Resource Allocation for 5G Network Considering Privacy Protection in Edge Computing Environment

Abstract

In the field of Internet of Things, mobile communication will be deeply integrated with industrial construction, biomedicine, agricultural production, transportation and other industries to fully realize the “Internet of Everything” and realize smart city and sustainable development. This paper intends to solve problems in increasing latency and consumption of energy and security after deploying Mobile Edge Computing (MEC) servers in single cell multi-user network model, and has advocated a strategy of allocating the resources of 5G communication in regards to the protection mechanism for privacy in the environment of edge computing. First of all, solution model for the problem is characterized as a model with time delay and energy consumption. Second, privacy is used to measure the uncertainty of data in order to quantify privacy data while computing the allocation of tasks and facilitate the design of objective function. Finally, the task migration problem of minimizing energy consumption under the limitation of completion time is constructed as a nonlinear 0–1 programming problem. Besides, we design the optimal resource allocation strategy of discrete algorithm of binary particle swarm optimization (BPSO) for problem solution. Results indicate that while the quantity of users is 100, the total user expenditure of proposed method is 18.3J, which is lower than 20.0J and 30.7J of the compared methods. Moreover, the proposed method has lower latency and energy consumption, which can well balance the load of MEC servers.