Sensors, Vol. 19, Pages 3830: Online Workload Allocation via Fog-Fog-Cloud Cooperation to Reduce IoT Task Service Delay

Sensors, Vol. 19, Pages 3830: Online Workload Allocation via Fog-Fog-Cloud Cooperation to Reduce IoT Task Service Delay
Sensors doi: 10.3390/s19183830
Authors:
Li
Guo
Ma
Mao
Guan

Fog computing has recently emerged as an extension of cloud computing in providing high-performance computing services for delay-sensitive Internet of Things (IoT) applications. By offloading tasks to a geographically proximal fog computing server instead of a remote cloud, the delay performance can be greatly improved. However, some IoT applications may still experience considerable delays, including queuing and computation delays, when huge amounts of tasks instantaneously feed into a resource-limited fog node. Accordingly, the cooperation among geographically close fog nodes and the cloud center is desired in fog computing with the ever-increasing computational demands from IoT applications. This paper investigates a workload allocation scheme in an IoT–fog–cloud cooperation system for reducing task service delay, aiming at satisfying as many as possible delay-sensitive IoT applications’ quality of service (QoS) requirements. To this end, we first formulate the workload allocation problem in an IoT-edge-cloud cooperation system, which suggests optimal workload allocation among local fog node, neighboring fog node, and the cloud center to minimize task service delay. Then, the stability of the IoT-fog-cloud queueing system is theoretic...

Source: Sensors - September 3, 2019 Category: Biotechnology Authors: Li Guo Ma Mao Guan Tags: Article Source Type: research