Publication Type : Journal Article
Publisher : Elsevier
Source : Computers & Electrical Engineering, 87, 106781. (2020) DOI: https://doi.org/10.1016/j.compeleceng.2020.106781
Url : https://www.sciencedirect.com/science/article/abs/pii/S0045790620306364
Campus : Amritapuri
School : School of Computing
Center : AI (Artificial Intelligence) and Distributed Systems
Year : 2020
Abstract : Lack of reliable and affordable mechanisms to communicate with the shore is one of the critical problems faced by fishermen engaged in deep-sea fishing. Offshore Communication Network (OCN) is an attempt to solve this issue by providing wireless internet over the ocean among a network of fishing vessels. A key challenge in OCN is the effective connectivity maintenance and restoration among nodes, due to the unpredictable characteristics of the ocean environment, the mobility, and density variations in the distribution of the fishing vessels. This paper proposes a metric, dynamic connectivity index (DCI), to quantify the communication capability of nodes, and to facilitate reorientation of node positions, for maintaining connectivity. The proposed position reorientation algorithm (PRA) is designed by considering the communication requirements and mobility pattern of fishing vessels. This paper details the results of simulation studies used for evaluating the effectiveness of the DCI and PRA over different OCN scenarios.
Cite this Research Publication : Simi, S., Maneesha Vinodini, R., Montag, M. J., & Montresor, A. (2020), "Modelling communication capability and node reorientation in offshore communication network," Computers & Electrical Engineering, 87, 106781. (2020) DOI: https://doi.org/10.1016/j.compeleceng.2020.106781