Quantum-Inspired PSO Based User Allocation in Edge Computing Systems

The growth of mobile and IoT devices has been tremendous in the edge computing (EC) environment. The device users (DUs) require high computational resources to run resource-intensive applications appropriately. Thus the efficient allocation of DUs in the EC environment known as the user allocation problem (UAP) is a crucial challenge considering various resource and time constraints. This paper proposes a quantum-inspired particle swarm optimization-based user allocation strategy (QIPSO-UA) for efficient user allocation in EC systems. Firstly, the UAP problem is mathematically formulated. Then the quantum particles (QPs) are designed to provide a complete and valid solution to the UAP. The quality of each solution is evaluated with the designed fitness function by considering user allocation rate (UAR), total computational delay, and load balance of the system. Extensive simulations in various scenarios have been conducted to evaluate the performance of the proposed QIPSO-UA. The simulation results show the superiority of the proposed QIPSO-UA compared to well-known meta-heuristic approaches such as PSO and DE.