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OlaRout: Optimal dropbox deployment based cluster routing for post disaster information exchange in a smart city

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Abstract

With the recent endeavour of smart city mission, it is being planned to install sophisticated infrastructure for providing various smart services. But the planning to handle unwanted events like disaster has not received much attention as part of this endeavour. In a post-disaster scenario, one of the most important services is to disseminate crucial situational information among different stakeholders when the traditional communication infrastructure becomes non-functional. The smart phone based delay tolerant network (DTN) shows its useful applicability in such a scenario. Further, it is well established that due to the movement pattern of the stakeholders with handheld device, it typically forms clusters based on their work areas. However, the existing DTN routing protocols are not designed for cluster architecture. This motivates us to propose a cluster routing considering a utility based optimal dropbox (DB) deployment that assists in providing improved network performance. In this paper, we primarily consider that DBs are deployed at strategic locations of the disaster affected area using an existing utility based dropbox deployment. Then we propose a mixed integer linear programming based optimization model, to enumerate the optimal number of dropboxes to be deployed at high utility locations. We finally propose a cluster based routing with a target to improve network performance. We evaluate the comparative performance of our proposed optimal DB deployment based cluster routing through both theoretical analysis and simulation. Exhaustive simulation is carried out in ONE simulator using real disaster data. Results show our scheme’s dominance over the competing schemes.

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Correspondence to Nabanita Das.

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Das, N., Basu, S. & Das Bit, S. OlaRout: Optimal dropbox deployment based cluster routing for post disaster information exchange in a smart city. Peer-to-Peer Netw. Appl. 16, 876–899 (2023). https://doi.org/10.1007/s12083-022-01433-1

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