Chapter 14: Incentive-aware opportunistic network routing

1. Routing in Opportunistic Networks Chapter 14: Incentive-aware opportunistic network routing Greg Bigwood and Tristan Henderson University of St Andrews

2. Problem: • Opportunistic networking relies on cooperation between nodes to perform efficiently • Opportunistic routing protocols depend on nodes forwarding messages • Otherwise nodes must delivery directly to recipient • Cooperative forwarding incurs a cost to forwarding nodes • Energy • Storage • Self-interested nodes avoid forwarding cost: • Refuse to pass messages on for other nodes

3. Outline • We discuss attack on opportunistic routing • With a focus on selfishness • We discuss incentive mechanisms for opportunistic routing • Conclude with discussions of outstanding challenges in the area

4. Opportunistic Network Routing • Frequent disconnections • Mobile nodes coming into and out of range • Non-static forwarding paths • A varied set of nodes in range over time • No predictable interaction schedule • Nodes are most likely carried by users with diverse and variable mobility patterns • Nodes must opportunistically use any available nodes for forwarding

5. Cooperation • Opportunistic networking necessarily relies on cooperation to perform efficiently • If all nodes participate, we find the shortest paths • If nodes do not participate in forwarding, we must pass message directly to destination • High latency • Low delivery ratio • Cooperative forwarding involves cost to intermediaries: • Storage of ferried messages • Energy cost of forwarding

6. Selfishness • Selfishness: refusing to forward other nodes messages • Reduces cost for intermediary • Still expect their own messages to be forwarded by others • Harms performance of network

7. Reality Mining Selfishness Simulation • As proportion of selfishness nodes increases, Delivery ratio decreases. Selfishness harms the network.

8. Attacks on Opportunistic Routing • Manipulation of routes • Nodes may alter the delivery path • Selective maliciousness • Nodes may be malicious only under certain circumstances • Selfishness • Nodes messages may not reach destination • Users’ economically rational desire to preserve battery affects their selfishness

9. Selfishness • Opportunistic routing protocols, in particular Epidemic routing and Spray-and-wait routing are vulnerable to selfishness (Panagakis et al). • Once 30% of the nodes in the network are selfish, performance degrades (Keränen et al). • Is there an acceptable amount of selfishness? • What if selfish nodes only forward to the destination, but not other intermediaries? • Is this acceptable?

10. Incentivising Routing Participation • Many approaches in traditional networks • Bartering • Swap messages 1-for-1 • Currency • Purchase credits to give to other nodes in return for their forwarding service • Asynchronous bilateral trading • Nodes perform actions that benefit each other, but not necessarily simultaneously • Watchdog mechanisms • Nodes monitor each others communication to ensure compliance

11. Which are appropriate for Opp Nets? • Bartering = • Not all nodes have equal number of messages to exchange • Currency = • No out of band oracle to administer currency • Watchdog mechanisms = • Not many encounters will be observed by a third party • Asynchronous bilateral trading < • Nodes perform actions that benefit each other, but not necessarily simultaneously

12. What information do we have? • We must rely only on encounters between nodes • Nodes can collect opinion data based on their interactions • Nodes can use collated opinion data to make decisions about the trustworthiness of individual nodes • Encounter tickets • Use PKI to generate provable encounter tickets • Used to prove messages were exchanges and encounters took place

13. How to bootstrap the mechanism? • The incentive mechanism must throughout the entire lifetime of the network • We need a mechanism to generate initial trust opinion data • We can use Self-Reported Social Networks (SRSNs) • Use online social network data or similar out of band data to provide information available before network startup • These SRSN data may correlate with trustworthyness

14. Attack against incentive mechanisms • Exploiting friendship mechansisms • Do not incentivise nodes to add as many other nodes as “friends”. • Increasing trust through epidemic behaviour • Malicious nodes may ignore routing protocols to gain credits/currency/inflated ranking • Tailgating • Generating large numbers of encounter tickets by following nodes • Manipulation of control traffic • Withholding ranking information • Offer non-existent routes

15. Attack against incentive mechanisms 2 • Defamation • Creating false reputation claims to damage other nods • Exploiting detection algorithms • Exploiting grace periods or allowances made for genuine device limitations such as battery failure • Do not encourage nodes to drop old messages (this may be acceptable) • Collusion • Sybil attacks • How do we know a user cannot easily create a new identity

16. IRONMAN: Addressing these concerns • IRONMAN Incentives and Reputation for Opportunistic routiNg in Mobile and Ad hoc Networks (Bigwood et al) • Use SRSN information to bootstrap network • Increase personal ranking of nodes considered friends • Use encounter histories to detect selfishness • No oracles, watchdogs, infrastructure networks nor flooded delivery receipts required

17. IRONMAN Detection Mechanism

18. Incentive Mechanism Performance • Detection Time • The time it takes a mechanism to correctly detect selfish behaviour • Detection Accuracy • The proportion of selfish nodes that were correctly detected as selfish by a mechanism • Selfishness Cost • The proportion of forwarded messages that were generated as a result of a node creating a message while selfish

19. Performance Comparison • Simulation of several popular incentive mechanisms • Epidemic routing over the Reality Mining Trace • We compare the selfishness cost when two proportions of nodes behave selfishly • Nodes have finite buffer, energy and message TTL • IRONMAN greatly outperforms other mechanisms

20. Incentive Summary • By bootstrapping the trust mechanism using SRSNS, and using Encounter histories IRONMAN outperforms existing mechanisms • IRONMAN suited to particular networking constraints in Opportunistic Networks • This demonstrates that Incentive mechanisms designed for opportunistic routing and useful, and motivates future work in this area

21. Challenges For Incentive Aware Routing • User behaviour • Some nodes may behave altruistically except under specific circumstances. Is this acceptable? • How can nodes corroborate information? Exact timings difficult in opportunistic network • Using social-network information • SRSN information has shown to be useful. Can we perhaps classify users based on social network information? • Are opportunistic routing patterns similar to social network communication patterns? • May lead to cross disciplinary research

22. Challenges For Incentive Aware Routing • Cross-layer information use • Many Opportunistic Routing applications might themselves involve social networks. E.g. crowdsourcing and mobile social networks. • Can we use information from the application at the routing layer or (vice versa)? E.g., spammers have their messages dropped? • Modeling social network behaviour • Advanced simulation • Allows for comparison of social networks and network communication networks • Predictive user location may improve routing performance

23. Challenges For Incentive Aware Routing • Academic challenges • Collecting datasets is costly • A lack of datasets is harming research • Datasets are not shared among researches effectively • Metrics for analysing incentive mechanism • No consensus on how best to compare and analyse the incentive mechanisms for opportunistic networks. • What constitutes a fair distribution of forwarding?

24. Conclusions • Incentive mechanisms will be vital for any opportunistic networking deployment • Existing incentive mechanisms from MANETs and DTNs are innapropriate for opportunistic networks • Using SRSN information provides incentive mechanisms with a method of bootstrapping their protocols • There a many challenges left for opportimostic routing, many of which are cross-discipline problems