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EcoPlan: energy-efficient downlink and uplink data transmission in mobile cloud computing

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Abstract

Mobile cloud computing (MC2) is emerging as a new computing paradigm that seeks to augment resource-constrained mobile devices for executing computing- and/or data-intensive mobile applications. Nonetheless, the energy-poverty nature of mobile devices has become a stumbling block that greatly impedes the practical application of MC2. Fortunately, for delay-tolerant mobile applications, energy conservation is achievable via two means: (1) dynamic selection of energy-efficient links (e.g., WiFi interface); and (2) deferring data transmission in bad connectivity. In this paper, we study the problem of energy-efficient downlink and uplink data transmission between mobile devices and clouds. In the presence of unpredictable data arrival, network availability and link quality, our objective is to minimize the time average energy consumption of a mobile device while ensuring the stability of both device-end and cloud-end queues. To achieve this goal, we propose an online control framework named EcoPlan under which mobile users can make flexible link selection and data transmission scheduling decisions to achieve arbitrary energy-delay tradeoffs. Real-world trace-driven simulations demonstrate the effectiveness of EcoPlan, along with its superior energy-efficiency over alternative WiFi-prioritized, minimum-delay and SALSA schemes.

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Notes

  1. Noted that: (1) the data arrival information \({\varvec{A}}(t)\) is not required for decision-making at time point \(t\tau\); and (2) the uplink and downlink data transmission rates can be estimated using interface-dependent mechanisms (cf. Sect. 4.2).

  2. Choosing a small value of \(\tau\) would introduce large overheads due to bandwidth estimation at the beginning of each time slot \(t\). However, if \(\tau\) is chosen to be very large, using \({\varvec{B}}_l(t)\) to represent the link bandwidth spanning a time slot can be unpersuasive considering the drastic fluctuations of network condition. Hence, we use a moderate value of \(\tau =30\) s in the light of the statistics of our link trace [30].

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Acknowledgments

The authors gratefully acknowledge the editor and the anonymous referees for their constructive comments. The research was supported in part by a grant from the National Grand Fundamental Research 973 Program of China under grant No. 2010CB328105, by a grant from the National Natural Science Foundation of China (NSFC) under grant No. 61020106002; Xin Chen's work is supported by a grant from the NSFC under grant No. 61370065.

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Authors and Affiliations

  1. Department of Computer Science and Technology, University of Science and Technology Beijing, Haidian District, Beijing, China

    Xudong Xiang

  2. Department of Computer Science and Technology, Tsinghua University, Haidian District, Beijing, China

    Chuang Lin

  3. Computer School, Beijing Information Science and Technology University, Chaoyang District, Beijing, China

    Xin Chen

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  1. Xudong Xiang
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  2. Chuang Lin
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Correspondence to Xudong Xiang.

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Xiang, X., Lin, C. & Chen, X. EcoPlan: energy-efficient downlink and uplink data transmission in mobile cloud computing. Wireless Netw 21, 453–466 (2015). https://doi.org/10.1007/s11276-014-0795-x

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