Probabilistic Task Assignment in Edge Computing

Recently, edge computing has attracted a lot of attention from academia and industry. One of the important problems in edge computing is the task assignment problem. Many task assignment optimization problems in the literature do not consider uncertain parameters. In this paper, we adopt the chance-constrained method as a powerful paradigm to model uncertainty in our task assignment optimization problem. Chance-constrained programming is one of the most difficult classes of optimization problems. To solve our defined problem, we propose a method called FMS that finds the optimal solution accurately and quickly. We first transform the original probabilistic problem into an equivalent problem using the Gauss error function, and then rely on an auxiliary problem to decrease the search space and find the candidate points that lead to the optimal solution and, therefiire, solve the defined problem. Simulation results confirm the correctness and efficiency of our method.