A Generalized Nash Game for Mobile Edge Computation Offloading

Genetic Algorithm-Based Optimization of Offloading and Resource Allocation in Mobile-Edge Computing

“…Simulation results demonstrate that our proposed algorithm can effectively shorten the completion time and guarantee fairness among users. For example, when the UD's number is 10, the total completion time in this paper is 12.1% lower than that in literature [18].…”

“…The figure illustrates that the larger the distributable resources are, the stronger the fairness is. Compared with the literature [18], the UD's completion time in this paper was fairer. Figure 7 shows the simulation results of the comparison of the UD numbers and the UD's fairness when B max = 10 MHz, F max = 5 GHz/s and compares the algorithm of this paper with the algorithm of [18].…”

“…As the number of UDs increases, other algorithms approach this value. Algorithm [18] does not consider the allocation of bandwidth and MES computing resources, resulting in a waste of resources, so the overall completion time of this paper is faster. In conclusion, both the optimized bandwidth and the computing resources can get a fast total completion time.…”

“…In conclusion, both the optimized bandwidth and the computing resources can get a fast total completion time. and compares the algorithm of this paper with the algorithm of [18]. In this paper, the standard deviation of time was used to reflect the fairness of users [22] and the metric was given by: where t is the average task completion time of all UDs.…”

“…Energy consumption at both the user and edge devices was considered herein. In [18], the optimized user offloading strategy algorithm based on game theory was put forward in a transmission queue model, and the optimization goal was defined as the overall time computing task to all users, but it only considered each user's offloading proportion and did not take channel resources and MES computing resources into account. So far, according to the partly offloading task model, there has been a limited joint allocation of partly offloading strategies and communication resources to minimize the completion time mechanism of user devices' (UDs') overall task.…”