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标题：Scalable Routing Protocol for Cognitive Radio Sensor Networks using ACO
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作者：Amit N. Thakare ; Dr. L. G. Malik ; Achamma Thomas 等
期刊名称：International Journal of Innovative Research in Science, Engineering and Technology
印刷版ISSN：2347-6710
电子版ISSN：2319-8753
出版年度：2017
卷号：6
期号：12
页码：22793
DOI：10.15680/IJIRSET.2017.0612099
出版社：S&S Publications
摘要：Wireless sensor network (WSN) is an autonomous system of number of sensor nodes deployed in theregion and connected by the wireless links. The sensor nodes are battery powered node with some limited energy toutilize in network for various applications. The nodes are changing the position frequently and forward the packetsfrom source to the destination. The routing is the main issue in wireless sensor networks. Thus there is need ofdesigning the routing protocol for large scale WSN. The next generation of wireless sensor network is the improvementin the hybridization techniques. The MAC and network layer is to be improved for the next generation wirelesstechnology. The new idea behind the routing techniques is by sending the packets whenever the communicationrequired with available spectrum holes. The next generation WSN is the CRSN (Cognitive radio sensor network) withcognitive capabilities. It is a possibly new routing philosophy that provides a scalable solution to relatively largenetwork in CRSN. An inspired from swarm colony optimization as artificial intelligence techniques likely to be ACO(Ant colony optimization) method used to find the shortest route with reliable routing in CRSN. In this paper anattempt has been made to compare the performance of routing methods for CRSN using biologically inspired methods.As per finding the differences in the protocol provides better solution for routing techniques with high density network.The performance differentials are analysed using varying number of pause time. The simulation is carried out usingNS2 simulation tool. The results illustrate the importance of implementing the routing protocols in CRSN environmentfor large network.
关键词：Routing; Scalability; Ant Colony Optimization; CRSN; Performance Analysis.