|Table of Contents|

Study on Improved Hybrid Mobile Agent Routing in Wireless Sensor Networks(PDF)

《南京师大学报(自然科学版)》[ISSN:1001-4616/CN:32-1239/N]

Issue:
2012年04期
Page:
145-149
Research Field:
计算机科学
Publishing date:

Info

Title:
Study on Improved Hybrid Mobile Agent Routing in Wireless Sensor Networks
Author(s):
Zhang Lihong
School of Computer Engineering,Huaihai Institute of Technology,Lianyungang 222005,China
Keywords:
routing algorithmGAACAwireless sensor networkmobile agent
PACS:
TN929.5;TP212.9
DOI:
-
Abstract:
The mobile agent route is essentially a multi-constraint optimization problem. Genetic Algorithms has fast random global search ability,but the feedback information of the system does not use and has the problem of low efficiency to find exact solutions. So this paper proposes a genetic hybrid ant colony algorithm for WSN mobile agent route. Using the fast random global search capabilities of genetic algorithm to find better solutions, then the better solution replaced by the initial pheromone of the ant colony algorithm, finally using the advantages of convergence speed of ant colony algorithm to find the global optimal solution for mobile agent route. Simulation result shows that the algorithm can find optimal mobile agent route in a relatively short time, relative to other routing algorithms, reducing network latency and average energy consumption, improving the speed and efficiency of data transfer.

References:

[1] Tilak S,Abu Ghazaleh N B,Heinzelman W. A taxonomy of wireless micro sensor network models[J]. Mobile Computing and Communications Review, 2002,1 ( 2) : 1-8.
[2] 于飞,郭静,胡继珍. 一种无线传感器网络路由协议的研究与仿真[J]. 青岛科技大学学报: 自然科学版, 2011, 32( 1) : 95-99.
[3] 任丰原,黄海宁,林闯. 无线传感器网络[J]. 软件学报, 2011, 14( 7) : 1282-1291.
[4] 崔莉,鞠海玲,苗勇,等. 无线传感器网络研究进展[J]. 计算机研究与发展, 2009, 42( 1) : 163-174.
[5] Qi H, Iyengar S S,Chakrabarty K. Multi-resolution data integration using mobile agents in distributed sensor networks[J]. IEEE Trans on Systems,Man, and Cybernetics-Part C: Applications and Reviews, 2001, 31( 3) : 383-291.
[6] 郑巍,刘三阳,寇晓丽. 动态传感器网络移动代理路由算法[J]. 控制与决策, 2010, 25( 7) : 1035-1039.
[7] 胡建理,周斌,吴泉源,等. ICA: 一种基于混合智能算法的移动Agent 路由算法[J]. 小型微型计算机系统, 2010( 2) : 348-354.
[8] 徐云剑,彭沛夫,郭艾寅,等. 基于改进蚁群算法的WSN 移动代理路由算法研究[J]. 计算机工程与应用, 2009, 45( 4) : 126-130.
[9] 姚永杰,席庆彪,刘慧霞. 基于改进遗传蚁群算法的无人机航路规划[J]. 计算机仿真, 2011, 28( 6) : 44-48.
[10] 方旺盛,黎飞龙. WSN 中基于改进自适应遗传算法的移动代理路由算法[J]. 计算机与数字工程, 2010, 38( 12) : 4-7.
[11] Peotta L,Vandergheynst P. Matching pursuit with block incoherent dictionaries[J]. IEEE Trans on Signal Processing, 2007, 55 ( 9) : 4549-4557.
[12] Corlorni A,Dorigo M,Maniezzo V, et al. Ant system for job-shop scheduling[J]. Belgian J Opera Rees Statistic Compute Sci, 1994, 34( 1) : 34-53.

Memo

Memo:
-
Last Update: 2013-03-11