SelfOrg.Net Control of Ad Hoc Networks using Game Theory

1. SelfOrg.NetControl of Ad Hoc Networks using Game Theory March 8, 2004 Steven M. Hoffberg WSD2004

2. About the Author • Steven M. Hoffberg is a registered patent attorney. He holds SB and SM degrees from MIT, an MSEE from RPI, JD from Cardozo Law School, and spent 3 years in medical school. • Mr. Hoffberg holds 13 patents, 2 of which are relevant to telematics. • Mr. Hoffberg represents clients in a broad range of technologies. • The goal of SelfOrg.Net is to gain support for adoption of advanced protocols for efficient use of unlicensed radio spectrum

3. Disclaimer • SelfOrg.Net is a non-commercial entity with no products or services. • The business plan elements presented herein are intended principally to place the system in proper context. • This project remains a work in progress. • The accuracy of modeling of mobile ad hoc networks is highly dependent on the presumptions used.

4. Predicates for Game Theoretic Analysis • Value function for all agents • Options for each agent • Realistic implementation possibility • Defined performance criteria

5. The Prototype System • Real Time Telematics Information communication system • Multihop n<10 • Multiplexed communications • High reliability communications • Control system timeconstant shorter than node mobility timeconstant • High complexity nodes • Real time sensor datastreams tend toward maximum network load

6. Goals of System • Communicate traffic conditions sensed at each node over distances of 5 miles in “real time”. • Hop distance 100-3000 ft. • 2.4 GHz spectrum • GPS-assisted network architecture determination • Not power constrained • Smart antennas

7. What are the alternatives? • Fixed infrastructure sensors and radio broadcast (asymmetric) • Non-Multihop communications (CB radio) • Cellular infrastructure communications (Cost) • Hotspot/Internet (Coverage)

8. Why do we Need Game Theory • Tragedy of the commons: With an unregulated public resource, each user has an incentive to take, even though if all users take, the resource will be eliminated. • Game theory underlies the theory of regulation, where a benefit is provided to all by limiting or controlling user selfishness. • All rational agents implicitly apply game theory in decision-making; understanding the agent allows optimization of the process.

9. What is Game Theory? • The study of the interaction of independent agents capable of making self-interested decisions based on rational factors • Game Theory requires that the costs and benefits be analytic, and is included within the scope of economic theory. • Game Theory includes auction theory. • In contrast to engineering, Game Theory includes a social element: agents may be given the choice of abstaining from the game, cheating, competing with the game for resources, and may include subjective factors.

10. Comparison of Engineering Analysis and Game Theoretic Analysis • Engineering analysis assumes that the system is “designed”, and operates in accordance with rules and parameters: marketing and business plan are external. • Game Theory provides users with “choice”; optimization of the system provides consistent incentives for users to act accordingly. • Game Theory may be more tolerant to extrinsic effects and market factors. • Game Theory approach may lead to substantially greater complexity and overhead.

11. Collision Sense Multiple Access • Decentralized architecture. • Inferential communication, low overhead. • Good performance below 50% capacity • Unstable at high utilization. • Not robust to selfish behavior.

12. Multihop Ad Hoc Networks • In a multihop ad hoc network, interested nodes assume one of four roles: Source, Sink, Intermediary, and Bystander. • A source node transmits a packet, which is forwarded by one or more intermediaries to a sink node. • A routing table may be maintained in event of a need for transmission, or a suitable route defined on an as-needed basis. • The physical transmission medium has limited capacity and therefore attempted excess usage leads to potential interference. Arbitration of control over transmission on the medium is a required part of the transmission protocol.

13. The Interested Bystander • Bystander nodes must defer to participating nodes during communications by others, and therefore receive no objective benefits during this period. • Intermediary nodes receive no objective benefits, and further incur costs in participating in forwarding packets • How do we create a stable and useful network if there is no incentive to cooperation and non-interference? • Create an economic system with subjective benefits!

14. The Synthetic Economic System • Why synthetic? If the economy is real, then extrinsic wealth can override “fairness” and nodes with less external wealth will have incentive to defect. • Cheating is dis-incentivized because neighbors can perform independent estimates of comparative wealth. • Temporal and spatial relevance can be tweaked, leading to adaptive fairness. • Real economies require external normalization, limiting decentralization and serverless performance, as well as an external incentive to cheat. • How does synthetic economy provide a real incentive to conform node behavior and avoid defection and interference?

