Improved Particle Swarm Optimization-Based Computation Offloading and Caching Decision for Internet of Things
Ke Yuan, Siguang Chen · 2022 IEEE/CIC International Conference on Communications in China (ICCC) · 2022
For satisfying the demands of resource-intensive and delay-sensitive applications, an intelligent computation offloading which jointly optimizes offloading and caching decisions, local CPU computation speed and edge sever (ES)'s transmission power to minimize the total cost is proposed. Then we utilize the mathematical method to reduce four optimization variables to three variables and add the penalty mechanism to transform the constrained optimization problem into the unconstrained optimization problem. To solve the above non-convex problem, we proposed an improved particle swarm optimization (PSO)-based computation offloading and caching decision (WPSO-COC) algorithm. Based on traditional PSO, our algorithm adopts the adaptive inertia weight to avoid falling into local optimum and obtain the optimal policy which adapts to the dynamic network environment with the ability of autodidacticism. Finally, the simulation results demonstrate that the WPSO-COC can converge at a faster rate and reduce the total cost significantly compared with other methods.