Distributed Problem Solving and the Boundaries of Self-Configuration in Multi-hop Wireless Networks

Authors:
B. Krishnamachari;R. Bejar;S. Wicker
Affiliations:
-;-;-
Venue:
HICSS '02 Proceedings of the 35th Annual Hawaii International Conference on System Sciences (HICSS'02)-Volume 9 - Volume 9
Year:
2002

Citing 0
Cited 10

Communication and Computation in Distributed CSP Algorithms

CP '02 Proceedings of the 8th International Conference on Principles and Practice of Constraint Programming
Distributed Bayesian Algorithms for Fault-Tolerant Event Region Detection in Wireless Sensor Networks

IEEE Transactions on Computers
Self-configuring localization systems: Design and Experimental Evaluation

ACM Transactions on Embedded Computing Systems (TECS)
Extremal Properties of Three-Dimensional Sensor Networks with Applications

IEEE Transactions on Mobile Computing
Sensor networks and distributed CSP: communication, computation and complexity

Artificial Intelligence - Special issue: Distributed constraint satisfaction
Asynchronous partial overlay: a new algorithm for solving distributed constraint satisfaction problems

Journal of Artificial Intelligence Research
Sensor networks and distributed CSP: communication, computation and complexity

Artificial Intelligence - Special issue: Distributed constraint satisfaction
Solving distributed asymmetric constraint satisfaction problems using an evolutionary society of hill-climbers

GECCO'03 Proceedings of the 2003 international conference on Genetic and evolutionary computation: PartI
Efficient and fault-tolerant feature extraction in wireless sensor networks

IPSN'03 Proceedings of the 2nd international conference on Information processing in sensor networks
Towards lightweight self-configuration in wireless sensor networks

Proceedings of the 2010 ACM Symposium on Applied Computing

Quantified Score

Hi-index	0.00

Visualization

Abstract

In this paper we consider three distributed decision making tasks that arise in the design and configuration of multi- hop wireless networks: medium access scheduling, Hamiltonian cycle formation, and the partitioning of network nodes into coordinating cliques. We first model these tasks as distributed constraint satisfaction problems (DCSPs). We first show that the communication complexity of DCSPs can be related to the computational complexity of centralized constraint satisfaction problems. We then use centralized algorithms to obtain experimental results on the solvability and complexity of the three DCSPs. We show that these problems exhibit ixphase transitionsll in solvability and complexity as the transmission power of the wireless nodes is varied. Based on these results, we argue that phase transition analysis provides a mechanism for quantifying the critical range of network resources needed for scalable, self-configuring multi-hop wireless networks.