Titlebook: Energy Efficient Computation Offloading in Mobile Edge Computing; Ying Chen,Ning Zhang,Sherman Shen Book 2022 The Editor(s) (if applicable

傻

高歌

Dynamic Computation Offloading for Energy Efficiency in Mobile Edge Computing,r challenges faced with this problem. For example, the uncertainty of wireless channel states and the dynamics of task arrivals make it very complex to solve this problem. In this chapter, we take advantage of stochastic optimization techniques to solve this problem, and propose the distributed EEDC

Admonish

Energy Efficient Offloading and Frequency Scaling for Internet of Things Devices,ed into two sub-problems. Then, a Computation Offloading and Frequency Scaling for Energy Efficiency (COFSEE) algorithm for online task offloading and frequency transformation is proposed. Our algorithm can solve optimal subproblems in parallel. We evaluate the performance of COFSEE algorithm throug

Hypomania

Clinch

Energy-Efficient Multi-Task Multi-Access Computation Offloading via NOMA,annel realizations in the dynamic scenario, this chapter proposes an online algorithm, which is based on deep reinforcement learning (DRL), to efficiently learn the near-optimal offloading solutions for the time-varying channel realizations. Numerical results are provided to validate the proposed la

史前

Gentry

burnish

Soziale Identitäten Jugendlicherng, and proposes the energy-efficient computation offloading solutions. Since the wireless channel state and task request arrival process are stochastic and dynamic, designing a dynamic and energy-efficient task offloading strategy faces severe challenges. This chapter introduces the background and

漫不经心

Degener Theresia,Mogge-Grotjahn Hildegardr challenges faced with this problem. For example, the uncertainty of wireless channel states and the dynamics of task arrivals make it very complex to solve this problem. In this chapter, we take advantage of stochastic optimization techniques to solve this problem, and propose the distributed EEDC

天空

,Das europäische Mehrebenensystem,ed into two sub-problems. Then, a Computation Offloading and Frequency Scaling for Energy Efficiency (COFSEE) algorithm for online task offloading and frequency transformation is proposed. Our algorithm can solve optimal subproblems in parallel. We evaluate the performance of COFSEE algorithm throug