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Mobility prediction in mobile ad hoc networks using a lightweight genetic algorithm

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Abstract

A mobile ad hoc network is a collection of wireless mobile nodes creating a network without using any existing infrastructure. Much research has been carried out to find out an optimal routing protocol for the successful transmission of data in this network. The main hindrance is the mobility of the network. If the mobility pattern of the network can be predicted, it will help in improving the QoS of the network. This paper discusses a novel approach to mobility prediction using movement history and existing concepts of genetic algorithms, to improve the MANET routing algorithms. The proposed lightweight genetic algorithm performs outlier removal on the basis of heuristics and parent selection using the weighted roulette wheel algorithm. After performing the genetic operations a node to node adjacency matrix is obtained from which the predicted direction of each node is calculated using force directed graphs and vector calculations. The technique proposes a new approach to mobility prediction which does not depend on probabilistic methods and which is completely based on genetic algorithms.

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Acknowledgments

This paper describes work in part undertaken in the context of the UKIERI project UGC2013-14/037 on Interfacing Ad hoc Mobile Networks with IP Mobile Systems. The project is a collaborative work supported under UKIERI programme between ABV-Indian Institute of Information Technology and Management, Gwalior, INDIA and Anglia Ruskin University, UK. The authors would like to thank ABV-Indian Institute of Information Technology and Management, Gwalior, India and Anglia Ruskin University, UK for providing the infrastructure and academic support.

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Correspondence to S. Tapaswi.

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Suraj, R., Tapaswi, S., Yousef, S. et al. Mobility prediction in mobile ad hoc networks using a lightweight genetic algorithm. Wireless Netw 22, 1797–1806 (2016). https://doi.org/10.1007/s11276-015-1059-0

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  • DOI: https://doi.org/10.1007/s11276-015-1059-0

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