TY - GEN
T1 - Evolutionary and noise-aware data gathering for wireless sensor networks
AU - Zhu, Bingchun
AU - Suzuki, Junichi
AU - Boonma, Pruet
PY - 2012
Y1 - 2012
N2 - This paper formulates a prioritized data gathering problem in noisy wireless sensor networks (WSNs) and solves the problem with a noise-aware evolutionary multiobjective optimization algorithm (EMOA). Unlike existing local search heuristics, the proposed algorithm can seek the Pareto-optimal routing structures with respect to conflicting optimization objectives. Simulation results demonstrate that the proposed algorithm outperforms a traditional EMOA in a noisy WSN.
AB - This paper formulates a prioritized data gathering problem in noisy wireless sensor networks (WSNs) and solves the problem with a noise-aware evolutionary multiobjective optimization algorithm (EMOA). Unlike existing local search heuristics, the proposed algorithm can seek the Pareto-optimal routing structures with respect to conflicting optimization objectives. Simulation results demonstrate that the proposed algorithm outperforms a traditional EMOA in a noisy WSN.
KW - Data gathering protocol
KW - Genetic algorithm
KW - Noisy multiobjective optimization problem
KW - Wireless sensor networks
UR - https://www.scopus.com/pages/publications/84869596835
UR - https://www.scopus.com/pages/publications/84869596835#tab=citedBy
U2 - 10.1007/978-3-642-32615-8_5
DO - 10.1007/978-3-642-32615-8_5
M3 - Conference contribution
AN - SCOPUS:84869596835
SN - 9783642326141
T3 - Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering
SP - 32
EP - 39
BT - Bio-Inspired Models of Network, Information, and Computing Systems - 5th International ICST Conference, BIONETICS 2010, Revised Selected Papers
T2 - 5th International ICST Conference on Bio-Inspired Models of Network, Information, and Computing Systems, BIONETICS 2010
Y2 - 1 December 2010 through 3 December 2010
ER -