Time synchronization in ad hoc networks
MobiHoc '01 Proceedings of the 2nd ACM international symposium on Mobile ad hoc networking & computing
A taxonomy of wireless micro-sensor network models
ACM SIGMOBILE Mobile Computing and Communications Review
Computers and Intractability: A Guide to the Theory of NP-Completeness
Computers and Intractability: A Guide to the Theory of NP-Completeness
Topology control in wireless ad hoc and sensor networks
ACM Computing Surveys (CSUR)
Organizing a global coordinate system from local information on an ad hoc sensor network
IPSN'03 Proceedings of the 2nd international conference on Information processing in sensor networks
MAC protocols for wireless sensor networks: a survey
IEEE Communications Magazine
Distributed self-tuning of sensor networks
Wireless Networks
Engineering of Software-Intensive Systems: State of the Art and Research Challenges
Software-Intensive Systems and New Computing Paradigms
A fully distributed node allocation scheme for partition protection in MANET
WCNC'09 Proceedings of the 2009 IEEE conference on Wireless Communications & Networking Conference
A fully distributed node allocation scheme with partition protection for Mobile Ad Hoc Networks
Computer Communications
Self-organization in an agent network: A mechanism and a potential application
Decision Support Systems
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This work is motivated by the idea of using randomly deployed wireless networks of miniature smart sensors to serve as distributed instrumentation. In such applications, often the objective of the sensor network is to repeatedly compute and, if required, deliver to an observer some result based on the values measured at the sensors. We argue that in such applications it is important for the sensors to self-organize in a way that optimizes network throughput. We identify and discuss two main problems of optimal self-organization: 1) building an optimal topology, and 2) tuning network access parameters, such as the transmission attempt rate. We consider a simple random access model for sensor networks and formulate these problems as optimization problems. We then present centralized as well as distributed algorithms for solving them. Results show that the performance improvement is substantial and implementation of such optimal self-organization techniques may be worth the additional complexity.