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Title: Efficient Community-Based Data Distribution Over Multicast Trees
Authors: Souravlas, Stavros
Sifaleras, Angelo
Type: Article
Subjects: FRASCATI::Natural sciences::Computer and information sciences
FRASCATI::Engineering and technology::Electrical engineering, Electronic engineering, Information engineering
Keywords: Community detection
Multicast trees
Social intelligence
Social systems’ simulation
Issue Date: 2018
Publisher: IEEE
Source: IEEE Transactions on Computational Social Systems
Volume: 5
Issue: 1
First Page: 229
Last Page: 243
Abstract: Communities are important attributes of today's networking, since people who join networks tend to join communities. Thus, community detection is an important issue in designing algorithms for delay-tolerant networks (DTNs). Multicasting is an appropriate method to share information within a community or between communities, because it delivers messages from a source to a group of targets using limited resources. This paper addresses the problem of detecting communities in weighted networks with irregular topologies. Based on communities, we propose an efficient data distribution algorithm for DTNs. The distribution strategy is based on the construction of a number of multicast trees, where each tree can be used to select the best relay node for each target to improve multicast efficiency. The proposed strategy provides better delivery ratio compared with other strategies and it reduces latencies when multiple nodes from a community need to multicast to other community members.
ISSN: 2329-924X
Other Identifiers: 10.1109/TCSS.2017.2779578
Appears in Collections:Department of Applied Informatics

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