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Abstract
En 中文
This paper addresses multi-access multi-server multi-task resource allocation in mobile edge computing (MEC). Our aim is to maximize social welfare for heterogeneous MEC servers from multiple access points (APs) providing heterogeneous virtual machine instances to the mobile devices (MDs) within the coverage area. In the system model, each MD has multiple tasks, and tasks can offload to more than one MEC server through different APs within its direct communication range. We formulated the problem with an auction-based model to provide flexible service. However, the MDs are self-interested and can misreport their preferences, leading to inefficient resource allocation. We designed an optimal approximation mechanism to solve this problem. Then, we showed that this mechanism achieves individual rationality and truthfulness, that is, the MDs had no incentive to declare untrue values. In addition, we analyzed the approximation ratio of our truthfulness mechanism. The task allocation problem was also considered, and the proposed approximation algorithm could stop at any step and provide reasonable performance. Experimental results demonstrated that our proposed approximation mechanism provides near-optimal social welfare in a reasonable time and effectively reduces energy consumption.
Keywords:
Mobile edge computing
Truthfulness
Resource allocation
Energy consumption
Algorithm design
Journal
IF:
2.6
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2.2K
Citations:
2.9K