A Data Transmission Scheme Based on Time-Evolving Meeting Probability for Opportunistic Social Network

With its widespread application prospects, opportunistic social network attracts more and more attention. Efficient data transmission strategy is one of the most important issues to ensure its applications. As is well known, most of nodes in opportunistic social network are human-carried devices, so...

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Main Authors: Fu Xiao, Guoxia Sun, Jia Xu, Lingyun Jiang, Ruchuan Wang
Format: Article
Language:English
Published: Wiley 2013-07-01
Series:International Journal of Distributed Sensor Networks
Online Access:https://doi.org/10.1155/2013/123428
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author Fu Xiao
Guoxia Sun
Jia Xu
Lingyun Jiang
Ruchuan Wang
author_facet Fu Xiao
Guoxia Sun
Jia Xu
Lingyun Jiang
Ruchuan Wang
author_sort Fu Xiao
collection DOAJ
description With its widespread application prospects, opportunistic social network attracts more and more attention. Efficient data transmission strategy is one of the most important issues to ensure its applications. As is well known, most of nodes in opportunistic social network are human-carried devices, so encounters between nodes are predictable when considering the law of human activities. To the best of our knowledge, existing data transmission solutions are less accurate in the prediction of node encounters due to their lack of consideration of the dynamism of users' behavior. To address this problem, a novel data transmission solution, based on time-evolving meeting probability for opportunistic social network, called TEMP is introduced, and corresponding copy management strategy is given to reduce the message redundancy. Simulation results based on real human traces show that TEMP achieves a good compromise in terms of delivery probability and overhead ratio.
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institution Kabale University
issn 1550-1477
language English
publishDate 2013-07-01
publisher Wiley
record_format Article
series International Journal of Distributed Sensor Networks
spelling doaj-art-9f20976f893e414eba1f3dba2f19c5cb2025-08-20T03:38:30ZengWileyInternational Journal of Distributed Sensor Networks1550-14772013-07-01910.1155/2013/123428A Data Transmission Scheme Based on Time-Evolving Meeting Probability for Opportunistic Social NetworkFu Xiao0Guoxia Sun1Jia Xu2Lingyun Jiang3Ruchuan Wang4 Key Lab of Broadband Wireless Communication and Sensor Network Technology (Nanjing University of Posts and Telecommunications), Ministry of Education Jiangsu Province, Nanjing, Jiangsu 210003, China College of Computer, Nanjing University of Posts and Telecommunications, Nanjing, Jiangsu 210003, China Key Lab of Broadband Wireless Communication and Sensor Network Technology (Nanjing University of Posts and Telecommunications), Ministry of Education Jiangsu Province, Nanjing, Jiangsu 210003, China Key Lab of Broadband Wireless Communication and Sensor Network Technology (Nanjing University of Posts and Telecommunications), Ministry of Education Jiangsu Province, Nanjing, Jiangsu 210003, China Key Lab of Broadband Wireless Communication and Sensor Network Technology (Nanjing University of Posts and Telecommunications), Ministry of Education Jiangsu Province, Nanjing, Jiangsu 210003, ChinaWith its widespread application prospects, opportunistic social network attracts more and more attention. Efficient data transmission strategy is one of the most important issues to ensure its applications. As is well known, most of nodes in opportunistic social network are human-carried devices, so encounters between nodes are predictable when considering the law of human activities. To the best of our knowledge, existing data transmission solutions are less accurate in the prediction of node encounters due to their lack of consideration of the dynamism of users' behavior. To address this problem, a novel data transmission solution, based on time-evolving meeting probability for opportunistic social network, called TEMP is introduced, and corresponding copy management strategy is given to reduce the message redundancy. Simulation results based on real human traces show that TEMP achieves a good compromise in terms of delivery probability and overhead ratio.https://doi.org/10.1155/2013/123428
spellingShingle Fu Xiao
Guoxia Sun
Jia Xu
Lingyun Jiang
Ruchuan Wang
A Data Transmission Scheme Based on Time-Evolving Meeting Probability for Opportunistic Social Network
International Journal of Distributed Sensor Networks
title A Data Transmission Scheme Based on Time-Evolving Meeting Probability for Opportunistic Social Network
title_full A Data Transmission Scheme Based on Time-Evolving Meeting Probability for Opportunistic Social Network
title_fullStr A Data Transmission Scheme Based on Time-Evolving Meeting Probability for Opportunistic Social Network
title_full_unstemmed A Data Transmission Scheme Based on Time-Evolving Meeting Probability for Opportunistic Social Network
title_short A Data Transmission Scheme Based on Time-Evolving Meeting Probability for Opportunistic Social Network
title_sort data transmission scheme based on time evolving meeting probability for opportunistic social network
url https://doi.org/10.1155/2013/123428
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