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A centrality-based history prediction routing protocol for opportunistic networks

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posted on 24.05.2021, 10:10 by Amarpreet Bamrah
Opportunistic networks are a subclass of delay tolerant networks based on a novel communication paradigm that aims at transmitting messages by exploiting direct contacts among nodes, without the need of a predefined infrastructure. Typical characteristics of OppNet include high mobility, short radio range, intermittent links, unstable topology, sparse connectivity, to name a few. As such, routing in such networks is a challenging task since it relies on node cooperation. This thesis focuses on using the concept of centrality to alleviate this task. Unlike other nodes in the network, central nodes are more likely to act as communication hubs to facilitate the message forwarding. In this thesis, a recently proposed History-Based Prediction Routing protocol is redesigned using this concept, yielding the so-called centrality-based HBPR protocol. The proposed CHBPR is evaluated by simulations using the ONE simulator, showing superior performance compared to HBPR without centrality and the Epidemic protocol with centrality.





Master of Science


Computer Science

Granting Institution

Ryerson University

LAC Thesis Type