FogBus3: A scalable and reliable framework for integrated IoT and fog computing scenario. Issue 9 (9th May 2022)

• Record Type: Journal Article
• Authors: Verma, Richa; Chandra, Shalini
• Is Part Of: Transactions on emerging telecommunications technologies. Volume 33:Issue 9(2022)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2022-05-09
• Subjects: Telecommunication -- Periodicals; 384.05
• DOI: 10.1002/ett.4535
• Languages: English
• ISSNs: 2161-5748

Abstract

Abstract: Fog computing is an advantageous concept that works in consonance with cloud computing to enhance user experience. It presents innumerable benefits such as low latency, bandwidth saving, and location awareness. But, just being opportunistic towards the platform without checking it for security is not at all justifiable. As more and more sensitive data flows through the fog layer, it becomes mandatory to examine it for security. The fog nodes being closer to the user end are highly vulnerable to being malicious. There exists a possibility that a faulty fog node tries to tamper the data generated from the Internet of things (IoT) device layer and restrains the other functioning nodes to operate upon a common perceived value. In this regard, the authors have proposed the FogBus3 framework that guarantees reliable results from the fog level even in the presence of faulty fog nodes. The proposed framework adds a job categorization mechanism and a reliability ensuring IoT‐Fog Agreement Algorithm (IFAA) to the fog layer. The proposed framework has been thoroughly examined with the help of a working example and simulated through MATLAB R2021a. Further, the scenario has been tested before and after implementation of the proposed algorithm on the basis of execution time. Experimental results show that FogBus3's IFAA algorithm improves the execution time of the said setup by 41%. FogBus3 has also been evaluated for its scalability and is believed to ensure reliability in the said scenario. Abstract : The authors have proposed an agreement algorithm that guarantees reliable results from the fog level even in the presence of faulty fog nodes. In the figure, fn4 is faulty fog node because of which the agreement is restrained. After the application of the proposed algorithm, the problem is resolved.