Abstract
Edge computing shows great potential in enhancing the energy efficiency of mobile users by transferring computation tasks to edge servers that are physically proximal and more resourceful. However, when numerous mobile users vie for limited wireless and computing resources, the energy consumption and task completion time can be significantly affected. To ensure that the Quality of Service (QoS) requirements are met, it is necessary to jointly make task offloading decisions and optimize resource allocations. In this chapter, we introduce both deterministic QoS guarantee and statistical QoS guarantee for computation offloading. We provide general models for energy consumption and delay in both computation and communication processes. To provide the deterministic QoS guarantee, we propose a distributed algorithm based on game theory. For tasks requiring statistical QoS guarantee, we propose a distributed algorithm that utilizes convex optimization theory and Gibbs sampling method. The numerical results confirm that the proposed algorithm offers asymptotically optimal performance and can considerably enhance the QoS of mobile users.
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© 2024 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
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Ma, X., Xu, M., Li, Q., Li, Y., Zhou, A., Wang, S. (2024). Edge Computing Based Computation Offloading. In: 5G Edge Computing. Springer, Singapore. https://doi.org/10.1007/978-981-97-0213-8_4
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DOI: https://doi.org/10.1007/978-981-97-0213-8_4
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