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Three-tier neural model for service provisioning over collaborative flying ad hoc networks

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Abstract

Collaboration among different ad hoc networks allows the formation of efficient guided networks. One of the such collaborative networks is formed between aerial ad hoc network and terrestrial ad hoc network. Simultaneous operation of both the networks can resolve complex missions collaboratively. Such cooperation can be achieved by deploying service models that allow efficient integration of distributed networks. The performance of service model can be enhanced by incorporating neural schema that provides a layered interface and cognitive transfers with higher accuracy. In this paper, a 3-tier neural model is proposed that allows the formation of guided ad hoc network. A layered network model is formulated that provides service-based integration of different network components required for the functioning of aerial guided ad hoc network along with provision for efficient service provisioning over flying ad hoc networks. The effectiveness and utility of the proposed model are demonstrated using simulations. Simulation study demonstrates that the proposed approach yields significant improvements in terms of service identification accuracy up to 13.6 %, fault identification up to 17.7 %, cognitive receival up to 23.56 %, fault tolerance up to 13.5 %, network errors reduction up to 34.11 %, and overheads up to 10 % compared to existing approaches.

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Acknowledgments

We are grateful to Editor-in-Chief and anonymous reviewers for their constructive comments and suggestions that helped in improving the quality of manuscript.

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Authors and Affiliations

  1. Research Lab, Computer Science and Engineering Department, Thapar University, Patiala, Punjab, India

    Vishal Sharma

  2. Computer Science and Engineering Department, Thapar University, Patiala, Punjab, India

    Rajesh Kumar

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  1. Vishal Sharma
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  2. Rajesh Kumar
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Correspondence to Vishal Sharma.

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Sharma, V., Kumar, R. Three-tier neural model for service provisioning over collaborative flying ad hoc networks. Neural Comput & Applic 29, 837–856 (2018). https://doi.org/10.1007/s00521-016-2584-1

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  • DOI: https://doi.org/10.1007/s00521-016-2584-1

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