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Mobile agent is a vehicle equipped with powerful transceiver and battery which finds the shortest path to gather data from the sensors and finally transports the data to the sink. The problem of minimizing the length of each data-gathering tour is mainly focused here. The mobile agent involves Bee Colony Optimization for travelling salesman problem. The Artificial Bee Colony algorithm (ABC) optimization is a population-based search algorithm which applies the concept of social interaction to problem solving. This algorithm is applied to the process of path planning problems for the mobile agents; it finds the shortest path for the mobile agents to collect the data from sensors as well as best in computation time. The effectiveness of the paths has been evaluated with the parameters such as tour length, agent travel time by Artificial Bee Colony Algorithm. This algorithm also prolong the lifetime of the sensors when compared to other existing approaches. Artificial Bee Colony algorithm has the advantages of strong robustness, fast convergence and high flexibility. This approach gives the best results for finding the shortest path in a shortest time.
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Mobile agent is a vehicle equipped with powerful transceiver and battery which finds the shortest path to gather data from the sensors and finally transports the data to the sink. The problem of minimizing the length of each data-gathering tour is mainly focused here. The mobile agent involves Bee Colony Optimization for travelling salesman problem. The Artificial Bee Colony algorithm (ABC) optimization is a population-based search algorithm which applies the concept of social interaction to problem solving. This algorithm is applied to the process of path planning problems for the mobile agents; it finds the shortest path for the mobile agents to collect the data from sensors as well as best in computation time. The effectiveness of the paths has been evaluated with the parameters such as tour length, agent travel time by Artificial Bee Colony Algorithm. This algorithm also prolong the lifetime of the sensors when compared to other existing approaches. Artificial Bee Colony algorithm has the advantages of strong robustness, fast convergence and high flexibility. This approach gives the best results for finding the shortest path in a shortest time.
Biografía del autor
Dr. S. Ramesh, Faculty in the Department of Computer Science and Engineering at Anna University Regional Office, Madurai. Received his Ph.D in Information and Communication Engineering by 2015 from Anna University, Chennai.His research interests include Wireless Networks, Network Security, and Optimization Techniques.
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Mobile Agent for Data Gathering in Wireless Sensor Networks
Verlag:
LAP LAMBERT Academic Publishing Sep 2015, 2015
ISBN 10: 3659786691
ISBN 13: 9783659786693
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Taschenbuch. Zustand: Neu. Neuware -Mobile agent is a vehicle equipped with powerful transceiver and battery which finds the shortest path to gather data from the sensors and finally transports the data to the sink. The problem of minimizing the length of each data-gathering tour is mainly focused here. The mobile agent involves Bee Colony Optimization for travelling salesman problem. The Artificial Bee Colony algorithm (ABC) optimization is a population-based search algorithm which applies the concept of social interaction to problem solving. This algorithm is applied to the process of path planning problems for the mobile agents; it finds the shortest path for the mobile agents to collect the data from sensors as well as best in computation time. The effectiveness of the paths has been evaluated with the parameters such as tour length, agent travel time by Artificial Bee Colony Algorithm. This algorithm also prolong the lifetime of the sensors when compared to other existing approaches. Artificial Bee Colony algorithm has the advantages of strong robustness, fast convergence and high flexibility. This approach gives the best results for finding the shortest path in a shortest time.Books on Demand GmbH, Überseering 33, 22297 Hamburg 68 pp. Englisch. Artikel-Nr. 9783659786693
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