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Hidden information and actions in multi-hop wireless ad hoc networks
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International Symposium on Mobile Ad Hoc Networking & Computing archive
Proceedings of the 9th ACM international symposium on Mobile ad hoc networking and computing table of contents
Hong Kong, Hong Kong, China
SESSION: Game-theoretical aspects table of contents
Pages 283-292  
Year of Publication: 2008
ISBN:978-1-60558-073-9
Authors
Xiang-Yang Li  NanJing University, NanJing, China
YanWei Wu  Illinois Institute of Technology, Chicago, IL, USA
Ping Xu  Illinois Institute of Technology, Chicago, IL, USA
GuiHai Chen  NanJing University, NanJing, China
Mo Li  Hong Kong University of Science and Technology, Hong Kong, China
Sponsors
SIGMOBILE: ACM Special Interest Group on Mobility of Systems, Users, Data and Computing
ACM: Association for Computing Machinery
Publisher
ACM  New York, NY, USA
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ABSTRACT

For multi-hop ad hoc networks formed by individually owned nodes, the endpoints can only observe whether or not the end-to-end transaction was successful or not, but not the individual actions of intermediate nodes. Consequently, in the absence of properly designed incentive schemes, rational (i.e., selfish) intermediate nodes may choose to forward data packets at a very low priority or simply drop the packets at all, and it could put the blame on the unreliable wireless channel. Using a principal-agent model, we propose several efficient methods that can eliminate the hidden actions under hidden information in multi-hop wireless networks with high probability. We design several algorithmic mechanisms for a number of routing scenarios such that each selfish agent will maximize its utility (i.e., profit) when it truthfully declares its type (i.e., cost and its actions) and it truthfully follows its declared actions. Our simulations show that the payment by our mechanisms is only slightly larger than the actual cost incurred by all intermediate nodes.


REFERENCES

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Collaborative Colleagues:
Xiang-Yang Li: colleagues
YanWei Wu: colleagues
Ping Xu: colleagues
GuiHai Chen: colleagues
Mo Li: colleagues