Improved Particle Swarm Optimization Based Workflow Scheduling in Cloud Fog Environment
Mobile edge devices with high requirements typically need to obtain faster response on local network services. Fog computing is an emerging computing paradigm motivated by this need, which currently is viewed as an extension of cloud computing. This computing paradigm is presented to provide low commutation latency service for workflow applications. However, how to schedule workflow applications for seeking the tradeoff between makespan and cost in cloud fog environment is facing huge challenge. To address this issue, in current paper, we propose a workflow scheduling algorithm based on improved particle swarm optimization (IPSO) where a nonlinear decreasing function of inertia weight in PSO is designed for promoting PSO to gain the optimal solution. Finally, comprehensive simulation experiment results show that our proposed scheduling algorithm is more cost effective and can obtain better performance than baseline approach.
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