All-to-All Data Exchange Method for MANET in Congestion Environment

Jumpei Tokunaga () and Hiroyuki Ebara ()
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Jumpei Tokunaga: Kansai University
Hiroyuki Ebara: Kansai University

The Review of Socionetwork Strategies, 2024, vol. 18, issue 2, 185-210

Abstract: Abstract Mobile Ad-hoc Network (MANET) are expected to be a means of communication for disaster victim support systems and information distribution systems at event sites where it is challenging to use existing infrastructure owing to their feature of being able to build a network immediately among nodes that are present on the spot. An operating scenario of such a post-disaster application requires an all-to-all exchange of information that quickly and reliably exchanges a lot of information among a large number of nodes present at the scene to collect more decision-making materials. All-to-all communication places a lot of load on all nodes in the network as they exchange information about all nodes with each other. The MANET routing protocol is also heavily loaded due to route discovery by flooding, which, together with the all-to-all information exchange, is a double challenge to MANET. In this article, we propose an information exchange method that is robust to high-density nodes and high-traffic environments, assuming a situation where communication becomes difficult as a result of requests to send and receive large amounts of information between overcrowded nodes in crowded environments, such as evacuation centers, during a disaster and event sites. The proposed method overcomes the problems of conventional methods and achieves smooth information exchange by applying a delay tolerant network(DTN), a clustering method, and a gossip protocol method. Simulation experiments have shown that the proposed method is highly tolerant of network congestion and increase in the number of nodes due to all-to-all information exchange.

Keywords: Mobile Ad-hoc network; MANET; All-to-all data exchange; Delay tolerant network; DTN; Clustering; Gossip algorithm (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1007/s12626-024-00161-7

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