-Peer Data Routing for Infrastructure-Based Wireless NetworksSethuram Balaji Kodeswaran, Olga Ratsimor,Anupam Joshi, Tim Finin, Yelena Yesha ebiquity.umbc.edu

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eBiquity Group Technical RootseBiquity Group Technical Roots

IntelligentIntelligentInformationInformation

SystemsSystems

NetworkingNetworking& Systems& Systems SecuritySecurity

AIAIDBDB

SemanticSemanticWebWeb

MobilityMobility

PervasivePervasiveComputingComputing

TrustTrust

PrivacyPrivacy

AssuranceAssurance

Web ServicesWeb Services

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OverviewOverview

• Introduction• Motivation• Network Model• Typical Usage Scenario• Numi Framework Overview• Simulation Results• Sample Application • Conclusion and Future Work• Q&A

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IntroductionIntroduction

• Combining infrastructure and ad hoc communication to meet mobile users data needs

• Mobile devices offer unused resources to support the needs of their peers

• Infrastructure components monitor device mobility and orchestrate utilization of available “excess” resources

• Mobile devices use peer-to-peer interactions to obtain data carried by peers on their behalf

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MotivationMotivation• Widespread use of personal devices• Devices with limited and varying

capabilities• Data-intensive services• Improved ad-hoc capabilities• Expensive cellular WAN connectivity• Increased Popularity of HotSpots

(commercial community networks)• Starbuck’s, Borders, T-Mobile Hotspots,

PersonalTelco, Seattle Wireless, Consume • Islands of high speed network connectivity

separated by areas of no network access

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Network ModelNetwork Model

• Landing Zones are islands of high speed cheap network connectivity around a Service Portal limited only by that portal’s wireless range

• Transit Zones are regions where there is no network connection

• In Landing Zones, mobile hosts communicate with service portals only

• In Transit Zones, mobile hosts communicate with each other

MH1

MH2

LandingZone

Transit Zone

LandingZone

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Network ComponentsNetwork ComponentsService Portals

• Infostations offering high-speed network connectivity and hosting services that can be used by nearby mobile hosts

• Portals use their wireless capabilities to interact with mobile hosts that are in range

• Portals use wireline connectivity to communicate among themselves.

Mobile Hosts• Mobile hosts are wireless mobile devices that can

communicate both with infrastructure and neighboring peer mobile hosts that are within range (ad hoc mode).

Services• Service Agents• Service Data Units• Service Data Volumes

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Typical Usage ScenarioTypical Usage Scenario

Bob

Susan

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Network Component InteractionsNetwork Component Interactions

• Node to Portal Interaction• A mobile host, in a landing zone, can request a set of

new services (upon user's request) or it can ask for additional data for currently running services (transparent to the user)

• Portal to Portal Interaction• Portals notify neighbors of service/data provided to a

passing by mobile node. This ensures that data that would be needed by mobile hosts are properly scheduled to be delivered to them

• Node to Node Interaction• The Node-to-Node interaction is employed by a mobile

host to obtain any additional data from another mobile hosts in transit zones

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Numi FrameworkNumi Framework• Heartbeat Generator Agent

is responsible for broadcasting device presence messages

• Location Monitor Agent is responsible for identifying whether or not that device is currently in a landing zone or a transit zone

• Message Handler Agent is responsible for handling the messaging needs of the framework

• Logger Agent records every interaction that takes place on the local device

Numi Node Framework

Message Handler

Location Monitor

Numi Task Scheduler

Data Handler Agent

Logging Agent

Node Heartbeat Generator

Node Service Manager

Numi Portal Framework

Message Handler

Location Monitor

Numi Task Scheduler

Data Handler Agent

Logging Agent

Portal Heartbeat Generator

Portal Service Manager

Music Service Agent

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Numi FrameworkNumi Framework• Task Scheduler Agent is

responsible for scheduling prescribed tasks at various times

• Data Handler Agent is used for transferring data volumes between MHs and between an MH and an SP

• Portal Service Agents run on top of our Numi platform on SPs and offer services to a user

• Node Service Agent runs within NUMI on an MH offering a service to the user

• Service Manager Agent is responsible for managing service agents on a platform

Numi Node Framework

Message Handler

Location Monitor

Numi Task Scheduler

Data Handler Agent

Logging Agent

Node Heartbeat Generator

Node Service Manager

Numi Portal Framework

Message Handler

Location Monitor

Numi Task Scheduler

Data Handler Agent

Logging Agent

Portal Heartbeat Generator

Portal Service Manager

Music Service Agent

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Simulation EnvironmentSimulation Environment• Simulations conducted using GlomoSim • 802.11 used as MAC protocol• Geographical region considered is 10 sq Kilometers• Node mobility assumed to be piece-wise linear• Numi configuration:

