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Energy-Optimal Mobile Cloud Computing under Stochastic Wireless Channel

Weiwen Zhang ; Yonggang Wen ; Guan, Kyle ; Kilper, Dan ; Haiyun Luo ; Wu, Dapeng Oliver

IEEE transactions on wireless communications, 2013-09, Vol.12 (9), p.4569-4581 [Periódico revisado por pares]

New York, NY: IEEE

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Título:
Energy-Optimal Mobile Cloud Computing under Stochastic Wireless Channel
Autor: Weiwen Zhang ; Yonggang Wen ; Guan, Kyle ; Kilper, Dan ; Haiyun Luo ; Wu, Dapeng Oliver
Assuntos: Applied sciences ; Channels ; Clocks ; Cloning ; Cloud computing ; Detection, estimation, filtering, equalization, prediction ; Energy consumption ; Energy-optimal execution ; Exact sciences and technology ; Information, signal and communications theory ; lagrangian multiplier method ; Mathematical models ; Miscellaneous ; mobile application ; Mobile communication ; Mobile communication systems ; Mobile handsets ; Operations research ; Optimal scheduling ; Optimization ; Policies ; Signal and communications theory ; Signal, noise ; stochastic wireless channel ; Stochasticity ; Studies ; Systems, networks and services of telecommunications ; Telecommunications ; Telecommunications and information theory ; Teleprocessing networks. Isdn ; Thresholds ; Transmission and modulation (techniques and equipments) ; Wireless communication
É parte de: IEEE transactions on wireless communications, 2013-09, Vol.12 (9), p.4569-4581
Notas: ObjectType-Article-2
SourceType-Scholarly Journals-1
ObjectType-Feature-1
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Descrição: This paper provides a theoretical framework of energy-optimal mobile cloud computing under stochastic wireless channel. Our objective is to conserve energy for the mobile device, by optimally executing mobile applications in the mobile device (i.e., mobile execution) or offloading to the cloud (i.e., cloud execution). One can, in the former case sequentially reconfigure the CPU frequency; or in the latter case dynamically vary the data transmission rate to the cloud, in response to the stochastic channel condition. We formulate both scheduling problems as constrained optimization problems, and obtain closed-form solutions for optimal scheduling policies. Furthermore, for the energy-optimal execution strategy of applications with small output data (e.g., CloudAV), we derive a threshold policy, which states that the data consumption rate, defined as the ratio between the data size (L) and the delay constraint (T), is compared to a threshold which depends on both the energy consumption model and the wireless channel model. Finally, numerical results suggest that a significant amount of energy can be saved for the mobile device by optimally offloading mobile applications to the cloud in some cases. Our theoretical framework and numerical investigations will shed lights on system implementation of mobile cloud computing under stochastic wireless channel.
Editor: New York, NY: IEEE
Idioma: Inglês

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Energy-Optimal Mobile Cloud Computing under Stochastic Wireless Channel

Weiwen Zhang ; Yonggang Wen ; Guan, Kyle ; Kilper, Dan ; Haiyun Luo ; Wu, Dapeng Oliver

New York, NY: IEEE

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