Workflow Scheduling and Offloading for Service-based Applications in Hybrid Fog-Cloud Computing

Saleh M Altowaijri

doi:10.14569/ijacsa.2021.0121290

Abstract

Workflow Scheduling and Offloading for Service-based Applications in Hybrid Fog-Cloud Computing

Highlights

In recent years, new computing paradigms, named fog computing [1]–[5] and edge computing [6]–[11] have emerged as an extension of cloud architecture to the edge of the network to support the computational demands of real-time, latency-sensitive, and location-aware service-based applications (SBA) of largely distributed Internet-of-Things (IoT) devices/sensors
Different well-known standardized workflow can be plugged in our proposed workflow scheduling models to study their various performance behaviors including network load, average response delay, energy consumption, and energy cost, and this can be done for a range of cloud-only, cloud-fog, and cloudwww.ijacsa.thesai.org (IJACSA) International Journal of Advanced Computer Science and Applications, Vol 12, No 12, 2021 fog-edge systems
This paper provided a detailed study of workflow scheduling and offloading of service-based applications

Summary

Introduction

New computing paradigms, named fog computing [1]–[5] and edge computing [6]–[11] have emerged as an extension of cloud architecture to the edge of the network to support the computational demands of real-time, latency-sensitive, and location-aware service-based applications (SBA) of largely distributed Internet-of-Things (IoT) devices/sensors. Fog computing refers to the computing at the intermediate layers between cloud data centers and IoT devices (many works have considered such definitions, see [3], for example). Edge and Fog layers have been proposed to bridge the gap between the cloud and IoT devices by enabling data management, computing, networking, storage, and application services at the intermediate layers and edge of the network while offering the possibility to interact with the cloud. The development and management of fog-based and edge-based systems for SBA face many challenges that need to be tackled. These include investigating and designing applications and systems for these emerging computing paradigms. One of the core challenging issues is workflow scheduling and offloading in such a dynamic, geo-distributed, heterogeneous environment where the set of computing nodes contains edge nodes, fog nodes, and cloud datacenters such as discussed in many works in the literature [19]–[23]

Methods

Results

Conclusion