Abstract
In recent years, mobile cloud computing (MCC) is utilized to process multimedia workflows due to the limitation of battery capacity of mobile devices, which influences the experience of multimedia applications on the mobile devices. Computation offloading based on cloudlet is introduced as a novel paradigm to relieve the high latency which offloading computation to remote cloud causes. However, it is still a challenge for mobile devices to offload computation of multimedia workflows in cloudlet-based cloud computation environment to reduce energy consumption, which meets time constraints at the same time. In view of the challenge, an energy-efficient computation offloading method of multimedia workflow with multi-objective optimization is proposed in this paper. Technically, an offloading method based on cloudlet using Differential Evolution (DE) algorithm is proposed to optimize the energy consumption of the mobile devices with time constraints. Finally, massive experimental evaluations and comparison analysis validate the efficiency of our proposed method.
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Acknowledgement
This research is supported by the Research Project of Shanghai Meteorological Bureau Scientific under Grant No. TD201807 and the National Science Foundation of China under grant no. 61702277, no. 61672276, no. 61772283, no. 61402167 and no. 61672290, the Key Research and Development Project of Jiangsu Province under Grant No. BE2015154 and BE2016120, and Natural Science Foundation of Jiangsu Province (Grant No. BK20171458). Besides, this work is also supported by The Startup Foundation for Introducing Talent of NUIST, the open project from State Key Laboratory for Novel Software Technology.
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© 2019 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
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Huang, T. et al. (2019). Energy-Efficient Computation Offloading for Multimedia Workflows in Mobile Cloud Computing. In: Gao, H., Yin, Y., Yang, X., Miao, H. (eds) Testbeds and Research Infrastructures for the Development of Networks and Communities. TridentCom 2018. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 270. Springer, Cham. https://doi.org/10.1007/978-3-030-12971-2_7
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DOI: https://doi.org/10.1007/978-3-030-12971-2_7
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