Energy-efficient user association with load-balancing for cooperative IIoT network within B5G era

As one of the key technologies of 5G wireless communication technology, cooperative multi-access edge computing allows one device to associate multiple edge nodes simultaneously, namely multi-association, which can provide scalable communication services with characteristics of high reliability, massive connectivity and low latency for promising Industrial Internet of Things (IIoT). Effective association between edge nodes and devices is the prerequisite for providing high quality communication services in dense deployed IIoT networks. Most of state of art researches focus on the user association problem in single-association scenario. There are rarely no solutions presented for the considered user association problem with multi-association. In this paper, user association, power allocation and edge node deployment are jointly considered for load balance and energy efficiency under the multi-association mechanism. The problem is formulated as a nested knapsack optimization problem (NKOP) with energy efficiency and load balancing as objective functions and power and signal quality as constraints. Differential evolution with Monte Carlo and sequential quadratic programming (DMS) algorithm is proposed to solve this problem, which decouples the problem into three parts, user association, power allocation and optimizing the location of edge nodes. Numerical results show that: (1) Compared with the single-association, multi-association with power allocation can provide better signal quality and improve energy efficiency; (2) Proposed DMS algorithm is feasible and stable for optimal deployment of edge nodes. These works together provide good reference for edge node deployment of high-density IIoT application scenarios.