Paper Info
Title
Routing path generation for reliable transmission in sensor networks using GA with fuzzy logic based fitness function
Abstract
There has been a growing interest in the applications of sensor networks, such as combat field surveillance, terrorist tracking and highway traffic monitoring. These applications gather sensed data from sensor nodes to monitor events in the territory of interest. One of the important issues in these applications is the existence of the radio-jamming zone between source nodes and the base station. Depending on the routing protocol the transmission of the sensed data may not be delivered to the base station. To solve this problem we propose a routing path generation method that is based on genetic algorithms for reliable transmission by considering the balanced energy depletion of the sensor nodes. The genetic algorithm finds an efficient routing path by considering the radio-jamming zone, energy consumption needed for data transmission and average remaining energy. The fitness function employed in the genetic algorithm is implemented by applying the fuzzy logic. In simulation, our proposed method is compared with LEACH and Hierarchical PEGASIS. The simulation results show that the proposed method is efficient in both the energy consumption and success ratio of the delivery.
Year
DOI
Venue
2007
10.1007/978-3-540-74484-9_55
ICCSA (3)
Keywords
Field
DocType
energy consumption,genetic algorithm,sensor node,fitness function,sensor network,data transmission,reliable transmission,fuzzy logic,balanced energy depletion,base station,average remaining energy,radio-jamming zone,efficient routing path,routing path generation,routing protocol,shortest path
Link-state routing protocol,Computer science,Path vector protocol,Destination-Sequenced Distance Vector routing,Computer network,Fitness function,Energy consumption,Wireless sensor network,Routing protocol,Zone Routing Protocol
Conference
Volume
ISSN
ISBN
4707
0302-9743
3-540-74482-5
Citations 
PageRank 
References 
2
0.40
13
Authors
2
Name
Order
Citations
PageRank
Jin Myoung Kim1234.85
Tae Ho Cho215926.82