Joint Task Offloading and Resource Allocation: A Historical Cumulative Contribution Based Collaborative Fog Computing Model

Abstract

Effective inter-node collaborative strategy can significantly improve fog computing (FC) system performance, thereby enhancing the users' quality of experience (QoE). With more and more smart personal devices serving as fog nodes (FNs) to assist users or other FNs, it is challenging to achieve effective collaboration among these FNs with selfishness. In this paper, a collaborative FC model is developed for achieving distributed collaborative processing of computational loads on the fog layer by data offloading and forwarding. Then, with this model, we propose a joint optimization problem to minimize the task execution delay of user equipments (UEs). Considering the trade-off between low delay and fairness of collaboration, we propose a historical cumulative contribution based inter-node collaboration algorithm (HCCCA) to derive the optimal task offloading and resource allocation decisions for FNs. Finally, the simulation results illustrate that HCCCA is much more effective compared with conventional schemes.