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Li, Y., Wang, X., Gan, X., Jin, H., Fu, L. and Wang, X. (2020) Learning-Aided Computation Offloading for Trusted Collaborative Mobile Edge Computing. IEEE Transactions on Mobile Computing, 19, 2833-2849. https://doi.org/10.1109/TMC.2019.2934103

has been cited by the following article:

• TITLE: Task Offloading Scheduling with Time Constraint for Optimizing Energy Consumption in Edge Cloud Computing

  AUTHORS: Shufa Wen, Hongzhi Xu

  KEYWORDS: Edge Cloud Computing, Offloading Scheduling, Improving Genetic Algorithms, Limited Latency, Optimal Energy Consumption

  JOURNAL NAME: Open Access Library Journal, Vol.10 No.11, November 29, 2023

  ABSTRACT: In this paper, an improved genetic algorithm with delay constraint was designed. When initializing the population, a greedy strategy was adopted to ensure that there were enough excellent genes in the initial population, a normal distribution ordering selection strategy was adopted when selecting the next generation, so that high-quality chromosomes have a greater probability of being selected, and an adaptive cross-mutation strategy was proposed to achieve dynamic probability when cross-mutation was carried out to avoid the problem that the algorithm was easy to fall into the local optimal solution in the later stage, and at the same time, a maximum subsegment crossover strategy and a discardable mutation strategy were proposed to solve the problem of individual solution deterioration after crossover.