Abstract
Mobile edge computing (MEC) casts the computation-intensive and delay-sensitive applications of mobiles on the network edges. Task offloading incurs extra communication latency and energy cost, and extensive efforts have been focused on the offloading scheme. To achieve satisfactory quality of experience, many metrics of the system utility are defined. However, most existing works overlook the balancing between the throughput and fairness. This paper investigates the problem of seeking optimal offloading scheme and the objective of the optimization is to maximize the system utility for leveraging between throughput and fairness. Based on KKT condition, we analyze the expectation of time complexity for deriving the optimal scheme. We provide an increment based greedy approximation algorithm with \(1 + \frac{1}{{e - 1}}\) ratio. Experimental results show that the proposed algorithm has better performance.
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Acknowledgments
This work is supported in part by the National Natural Science Foundation of China (61602084, 61602080, 61772112, 61761136019), the Post-Doctoral Science Foundation of China (2016M600202), the Doctoral Scientific Research Foundation of Liaoning Province (201601041), the Fundamental Research Funds for the Central Universities (DUT19JC53).
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Bi, R., Ren, J., Wang, H., Liu, Q., Yang, X. (2019). Utility Aware Task Offloading for Mobile Edge Computing. In: Biagioni, E., Zheng, Y., Cheng, S. (eds) Wireless Algorithms, Systems, and Applications. WASA 2019. Lecture Notes in Computer Science(), vol 11604. Springer, Cham. https://doi.org/10.1007/978-3-030-23597-0_44
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DOI: https://doi.org/10.1007/978-3-030-23597-0_44
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