Abstract
The recent advancement in wireless communication has motivated increasing number of mobile applications, including computing-intensive tasks. However, it takes resource-limited mobile devices a lot of energy to execute these tasks. Computing offloading is helpful in the scenario, where mobile device offloads part of the task to available devices. In this paper, we propose an algorithm AOA (Alternately Optimizing Algorithm) to alternatively optimize task and power allocation in order to achieve the minimum system energy consumption under given time constraint. KM (Kuhn-Munkres) algorithm in graph theory is adopted to get the optimal task assignment. And we get the optimal solution for power allocation via mathematical derivation. Simulations have shown that the proposed algorithm can give a global optimal task and power allocation solution.
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Acknowledgements
This work is supported by National Natural Science Foundation of China (No. 61171097 and No. 61771072). We thank the reviewers and editors for their helpful comments.
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Zhou, X., Zhang, Y., Ma, T. (2018). Computing Offloading to Save Energy Under Time Constraint Among Mobile Devices. In: Yuan, H., Geng, J., Liu, C., Bian, F., Surapunt, T. (eds) Geo-Spatial Knowledge and Intelligence. GSKI 2017. Communications in Computer and Information Science, vol 849. Springer, Singapore. https://doi.org/10.1007/978-981-13-0896-3_38
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DOI: https://doi.org/10.1007/978-981-13-0896-3_38
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