Abstract
The opportunistic network is a type of ad hoc network that relies on the chance encounters between nodes to transmit messages. It also uses store-and-carry-forward techniques for data transfer between nodes. Developing effective message forwarding strategies based on opportunistic network characteristics and node behavior poses a significant challenge . In this paper, we delve into the mobility and social characteristics of nodes using historical encounter information. Furthermore, we calculate the migration degree and community relations to build the Meta Meeting Mountain, which representing node encounter characteristics. Moreover, we introduce the concept of Forwarding Degree to measure the nodes’ ability to deliver messages, enhancing the predictability of message delivery. Furthermore, a new forwarding strategy is proposed, which is equipped with Meta Meeting Mountain and Forwarding degree to improve the delivery rate. Our experimental scenarios include Infocom06, Rome taxi, and Helsinki. Therefore, the impact of buffer size and TTL is discussed in detail regarding the different opportunistic routing algorithms. Finally, extensive experimental results show that the proposed algorithm outperforms UBPR, MaxProp, PRoPHET, Spray And Wait and RAPAR in terms of delivery rate in the above scenarios by 127.905%, 93.7525%, 138.6888%, 175.3663%, and 281.4625%, respectively, while keeping the hopcount value less than 5.
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