Overbooking-enabled Virtual Machine Deployment Approach in Mobile Edge Computing

Abstract

Mobile Edge Computing (MEC) integrates computing, storage and other resources on the edge of the network and constructs a unified user service platform. Then, according to the principle of nearest service, MEC responds to the task requests of the edge nodes in time and effectively processes them. In MEC, edge servers are virtualized into several slots so that resources can be shared among different mobile users. However, there are many unpredictable risks in MEC, these risks can cause edge servers to fail, the virtual machine deployed in the server slot fails and the task cannot be executed normally. The introduction of primary-backup virtual machines solves this problem well. However, when the primary virtual machine is working normally, its backup virtual machine is idle, this will result in a waste of resources. In order to improve the resource utilization of the system, this paper firstly overbooks the backup virtual machine reasonably, and then formulates the virtual machine deployment problem as a combinatorial optimization problem. Finally, Virtual Machine Deployment Algorithm (VMDA) is proposed based on genetic algorithm. With the increase of the number of algorithm iterations and the population size of the virtual machine deployment scheme, there may be more optimal virtual machine deployment scheme individuals in the population. Therefore, the algorithm can obtain the approximate optimal value of resource utilization within the risk range allowed by the system, and the algorithm is compared with two other typical bin packing algorithms. The results confirm that VMDA outperforms the other two algorithms.