Wireless sensor network node optimal coverage based on improved genetic algorithm and binary ant colony algorithm

Considering the situation of some practical factors such as energy saving of the nodes and the high density of distributing nodes in wireless sensor networks, a wireless sensor network (WSN) node optimal coverage method based on improved genetic algorithm and binary ant colony algorithm is proposed...

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Vydáno v:EURASIP journal on wireless communications and networking Ročník 2016; číslo 1; s. 1 - 11
Hlavní autoři: Tian, Jingwen, Gao, Meijuan, Ge, Guangshuang
Médium: Journal Article
Jazyk:angličtina
Vydáno: Cham Springer International Publishing 14.04.2016
Springer Nature B.V
Témata:
Algorithms
Ant colony optimization
Communications Engineering
Computation
Engineering
Genetic algorithms
Information Systems Applications (incl.Internet)
Networks
Optimization
Remote sensors
Sensors
Signal,Image and Speech Processing
Wireless networks
Wireless sensor network
Node optimal coverage
Binary ant colony algorithm
Genetic algorithm
ISSN:1687-1499, 1687-1472, 1687-1499
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Shrnutí:Considering the situation of some practical factors such as energy saving of the nodes and the high density of distributing nodes in wireless sensor networks, a wireless sensor network (WSN) node optimal coverage method based on improved genetic algorithm and binary ant colony algorithm is proposed in this paper. The genetic algorithm and ant colony algorithm are improved and fused aiming at their disadvantages. The binary code expects a low intelligence of each ant, and each path corresponds to a comparatively small storage space, thus considerably improving the efficiency of computation. The optimal working node set is computed according to the max-coverage area of working sensor and the min-number of working sensor constraint conditions to optimize algorithm. The simulation results demonstrate that the proposed algorithm can converge at the optimal solution fast and satisfy the requirement of low node utilization rate and a high coverage rate, thus prolonging the network lifetime efficiently.
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ISSN:1687-1499
1687-1472
1687-1499
DOI:10.1186/s13638-016-0605-5