Abstract
Energy consumption plays a key role in determining the cost of services in edge computing systems and has a significant environmental impact. Therefore, minimizing the energy consumption in such systems is of critical importance. In this paper, we address the problem of energy-aware optimization of capacity provisioning and resource allocation in edge computing systems. The main goal is to provision and allocate resources such that the net profit of the service provider is maximized, where the profit is the difference between the aggregated users’ payments and the total operating cost due to energy consumption. We formulate the problem as a mixed integer linear program and prove that the problem is NP-hard. We develop a heuristic algorithm to solve the problem efficiently. We evaluate the performance of the proposed algorithm by conducting an extensive experimental analysis on problem instances of various sizes. The results show that the proposed algorithm has a very low execution time and is scalable with respect to the number of users in the system.
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Bahreini, T., Badri, H., Grosu, D. (2019). Energy-Aware Capacity Provisioning and Resource Allocation in Edge Computing Systems. In: Zhang, T., Wei, J., Zhang, LJ. (eds) Edge Computing – EDGE 2019. EDGE 2019. Lecture Notes in Computer Science(), vol 11520. Springer, Cham. https://doi.org/10.1007/978-3-030-23374-7_3
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DOI: https://doi.org/10.1007/978-3-030-23374-7_3
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