Name
Abstract | ||
|---|---|---|
In this paper, we present a new general framework allowing sensor networks design using Random Markov Fields (MRF) theory. We explain how the principles underlying MRF theory naturally fit design requirements in sensor networks in particular the need to rely on decentralised and distributed methods to solve global optimisation problems. We illustrate the potential of this new general concept with the practical problems of power control and resource allocation. In addition, we present a new method to improve the convergence rate of the simulated annealing when the sensor network design problem is a constrained optimisation problem. |
Year | DOI | Venue |
|---|---|---|
2009 | 10.1109/SAHCN.2009.5168969 | SECON |
Keywords | Field | DocType |
sensor networks design,new general concept,fit design requirement,global optimisation problem,sensor networks protocol design,new general framework,mrf theory,sensor network design problem,optimisation problem,new method,sensor network,random markov field theory,resource allocation,optimization,convergence rate,topology,ad hoc networks,markov processes,mathematical model,image processing,power control,convergence,resource management,design optimization,network topology,simulated annealing,protocols,base stations,field theory | Convergence (routing),Simulated annealing,Mathematical optimization,Markov process,Computer science,Markov chain,Power control,Network topology,Resource allocation,Wireless sensor network,Distributed computing | Conference |
ISBN | Citations | PageRank |
978-1-4244-2908-0 | 7 | 0.63 |
References | Authors | |
6 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Sylvie Perreau | 1 | 373 | 30.75 |
| Marc Sigelle | 2 | 316 | 34.12 |
| Paolo Da Silva | 3 | 7 | 0.63 |
| Aruna Jayasuriya | 4 | 65 | 7.56 |