A Genetic Algorithm Approach to Multi-Agent Itinerary Planning in Wireless Sensor Networks

被引：21

作者：

Cai, Wei ^{[1
]}

Chen, Min ^{[1
]}

Hara, Takahiro ^{[2
]}

Shu, Lei ^{[2
]}

Kwon, Taekyoung ^{[1
]}

机构：

[1] Seoul Natl Univ, Sch Comp Sci & Engn, Seoul, South Korea

[2] Osaka Univ, Dept Multimedia Engn, Osaka, Japan

来源：

MOBILE NETWORKS & APPLICATIONS | 2011年 / 16卷 / 06期

关键词：

mobile agent; wireless sensor networks; genetic algorithm; itinerary planning;

D O I：

10.1007/s11036-010-0269-z

中图分类号：

TP3 [计算技术、计算机技术];

学科分类号：

0812 ;

摘要：

It has been shown recently that using Mobile Agents (MAs) in wireless sensor networks (WSNs) can help to achieve the flexibility of over-the-air software deployment on demand. In MA-based WSNs, it is crucial to find out an optimal itinerary for an MA to perform data collection from multiple distributed sensors. However, using a single MA brings up the shortcomings such as large latency, inefficient route, and unbalanced resource (e.g. energy) consumption. Then a novel genetic algorithm based multi-agent itinerary planning (GA-MIP) scheme is proposed to address these drawbacks. The extensive simulation experiments show that GA-MIP performs better than the prior single agent algorithms in terms of the product of delay and energy consumption.

引用

页码：782 / 793

页数：12

共 16 条

[1]

[Anonymous], 2001, An Introduction to Genetic Algorithms. Complex Adaptive Systems

[2]

Beigl M, 2003, LECT NOTES COMPUT SC, V2864, P132

[3]

Chen M., 2007, EURASIP J APPL SIG P, P219

[4]

Chen M, 2006, J COMPUT, V1, P14

[5] Applications and design issues for mobile agents in wireless sensor networks [J].

Chen, Min ;

Gonzalez, Sergio ;

Leung, Victor C. M. .

IEEE WIRELESS COMMUNICATIONS, 2007, 14 (06) :20-26

[6]

CHENG L, 2009, P 7 IEEE IFIP INT C

[7]

Chenine Moustafa., 2009, 2009 International Conference on Electric Power and Energy Conversion Systems, (EPECS), P1, DOI DOI 10.1109/ICC.2009.5198997

[8]

De Jong K. A., 1992, Annals of Mathematics and Artificial Intelligence, V5, P1, DOI 10.1007/BF01530777

[9]

Petrás I, 2009, IEEE INT C EMERG

[10] Schema Theory for Genetic Programming with One-Point Crossover and Point Mutation [J].

Poli, Riccardo ;

Langdon, William B. .

EVOLUTIONARY COMPUTATION, 1998, 6 (03) :231-252

← 1 2 →