In this paper, we consider sequential task offloading to multiple mobile-edge computing servers to providing ultra-reliable low- latency mobile edge computing. The task consists of a set of sub-tasks, with a general dependency model among sub-tasks. Our objective is to minimize both latency and offloading failure probability by scheduling sub-tasks to servers. We formulate an optimization problem with constraints over binary scheduling decision variables. A genetic algorithm is devised to solve the formulated optimization problems. Simulation results show that the proposed algorithm provides performance close to the optimal solution, which is obtained through exhaustive search.
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Al-Habob et al. (2019) studied this question.
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