• Node presence interval 8 sec• Node zone refresh interval 1 sec• Portal presence interval 8 sec• Portal zone refresh interval 1 sec• Presence message validity 10 secs• Data Query Manager runs every 100ms to identify next data

segment needed

• Simulated behavior of an application that is non-real time and whose data needs are fairly predictable (example playlist, newspaper, eBooks, etc)

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Simulation ExperimentsSimulation ExperimentsCompared the performance of the following

schemes:• Data Hoarding (DH): Device tries to cache as much data

as needed until it reaches the next portal on its route. If device runs out of data, a service disruption is assumed to occur

• Ad hoc Querying (AQ): Device tries to cache as much data as needed until it reaches the next portal on its route .If device runs out data, device queries its immediate neighborhood for next segment. If query fails, a service disruption is assumed to occur

• Ad hoc Querying with Peer Routing (AQPR): Similar to above scheme but in addition, devices offer their excess capacity to the network portals to use for transporting data segments for other peers

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Service Loss Vs Number of Portals

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

5 10 15

Number of Portals

Per

cent

age

Ser

vice

Dis

trup

tion

Data Hoarding Adhoc Querying Adhoc Querying with Peer Routing

Service Disruption vs Number of Portals

Service Disruption vs Number of Portals

Device capacity < 1MB

Number of nodes 100

Speed < 20 mt/sec

Data segment size < .2 MB

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Service Distruption Vs Nodes in Network

00.10.20.30.40.5

0.60.70.80.9

1

40 80 120 160 200

Number of Nodes in Network

Per

cent

age

Ser

vice

D

istru

ptio

n

DataHoarding Adhoc Querying Adhoc Querying with Peer Routing

Service Disruption vs Nodes in Network

Service Disruption vs Nodes in Network

Device capacity < 1MB

Number of portals 3

Speed < 20 mt/sec

Data segment size < .2 MB

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Loss of Service Vs Mobility Speed

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

10 15 20 25 30 35 40 45 50

Speed (mt/sec)

% o

f Tim

e N

ode

has

Ser

vice

D

ata

loss

Data Hoarding Adhoc Querying Adhoc Querying with Peer Routing

Service Disruption vs Node SpeedService Disruption vs Node Speed

Device capacity < 1MB

Number of nodes 100

Number of portals 5

Data segment size < .2 MB

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Loss of Service Vs Total Universe of Responses

0

0.1

0.2

0.3

0.4

0.5

0.6

20 100 200

Universe of Responses

Per

cent

age

Ser

vice

Dis

rupt

ion

Data Hoarding Adhoc Querying Adhoc Querying with Peer Routing

Service Disruption vs Total Universe of Responses

Service Disruption vs Total Universe of Responses

Device capacity < 1MB

Number of nodes 100

Number of portals 5

Speed < 20 mt/sec

Data segment size < .2 MB

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Service Disruption with Increasing Memory

00.10.20.30.40.5

0.60.70.80.9

1

2 5 10

Memory Available (MB)

Per

cent

age

of S

ervi

ce

Dis

rupt

ion

Data Hoarding Adhoc Querying Adhoc Querying with Peer Routing

Service Disruption vs Device MemoryService Disruption vs Device Memory

Number of nodes 100

Number of portals 5

Speed < 20 mt/sec

Data segment size < .2 MB

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Prototype ApplicationPrototype Application• A Music Jukebox application

that allows a user to listen to his favorite MP3 playlist on his PDA

• Implemented in Java (Personal Java)

• Network Model Used• 3 PCs equipped with 802.11b

wireless LAN cards acting as Service Portals

• 3 iPAQs equipped with 802.11b wireless LAN cards acting as Mobile Hosts

• Web Browser on iPAQ used as User Interface

• Service Portals run Tomcat Servlet Engine for accepting user’s requests

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Mobility CoordinatorMobility Coordinator• We have developed an

additional simulation component called the Mobility Coordinator

• Control messages can be sent to any mobile host to change its current cell ID

• Only messages tagged with the same cell ID that a mobile device belongs to are accepted. Others are dropped

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Conclusion and Future WorkConclusion and Future Work

• Utilize a combination of infrastructure and ad hoc communication to provide uninterrupted services to a user

• Mobile devices offer up excess capacity to the network for supporting peers

• Ongoing work• Group and Multi-hop scheduling • Route deviations and its effects• Optimal Portal Placement strategies• Security and Privacy Issues

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Typical Usage ScenarioTypical Usage Scenario

Portal 1

P 5

P 6

Portal 2

P 4P 3

MH1

MH2