2021/08/02 by Mohammad Ali Goudarzi, Goudarzi, Mohammad, Qifan Deng +3 · 3 citations
Computer Science · #Cloud Computing and Resource Management #Distributed #Energy Efficient Wireless Sensor Networks #FOS: Computer and information sciences #FOS: Electrical engineering #IoT and Edge/Fog Computing #Networking and Internet Architecture (cs.NI) #Parallel #Performance (cs.PF) #Systems and Control (eess.SY) #and Cluster Computing (cs.DC) #electronic engineering #information engineering
paper · pdf · doi:10.48550/arxiv.2108.00591
openalex publication_date 2021/08/02 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Edge/Fog computing is a novel computing paradigm that provides resource-limited Internet of Things (IoT) devices with scalable computing and storage resources. Compared to cloud computing, edge/fog servers have fewer resources, but they can be accessed with higher bandwidth and less communication latency. Thus, integrating edge/fog and cloud infrastructures can support the execution of diverse latency-sensitive and computation-intensive IoT applications. Although some frameworks attempt to provide such integration, there are still several challenges to be addressed, such as dynamic scheduling of different IoT applications, scalability mechanisms, multi-platform support, and supporting different interaction models. FogBus2, as a new python-based framework, offers a lightweight and distributed container-based framework to overcome these challenges. In this chapter, we highlight key features of the FogBus2 framework alongside describing its main components. Besides, we provide a step-by-step guideline to set up an integrated computing environment, containing multiple cloud service providers (Hybrid-cloud) and edge devices, which is a prerequisite for any IoT application scenario. To obtain this, a low-overhead communication network among all computing resources is initiated by the provided scripts and configuration files. Next, we provide instructions and corresponding code snippets to install and run the main framework and its integrated applications. Finally, we demonstrate how to implement and integrate several new IoT applications and custom scheduling and scalability policies with the FogBus2 framework.