Hierarchical fuzzy‐based Quality of Experience (QoE)‐aware application placement in fog nodes. (6th September 2022)

• Record Type: Journal Article
• Authors: Mirampalli, Sreenivasu; Srirama, Satish Narayana; Wankar, Rajeev; Chillarige, Raghavendra Rao
• Is Part Of: Software, practice & experience. Volume 53:Number 2(2023)
• Page Start: 263
• Page End: 282
• Publication Date: 2022-09-06
• Subjects: fog computing -- fuzzy logic -- Hungarian maximization assignment algorithm -- IoT -- quality of experience; Computer software -- Periodicals; Computer programming -- Periodicals; Computer programs -- Periodicals; 005.3
• DOI: 10.1002/spe.3147
• Languages: English
• ISSNs: 0038-0644

Abstract

Abstract: Fog computing or a fog network is a decentralized network placed in between data source and the cloud to minimize the network latency issues and thus support in‐time service delivery, of Internet of Things (IoT) applications. However, placing computational tasks of IoT applications in fog infrastructure is a challenging task. State of the art focuses on quality of service and quality of experience (QoE) based application placement. In this article, we design hierarchical fuzzy based QoE‐aware application placement strategy for mapping IoT applications with compatible instances in the fog network. The proposed method considers user application expectation parameters and metrics of available fog instances, and assigns the priority of applications using hierarchical fuzzy logic. The method later uses Hungarian maximization assignment algorithm to map applications with compatible instances. The simulation results of the proposed policy show better performance over the existing baseline algorithms in terms of resource gain (RG), processing time reduction ratio (PTRR), and similarly network relaxation ratio. When considering 10 applications in the fog network, our proposed method simulation results show 70.00%, 22.44%, 37.83% improvement in RG, and 28.46%, 37.5%, 23.07% improvement in PTRR, when compared with QoE‐aware, randomized, FIFO algorithms, respectively.