Towards power consumption-delay tradeoff by workload allocation in cloud-fog computing

TLDR

Fog computing extends cloud services to the network edge, acting as a powerful complement rather than a replacement. The study investigates the interaction and cooperation between fog (edge) and cloud (core) resources. The authors formulate a workload‑allocation problem and propose an approximate solution that decomposes the primal problem into three independently solvable subproblems for the respective subsystems. Simulations demonstrate that modestly reducing computation resources to save bandwidth and lower latency enables fog computing to markedly enhance cloud performance.

Abstract

Fog computing, characterized by extending cloud computing to the edge of the network, has recently received considerable attention. The fog is not a substitute but a powerful complement to the cloud. It is worthy of studying the interplay and cooperation between the edge (fog) and the core (cloud). To address this issue, we study the tradeoff between power consumption and delay in a cloud-fog computing system. Specifically, we first mathematically formulate the workload allocation problem. After that, we develop an approximate solution to decompose the primal problem into three subproblems of corresponding subsystems, which can be independently solved. Finally, based on extensive simulations and numerical results, we show that by sacrificing modest computation resources to save communication bandwidth and reduce transmission latency, fog computing can significantly improve the performance of cloud computing.