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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Wongsathan, R. Seedadan, I. Pattarangoon, S. |
| Copyright Year | 2010 |
| Description | Author affiliation: Department of Electrical Engineering, Faculty of Engineering, North-Chiang Mai University, 169 Hang Dong, Thailand 50230 (Wongsathan, R.; Seedadan, I.; Pattarangoon, S.) |
| Abstract | There are many routing protocols and algorithms developed for data transmission in Wireless Sensor Network (WSN). The main objective of this paper is an increasing of performance and reduction of energy dissipation in WSN. In this paper, the Bacterial Evolutionary Algorithm (BEA) or Bacteriologic Algorithm (BA) is selected to compare performance with Genetic Algorithm (GA) and Low Energy Adaptive Clustering Hierarchy (LEACH). The fastest computation for the near optimal solution is obtained by using BA which causes less energy dissipation. The computer simulation showed that GA can decrease the distance of data transmission lower than BA and LEACH about 4% and 30% respectively. However, Ga's disadvantage comes from slower speed with a high number of computed generation for data transmission in a WSN so the near optimal solution with faster computation can be obtained by using BA. According to the test, BA gives a lower energy dissipation of about 50% less than GA. |
| File Size | 244495 |
| File Format | |
| ISBN | 9781424463473 |
| e-ISBN | 9781424463497 |
| DOI | 10.1109/ICCET.2010.5486342 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2010-04-16 |
| Publisher Place | China |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | LEACH Computer simulation Evolutionary computation wireless sensor network Genetic algorithms genetic algorithm Wireless sensor networks Microorganisms bacteriologic algorithm Energy dissipation Clustering algorithms Routing protocols Data communication Testing |
| Content Type | Text |
| Resource Type | Article |
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