In opportunistic networks, data are often delivered by dissemination-based routing approaches using the store-carry-and-forward concept. However, the heavy overheads incurred by these approaches lead to inefficient data delivery. Generally, users in an area usually demand similar data, called "locality of demand", and this area is referred to as a community. Based on such property, this paper presents a community-based data dissemination (ComD) scheme to improve the data delivery efficiency in the opportunistic network. By delivering data to appropriate communities, users can obtain what they are actually interested in. Moreover, the ComD also uses the cooperative caching technique to reduce transmission redundancy. To optimize system utility, the proposed delivery model is formulated as a multiple knapsack problem to determine which data should be carried, and a greedy-based method is adopted to reduce the computational complexity. Simulation results show ComD can significantly improves the system utility and delivery rate under various situations. Index Terms-Opportunistic networks, community-based data dissemination, cooperative cache. I. INTRODUCTION Opportunistic networks are emerging network models evolved from Mobile Ad-Hoc Network (MANET). The communication in this type of network is intermittent and complete routes between sources and destinations rarely exist. The communication in this network is highly affected by human mobility [1], the link performance depends extensively on the characteristic of the mobility present in the network. Therefore, designing an efficient dissemination method is considered as one of the most compelling challenges in this type of network. Several existing forwarding strategies [1] exploit human mobility and opportunistic contacts to deliver data via store-carry-and-forward principle. In the dissemination-based strategies, such as epidemic routing protocol [2] and Spray and Wait [3] scheme, data copies are diffused all over the network. As the data copies increases in the network, the
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.