Clustering-Based Energy Efficient Task Offloading for Sustainable Fog Computing

Delay and energy efficient task offloading from device to fog nodes involves decision making challenges wherein an integrated optimal scheme for preserving sustainability of the terminal nodes (TNs) and fog nodes (FNs) is extremely important. In this paper, we propose a novel clustering based delay aware energy efficient task offloading scheme in a Software-Defined Networking (SDN) based fog architecture. A bi-objective problem is formulated for optimum clustering of TNs with respect to FNs, selection of offloading parameters and, joint delay and energy minimization. It is then tranformed to a scalarized single objective problem which has a nested structure with the two problems: 1) optimal clustering and 2) optimal offloading for a given set of clusters. Based on this, Optimal Clustering and Offloading Parameters (OCOP) algorithm is designed which has lesser time complexity than the usual quadratic case. Through extensive simulations, we have shown that the use of explicit clustering in the proposed algorithm improves FN participation and reduces activity time and energy levels thereby increasing sustainability of the FNs and TNs as compared with the random case and a similar task offloading algorithm. Moreover, even cluster size distribution lowers our algorithm's running time than the quadratic case.