Multi-stream adaptive offloading scheme based on mobile edge computing
The transmission and analysis of massive video streams require significant edge bandwidth and computa-tional resources,posing severe challenges to the current multimedia frameworks based on mobile edge computing(MEC).To address this issue,an adaptive offloading scheme based on a multi-stream collaborative optimization framework was proposed.Firstly,under the constraint of the long-term MEC energy budget,the processing cost of video tasks was minimized by optimizing the data stream selection decisions,server offloading decisions,bandwidth resource allocation,and computing resource allocation.Then,based on the Lyapunov optimization method,the long-term optimization problem was transformed into independent deterministic subproblems for each time slot,and the mixed-integer nonlinear programming problems for each time slot were solved by Markov approximation and KKT conditions.Simulation results indicate that the proposed scheme not only meets the long-term MEC energy constraint,but also significantly outperforms existing benchmark schemes in terms of cost performance.
mobile edge computingmulti-stream adaptive offloadingvideo processingLyapunov optimization
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