Abstract
Recently, due to the limitations in using cloud computing services for the recent advances IoTs applications, a newly distributed computing architecture is established called cloud-fog paradigm by exploiting the cooperation between fog and cloud entities. Fog nodes are used to reduce monetary cost and transferring latency for cloud resources, while for offloading of large-scale applications cloud servers are used. In this paradigm, The main problem is task allocation which aims to select the optimal nodes among cloud and fog nodes for each task to minimize makespan, monetary and energy costs. In this paper, to solve this problem a new task allocation approach called bipartite graph with fuzzy clustering task allocation approach is proposed and it uses a hybrid DAG for representing independent and dependent tasks. Also, it uses fuzzy clustering and bipartite graph to solve the uncertainty executing problem and find the maximum bipartite matching, respectively. The conducted simulation results show that the proposed approach can achieve a higher performance int terms of makespan, total cost, and cost-makespan tradeoff than existing approaches.