An Optimized Task Placement in Computational Offloading for Fog-Cloud Computing Networks
Indranil Sarkar, Sanjay Kumar, Mithun Mukherjee · 2019
The association between the fog node and the cloud in fog-cloud computing enables task data offloading for the delay-sensitive services generated from the end-users. Limited by the computational and storage resources, it is nearly impossible to execute the entire task by itself for an end-user. In this paper, we study the cooperation among fog node and the remote cloud. The task data offloading policies becomes a challenging issue when a fog node further offloads the task data to a set of neighbor fog node. We propose a task data offloading policy to find the optimum values of the amount of the offloaded tasks to each of the neighbor fog nodes and to the cloud. Besides, where to process the tasks and how many fog nodes are required for the tasks are also important to be considered. The optimization problem is formulated as a Quadratically Constraint Quadratic Programming (QCQP) and provide a solution. The extensive simulation results show the significant performance improvement in terms of delay minimization compared with several stand-alone task data execution with the increase of traffic intensity levels.