DocumentCode :
2208730
Title :
Automata based energy efficient spanning tree for data aggregation in Wireless Sensor Networks
Author :
Eskandari, Zahra ; Yaghmaee, Mohammad Hossien ; Mohajerzadeh, AmirHossien
Author_Institution :
Dept. of Comput. Eng., Ferdowsi Univ. of Mashhad, Mashhad, Iran
fYear :
2008
fDate :
19-21 Nov. 2008
Firstpage :
943
Lastpage :
947
Abstract :
Wireless sensor networks (WSNs) are networks that consist of low power nodes with limited processing ability. In some applications, these sensor nodes sense data from the environment periodically and transmit these data to sink node. In order to increase network¿s lifetime, number of transmitted data packet should be minimized. A solution which is suggested for decreasing transmitted data volume is aggregation. Aggregation algorithms should construct aggregation tree and transmit data to sink based on this tree. In this paper, we propose new learning automata based aggregation protocol which called automata energy efficient spanning tree, AEEspan. Simulation results show that the proposed algorithm has better performance in energy efficiency which leads to higher lifetime.
Keywords :
data communication; learning automata; protocols; telecommunication computing; trees (mathematics); wireless sensor networks; AEEspan; automata based energy efficient spanning tree; data aggregation; learning automata; low power nodes; protocol; sensor nodes sense data; sink node; wireless sensor networks; Computer networks; Data engineering; Electronic mail; Energy efficiency; Learning automata; Power engineering and energy; Power engineering computing; Protocols; Routing; Wireless sensor networks; Automata learning; Data Aggregation; Energy efficient; Spanning Tree; Wireless Sensor Networks;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Communication Systems, 2008. ICCS 2008. 11th IEEE Singapore International Conference on
Conference_Location :
Guangzhou
Print_ISBN :
978-1-4244-2423-8
Electronic_ISBN :
978-1-4244-2424-5
Type :
conf
DOI :
10.1109/ICCS.2008.4737323
Filename :
4737323
Link To Document :
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