DocumentCode :
3176180
Title :
Data Aggregation and Routing in Wireless Sensor Networks Using Improved Ant Colony Algorithm
Author :
Jinghua, Wang ; Huan, He ; Bo, Chen ; Yuanyuan, Chen ; Tingting, Guan
Author_Institution :
Dept. of Comput. Sci., Central China Normal Univ., Wuhan, China
Volume :
3
fYear :
2009
fDate :
25-27 Dec. 2009
Firstpage :
215
Lastpage :
218
Abstract :
A wireless sensor network consists of a large number of sensor nodes scattered in the region of the network which have limited energy and limited computational and sensing ability. Data aggregation is important in this kind of network which can make use of the energy of the sensor nodes efficiently, and reduce the traffic in network by utilizing the abilities of the nodes in local computation and storage. Ant colony algorithm is a paradigm for designing meta heuristic algorithm for combinatorial optimization problems. An improved ant colony algorithm is studied and applied it into data aggregation in wireless sensor network for a group of source nodes to send data to a single sink node. Moreover, Dijkstra algorithm is introduced in computing the hop counts for all the nodes to the sink node. Simulation has shown that the amounts of pheromone on the optimal path increase faster than others. At last, we can get the global optimal path.
Keywords :
combinatorial mathematics; optimisation; telecommunication computing; wireless sensor networks; Dijkstra algorithm; ant colony algorithm; combinatorial optimization; data aggregation; hop counts; metaheuristic algorithm; pheromone; routing; wireless sensor networks; Algorithm design and analysis; Ant colony optimization; Computer networks; Design optimization; Energy storage; Heuristic algorithms; Routing; Scattering; Telecommunication traffic; Wireless sensor networks; Wireless sensor network; ant colony algorithm; data aggregation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Science-Technology and Applications, 2009. IFCSTA '09. International Forum on
Conference_Location :
Chongqing
Print_ISBN :
978-0-7695-3930-0
Electronic_ISBN :
978-1-4244-5423-5
Type :
conf
DOI :
10.1109/IFCSTA.2009.292
Filename :
5384807
Link To Document :
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