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Switching cost minimization in the IEEE 802.16e mobile WiMAX sleep mode operation
Author(s) -
Wong Gary K. W.,
Zhang Qian,
Tsang Danny H. K.
Publication year - 2010
Publication title -
wireless communications and mobile computing
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.42
H-Index - 64
eISSN - 1530-8677
pISSN - 1530-8669
DOI - 10.1002/wcm.875
Subject(s) - computer science , wimax , sleep mode , heuristic , energy consumption , ieee 802 , energy (signal processing) , real time computing , sleep (system call) , battery (electricity) , mode (computer interface) , handover , computer network , telecommunications , wireless , quality of service , artificial intelligence , electrical engineering , power (physics) , physics , power consumption , quantum mechanics , operating system , statistics , mathematics , engineering
To prolong the battery lifetime, it is important to continue designing a better energy efficient mechanism for different mobile technologies. Most of the existing works on the IEEE 802.16e sleep mode operation focus on the decision making before a mobile station switching to sleep mode state. The correlation of the decision is mainly on when and how to sleep based on the traffic demands. After the mobile station is switched to sleep mode, the deactivation of it mainly depends on new incoming traffic regardless of the actual amount. Truly, frequent switching can increase the energy cost on the mobile station, which can significantly reduce the battery lifetime. To minimize the switching frequency, we propose a novel approach to resolve this issue by making a heuristic decision during the listening interval. With this aim, we propose a real‐time heuristic algorithm, WAKSLP_DECISION , to accommodate our target. Three main decision criteria are analyzed and designed, namely the probability of buffer overflow, expected delay violation, and battery lifetime expiry, to achieve our goal. We verify the energy consumption performance with simulation experiments to validate our proposed scheme. The result shows that our scheme performs 25–30% better compared with the original standard in terms of energy consumption. We believe this algorithm is practical and implementable without changing the original standard, which can contribute both in the research community and industrial development. Copyright © 2009 John Wiley & Sons, Ltd.

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