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Wireless Communications and Mobile Computing
Volume 2017, Article ID 3410350, 12 pages
https://doi.org/10.1155/2017/3410350
Research Article

Exploiting Delay-Aware Load Balance for Scalable 802.11 PSM in Crowd Event Environments

1School of Computer Science, Northwestern Polytechnical University, Xi’an, China
2School of Computer Science and IT, RMIT University, Melbourne, VIC, Australia

Correspondence should be addressed to Yu Zhang; nc.ude.upwn@uygnahz and Zhigang Li; nc.ude.upwn@gnagihzil

Received 19 March 2017; Accepted 1 June 2017; Published 12 July 2017

Academic Editor: Xiaoqiang Ma

Copyright © 2017 Yu Zhang et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

This paper presents ScaPSM (i.e., Scalable Power-Saving Mode Scheduler), a design that enables scalable competing background traffic scheduling in crowd event 802.11 deployments with Power-Saving Mode (PSM) radio operation. ScaPSM prevents the packet delay proliferation of previous study, if applied in the crowd events scenario, by introducing a new strategy of adequate competition among multiple PSM clients to optimize overall energy saving without degrading packet delay performance. The key novelty behind ScaPSM is that it exploits delay-aware load balance to control judiciously the qualification and the number of competing PSM clients before every beacon frame’s transmission, which helps to mitigate congestion at the peak period with increasing the number of PSM clients. With ScaPSM, the average packet delay is bounded and fairness among PSM clients is simultaneously achieved. ScaPSM is incrementally deployable due to only AP-side changes and does not require any modification to the 802.11 protocol or the clients. We theoretically analyze the performance of ScaPSM. Our experimental results show that the proposed design is practical, effective, and featuring with significantly improved scalability for crowd events.