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Trust based Intelligent Routing Algorithm for Delay Tolerant Network using Artificial Neural Network

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Abstract

In today’s world, when every mobile device corresponds with human behavioral patterns. People often come across with various communities having patterns such as mobility, communication and groups. Trust is an intrinsic factor, which plays important role in formation of such communities. It is important to see the inherent risk involved in such socially active communities. Such factors motivate the use of trust as a routing factor in Delay Tolerant Networks (DTNs). This paper proposes a Trust based Intelligent Routing Algorithm, which exploits the Call Data Record from Call Detail Record. The function of Artificial Neural Network is to calculate and learn, trust value that can be shared among network devices. Our algorithm lowers the need of nodes resources like energy consumption, computation time and space overheads. The proposed algorithm enhances the routing performance in DTN. The earlier work claiming better efficiency generally ends up consuming network’s resources. On the contrary our proposed algorithm provides in-built security, without any additional overhead. To the best of our knowledge the proposed work is the first of its kind, providing ingrained security feature to the DTN. This work gives vantage point to the researchers in the field over other schemes proposed in the past.

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Acknowledgments

Researchers wishes to express sincere gratitude to the administration of M.C.A Department of Banarsidas Chandiwala Institute of Information Technology (BCIIT), affiliated to G.G.S.I.P. University, Delhi, India and Amity Institute of Information Technology (AIIT), Amity University Uttar Pradesh (AUUP), India, for providing the academic environment to pursue research activities.

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Correspondence to Vandana Juyal.

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Singh, A.V., Juyal, V. & Saggar, R. Trust based Intelligent Routing Algorithm for Delay Tolerant Network using Artificial Neural Network. Wireless Netw 23, 693–702 (2017). https://doi.org/10.1007/s11276-015-1166-y

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  • DOI: https://doi.org/10.1007/s11276-015-1166-y

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