Research On Joint Resource Management Algorithm In Edge Access Network

The rapid development of wireless mobile communication technology leads to the surge of mobile Internet data.As user data usually need to be processed and stored in the cloud data center and content server in the core network,hence,the congestion of backhaul link in the edge access network might occur and the end-to-end delay may increase,thereby the overall quality of experience of users is affected severely.In order to tackle this problem,edge caching technology and edge computing technology are proposed as two promising approaches for achieving the storage and computing of required data at the edge of the network.Moreover,in order to alleviate the load of the network resources,it is quite important to design reasonable joint resource management algorithms.In this thesis,the joint resource management algorithms for edge access networks are studied.The main contents of this thesis are summarized as follows:Firstly,based on the brief introduction of the characteristics and architecture of the edge access network,the key technologies of resource management for edge access network are described,and the edge access network resource management algorithms are analyzed and summarized in this thesis.For a cache-enabled edge access network consisting of multiple base stations,multiple wireless access points and multiple users,a joint user association and cache content placement optimization algorithm is proposed.Considering the constraints on the user service requirement and the network resource,this thesis defines network cost as the weighted sum of the total download delay of the users and content cache cost in the network,and formulates the joint user association and content placement problem as a network cost minimization problem.Since the optimization problem is a nonlinear integer optimization problem,by applying the McCormick envelopes and Lagrange partial relaxation method,the original optimization problem can be equivalently transformed into three convex subproblems.An iterative algorithm based on Kuhn-Munkres(K-M)algorithm and subgradient algorithm is proposed to iteratively solve the optimization problem.The globally optimal joint user association and cache content placement optimization strategy can be obtained.For an edge access network composed of multiple small cell base stations and multiple users,where cloudlet servers are colocated at the small cell base stations.A joint computing offloading and radio resource allocation algorithm is proposed.Assuming that each user in the system has a computation task to complete,taking into account the maximum delay tolerance of the tasks,this thesis formulates joint offloading decision and user transmission power allocation optimization problem as an energy consumption minimization problem.Since the optimization problem is a mixed integer nonlinear optimization problem,the optimization problem is equivalently decomposed into multiple power allocation subproblems and an offloading decision subproblem.By applying a proposed iterative algorithm and modified K-M algorithm,the subproblems can be effectively solved,and the joint offloading decision and user transmission power allocation optimization strategy is obtained.