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Performance Evaluation Considering the Capture Effect in Ad hoc Networks on User Cooperative Mobility for QoS Improvement

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Published:05 January 2018Publication History

ABSTRACT

1To mitigate performance anomalies due to different transmission rates and to improve throughput performance in ad hoc networks, previous work has proposed a new method called user-cooperative mobility. This article also shows that the method achieves good improvement in ad hoc nodes, i.e., human users appropriately move. However, this method only employed a theoretical evaluation, which does not include detailed behaviors such as the capture effect or dynamic back-off time, which are considered to largely affect the performance in terms of throughput. Here, we employ an NS3 network simulator to clarify how the difference in throughput affects user mobility and throughput improvement in an ad hoc network. The result shows a huge difference in system throughput between theoretical estimations and simulations. This is caused by different transmitting opportunities due to the capture effect and the dynamic back-off time. In some cases, the system throughput will even drop when the throughput improvement ratio is under 1.0, being 0.64 when the throughput results from user moves are compared with those from no moves. We conclude that to improve the throughput as much as possible, a user should move based on the simulation results, which includes a capture effect and back-off time, instead of using only theoretical evaluation.

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  1. Performance Evaluation Considering the Capture Effect in Ad hoc Networks on User Cooperative Mobility for QoS Improvement

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          cover image ACM Other conferences
          IMCOM '18: Proceedings of the 12th International Conference on Ubiquitous Information Management and Communication
          January 2018
          628 pages
          ISBN:9781450363853
          DOI:10.1145/3164541

          Copyright © 2018 ACM

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          Publication History

          • Published: 5 January 2018

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          IMCOM '18 Paper Acceptance Rate100of255submissions,39%Overall Acceptance Rate213of621submissions,34%

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