Store-Carry-Cooperative Forward Routing with Information Epidemics Control for Data Delivery in Opportunistic Networks
Data delivery in opportunistic networks requires robustness and resiliency due to the mobility and probabilistic propagation channels caused by fading. Besides the 100% data delivery, delivery with minimum delay, overhead, buffer consumption, and controlling unnecessary transmissions/replications ar...
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sg-ntu-dr.10356-868942020-03-07T13:57:30Z Store-Carry-Cooperative Forward Routing with Information Epidemics Control for Data Delivery in Opportunistic Networks Aung, Cherry Ye Ho, Ivan Wang-Hei Chong, Peter Han Joo School of Electrical and Electronic Engineering Cooperative Forwarding Opportunistic Networks Data delivery in opportunistic networks requires robustness and resiliency due to the mobility and probabilistic propagation channels caused by fading. Besides the 100% data delivery, delivery with minimum delay, overhead, buffer consumption, and controlling unnecessary transmissions/replications are equally important. In this paper, we propose a data delivery solution for opportunistic networks. The solution comprises two main algorithms: store-carry-cooperative forward routing and information epidemic control. In the data forwarding, nodes proactively monitor and exploit the direct/two-hop cooperative forwarding opportunities and adaptively switch between the cooperative forwarding and reactive store-carry-forward routing. An information epidemics control algorithm, which provides earlier control signal distribution time and faster recovery rate, is also proposed. The susceptible-infected-recovered model is used to study the effectiveness of the proposed mechanism. Extensive network performance evaluation is conducted under a wide range of scenarios, which include fading environments, obstacle-constrained environments, and mobile social network environments. We show that: 1) the information epidemics control mechanism provides higher vaccination rate and recovery rate; 2) proactive replication incurs a number of unnecessary transmissions; 3) monitoring the vicinity and exploiting the opportunity shorten the data delivery delay; and 4) with the integrated solution, a robust data delivery is achieved and a substantial amount of unnecessary transmissions are well deterred. Published version 2018-01-03T06:28:52Z 2019-12-06T16:31:07Z 2018-01-03T06:28:52Z 2019-12-06T16:31:07Z 2017 Journal Article Aung, C. Y., Ho, I. W.-H., & Chong, P. H. J. (2017). Store-Carry-Cooperative Forward Routing with Information Epidemics Control for Data Delivery in Opportunistic Networks. IEEE Access, 5, 6608-6625. Aung, C. Y., Ho, I. W.-H., & Chong, P. H. J. (2017). Store-Carry-Cooperative Forward Routing with Information Epidemics Control for Data Delivery in Opportunistic Networks. IEEE Access, 5, 6608-6625. https://hdl.handle.net/10356/86894 http://hdl.handle.net/10220/44248 10.1109/ACCESS.2017.2690341 en IEEE Access © 2017 IEEE. Translations and content mining are permitted for academic research only. Personal use is also permitted, but republication/redistribution requires IEEE permission. See http://www.ieee.org/publications_standards/publications/rights/index.html for more information. 18 p. application/pdf |
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Cooperative Forwarding Opportunistic Networks Aung, Cherry Ye Ho, Ivan Wang-Hei Chong, Peter Han Joo Store-Carry-Cooperative Forward Routing with Information Epidemics Control for Data Delivery in Opportunistic Networks |
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Data delivery in opportunistic networks requires robustness and resiliency due to the mobility and probabilistic propagation channels caused by fading. Besides the 100% data delivery, delivery with minimum delay, overhead, buffer consumption, and controlling unnecessary transmissions/replications are equally important. In this paper, we propose a data delivery solution for opportunistic networks. The solution comprises two main algorithms: store-carry-cooperative forward routing and information epidemic control. In the data forwarding, nodes proactively monitor and exploit the direct/two-hop cooperative forwarding opportunities and adaptively switch between the cooperative forwarding and reactive store-carry-forward routing. An information epidemics control algorithm, which provides earlier control signal distribution time and faster recovery rate, is also proposed. The susceptible-infected-recovered model is used to study the effectiveness of the proposed mechanism. Extensive network performance evaluation is conducted under a wide range of scenarios, which include fading environments, obstacle-constrained environments, and mobile social network environments. We show that: 1) the information epidemics control mechanism provides higher vaccination rate and recovery rate; 2) proactive replication incurs a number of unnecessary transmissions; 3) monitoring the vicinity and exploiting the opportunity shorten the data delivery delay; and 4) with the integrated solution, a robust data delivery is achieved and a substantial amount of unnecessary transmissions are well deterred. |
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School of Electrical and Electronic Engineering |
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School of Electrical and Electronic Engineering Aung, Cherry Ye Ho, Ivan Wang-Hei Chong, Peter Han Joo |
format |
Article |
author |
Aung, Cherry Ye Ho, Ivan Wang-Hei Chong, Peter Han Joo |
author_sort |
Aung, Cherry Ye |
title |
Store-Carry-Cooperative Forward Routing with Information Epidemics Control for Data Delivery in Opportunistic Networks |
title_short |
Store-Carry-Cooperative Forward Routing with Information Epidemics Control for Data Delivery in Opportunistic Networks |
title_full |
Store-Carry-Cooperative Forward Routing with Information Epidemics Control for Data Delivery in Opportunistic Networks |
title_fullStr |
Store-Carry-Cooperative Forward Routing with Information Epidemics Control for Data Delivery in Opportunistic Networks |
title_full_unstemmed |
Store-Carry-Cooperative Forward Routing with Information Epidemics Control for Data Delivery in Opportunistic Networks |
title_sort |
store-carry-cooperative forward routing with information epidemics control for data delivery in opportunistic networks |
publishDate |
2018 |
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https://hdl.handle.net/10356/86894 http://hdl.handle.net/10220/44248 |
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1681043182337392640 |