15. The Subjective Incentive • The benefit sought by a user is some assurance of availability of the services when required. • Few users intend to make a profit from an investment in the system; and an opportunity for external profit should not be required. • Anticipation of fairness and availability given selfish incentives of others is sufficient incentive. • If one user anticipates that others will act selfishly to his detriment, and that acting selfishly himself will not lead to punishment, then likelihood of network instability increases.

16. The Economy • Micropayment technology. • Cryptographically secure value, does not mandate real-time verification. • Modifications from traditional schemes: • Currency has value which changes over time. • Currency automatically generated over time. • No extrinsic value. • Honesty assured by peer monitoring.

17. The Auction for Bandwidth • Each node broadcasts a “value function” fvn for information it desires, and a “cost” Cn for its involvement in communications benefiting others. • All fvn and Cn are propagated within relevance sphere. • Each node evaluates fvn based on its own available information, and broadcasts back to source node and relevance sphere a resolved value Vn. Since relevance sphere may differ for each node, boundary estimates may be used to represent network edge. • Each node within the relevance sphere performs a global minimization (VCG Auction) of Cn to produce a consistent set of non-interfering network routes with the maximum sum of all fvn.

18. The VCG Auction • Combinatorial optimization. Least cost combination selected. • Second price paid. • Decentralized control requires massive redundancy. • Full information requirement leads to substantial communications burden. • Well studied in traditional form. • True value bid is a dominant strategy.

19. Payment for Auction • Sink node transmits cryptographic micropayment in the amount of its fvn or a second price fvn-1. • Payment distributed to involved nodes according to VCG principles. Surplus between VCG payment and fvn is distributed to deferring bystander nodes in proportion to their fvn.

20. Modifications to VCG • Transmit value function instead of bid. • Multiple bidders and multiple sellers. • Surplus distributed to bystanders in proportion to bid. (Only bystanders impacted by network operation). • Interested bystander distribution prevents reciprocal transactions.

21. What do we gain? • Economic surplus of network is maximized globally. • Anticipated value function for each node maximized, leads to cooperation with network as a dominant strategy. • All nodes incentivized to cooperate and bid their true value. • Bystanders are incentivized to defer to involved nodes by economic compensation in accordance with their value for use of the network. • Communications are “priority” based, with temporal fairness. • In-network interference eliminated. • Coordination with respect to interfering externalities (deference, competition).

22. What does it cost? • Complex protocol. • Complex hardware. • High overhead. • Additional complexity for fault tolerance. • Simpler protocol with less overhead might be more optimal?

23. Other Characteristics • Emergency network commandeering is not supported in this scheme. (Use a cell phone?). • Cn does not discriminate between source and intermediary functions; node can charge for information value, but may forego opportunity for intermediary status as a result. Alternate auction could differentiate, but increased optimization complexity would result.

24. System Enhancements • High gain directional antennas, multiple apertures (spatial division multiplexing). • Out of band control channel (omnidirectional communications).

25. What happens if we compensate intermediate nodes using a fixed cost per hop? • Must still perform route discovery • Critical nodes will be congested • Optimal network topologies “overpriced” • Network will fragment and be used below capacity • High demand nodes will defect to gain larger payoff, if available

26. What happens if we charge a fixed cost per hop? • Emphasize short range communications and network fragmentation • Possibility of VCG distribution between intermediaries, otherwise, high valued intermediaries may defect • Network will fragment and be used below capacity • Low valued sinks may defect

27. Network Architecture Communication • During bidding process, each node communicates its location, itinerary, value function, cost function, local routing table contents. • Privacy issues remain; may require intentional data corruption—processing algorithms must then be fault tolerant. • Allows prediction of network and routes over time.

28. Conclusion • Game Theory provides a basis for competitive optimization. • Fairness and optimization lead to probability of acceptance. • Further work required for proof of extensions to existing paradigms. • Is this system intended for telematics also be usefully applied to other uses of band?