Task Offloading Scheduling in Fog Computing Using Hybrid Genetic Algorithm
Samaa Aleteemat, Mohammad M. Shurman · 2023
Fog computing is a new paradigm used to process high-intensive tasks from IoT devices with low latency requirements. Therefore, to improve the quality of services and user satisfaction the offloaded tasks should be assigned and distributed over fog nodes effectively. However, achieving this goal is still challenging in fog networks due to the heterogeneity and dynamic distribution of the resources in the system. Task scheduling is an NP-Complete problem, heuristic and metaheuristic algorithms are used to find the best and optimal solution. This research proposes a hybrid genetic algorithm to search for the optimal task scheduling scheme. In the proposed method, a bi-objective optimization approach is presented to minimize the completion time and communication cost in fog systems. The experiment has been working in more than one stage, and the initial results show that our method is valid to use for optimizing task scheduling problems.