An Evaluation of Routing An Evaluation of Routing Reliability in Non-CollaborativeReliability in Non-Collaborative

Opportunistic NetworksOpportunistic Networks

Ling-Jyh Chen, Che-Liang Chiou, and Yi-Chao Chen

Institute of Information Science, Academia Sinica

{cclljj, clchiou, yichao}@iis.sinica.edu.tw

Motivation 1/2Motivation 1/2

• Opportunistic Networks:– Network contacts are intermittent– There is rarely an e2e path between the source and the

destination– Disconnection and reconnection are common– Link performance is highly variable or extreme

• Potential Applications– Interconnect mobile search and rescue nodes in disaster

areas– Allow message exchange in underdeveloped areas– Permit scientific monitoring of wilderness areas

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Motivation 2/2Motivation 2/2

• An implicit assumption is usually made in opportunistic networks: all participating peers are collaborative.

• Many schemes proposed for data dissemination are based on the assumption.

• However, there may be uncooperative or malicious peers in the network, and these schemes may be vulnerable.

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Our ContributionOur Contribution

• We identify five types of non-cooperative behaviors: Free Rider, Black Hole, Supernova, Hypernova, and Wormhole

• We evaluate the impacts of non-cooperative behaviors on data transmission performance of three popular opportunistic network routing schemes.

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Type 1: Free RiderType 1: Free Rider

• A type of selfish behavior

• Use the network to forward data, but refuse to serve as a relay for others

• Effects:– Free riders require less memory and energy

than others– Data transmission performance of the

system degrades due to the reduced level of collaboration.

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Type 2: Black HoleType 2: Black Hole

• Drop all relayed data without forwarding to other peers

• Dropping may be:– Intentional– Due to a lack of capability, e.g. limited battery power

or buffer size

• Black holes cause data loss and may significantly degrade the transmission performance

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Type 3: SupernovaType 3: Supernova

• A type of malicious attack that propagates random messages destined to other network peers

• Similar to – Email spamming– Network worms– Denial of service attacks

• The malicious traffic – consume network resources– interfere with the transmission

of regular messages

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Type 4: HypernovaType 4: Hypernova

• A type of malicious behavior that propagates random messages intended for virtual peers that may or may not exist

• The network keeps random messages until – destination nodes are found or– they are dropped due to buffer

overflow• Random messages initiated by

hypernova peers may exist longer than those by supernova peers.

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Type 5: WormholeType 5: Wormhole

• Composed of one black hole and one white hole – Black holes ‘absorb’ data from others– White hole ‘radiate’ data as much as they can

• Effects:– likely to be overloaded– single-point-of-failure– security and privacy

issues

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Evaluation SettingsEvaluation Settings

• Evaluate reliability of three opportunistic network routing schemes:

– Epidemic

– PRoPHET

– HEC-BI

• Simulator: DTNSIM

– A Java-based opportunistic simulator

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Evaluation Settings (cont.)Evaluation Settings (cont.)

• Messages: – generated in the first 10% of the simulation time – with a Poisson rate of 1,800 seconds/message– are 1M Bytes

• Data rate: 2Mbps• Buffer size:

– 1G Bytes for evaluations of free riders and black holes

– 100 Bytes for evaluations of supernova, hypernova, and wormholes

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Evaluation ScenariosEvaluation Scenarios

• Use two realistic wireless network traces:– iMote: collected from 2005 Infocom

conference– UCSD: collected from UCSD campusTrace Name iMote UCSD

Device iMote PDA

Network Type Bluetooth WiFi

Duration(days) 3 77

Devices participating 274 273

Number of contacts 28,217 195,364

Avg # Contacts/pair/day 0.25148 0.06834

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Evaluation I: Free RidersEvaluation I: Free Riders- The results indicates that free riders are very harmful to data transmission in opportunistic networks.

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Evaluation II: Black Hole PeersEvaluation II: Black Hole Peers- Similar to free riders, the results indicates that black holes are very harmful to data transmission in opportunistic networks.

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Evaluation III: Supernova PeersEvaluation III: Supernova Peers- The degradation rates in the supernova scenario are much slower than those in the free rider and black hole scenarios.- The three schemes are more robust against supernova behavior than free rider and black hole behavior.

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Evaluation IV: Hypernova PeersEvaluation IV: Hypernova Peers- The effects of supernova and hypernova are similar.- Hypernova, similar to supernova, has less impact on the data transmission performance than free riders and black holes.

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Evaluation V: Wormhole PeersEvaluation V: Wormhole Peers- Surprisingly, the delivery performance does not degrade as the percentage of wormholes increases.- The results indicate that the three schemes are robust against wormholes, and they can even benefit substantially from wormholes when the network connectivity is poor.

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ConclusionConclusion

• We identify five types of non-cooperative behaviors, namely free rider, black hole, supernova, hypernova, and wormhole.

• We evaluate their impacts on Epidemic, ProPHET, and HEC-BI.

• Data transmission performance degrades significantly as free rider, black hole, supernova, or hypernova behavior increases.

• All three routing schemes are robust against wormhole behavior, and can even benefit from it – especially when the network connectivity is poor.

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Thanks!Thanks!

http://www.iis.sinica.edu.tw/~cclljj/http://www.iis.sinica.edu.tw/~cclljj/

http://nrl.iis.sinica.edu.tw/http://nrl.iis.sinica.edu.tw/

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