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A resilient self-organizing offshore communication network for fishermen

Publication Type : Conference Paper

Thematic Areas : Wireless Network and Application

Publisher : ACM International Conference Proceeding Series, Association for Computing Machinery,

Source : ACM International Conference Proceeding Series, Association for Computing Machinery, Volume Part F125794 (2017)

Url : https://www.scopus.com/inward/record.uri?eid=2-s2.0-85014820549&doi=10.1145%2f3007748.3018283&partnerID=40&md5=d9e690ddb37a6a7c57b2b6b785e472dd

ISBN : 9781450348393

Campus : Amritapuri

School : School of Engineering

Center : Amrita Center for Wireless Networks and Applications (AmritaWNA)

Department : Electronics and Communication

Year : 2017

Abstract : Fishing is a major industry that provides the livelihood for millions of families worldwide. The fishing vessels are typically at sea for 5-7 days at a stretch completely cut off from the land. In a low-cost offshore communication system for fishermen currently being developed, a multilevel P2MP backhaul network connects clusters of boats at the fishing zones. Each cluster forms a wireless mesh network with multiple potential gateways to the backhaul network. This work proposes a resilient lightweight protocol for optimized dynamic provisioning of the backhaul network based on an adaptive, demand driven algorithm. A local controller, capable of running on any access router, selects the optimal subset of gateways so that the rest can be reconfigured as mobile base stations or switched to power saver mode. It assigns every boat in a cluster to the most appropriate gateway maximizing the utilization of gateways. A proof-of-concept implementation has been done with a hardware test bed and the results are very encouraging. © 2017 ACM.

Cite this Research Publication : H. S. Jennath, Nandesh Nair, Sethuraman Rao, Raj Dhanesh, Narayanan, S., and Krishnaswamy, D., “A resilient self-organizing offshore communication network for fishermen”, in ACM International Conference Proceeding Series, 2017, vol. Part F125794.

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