Mohammad Aknan, Maheshwari Prasad Singh, Rajeev Arya
{"title":"AI and Blockchain Assisted Framework for Offloading and Resource Allocation in Fog Computing","authors":"Mohammad Aknan, Maheshwari Prasad Singh, Rajeev Arya","doi":"10.1007/s10723-023-09694-7","DOIUrl":null,"url":null,"abstract":"<p>The role of Internet of Things (IoT) applications has increased tremendously in several areas like healthcare, agriculture, academia, industries, transportation, smart cities, etc. to make human life better. The number of IoT devices is increasing exponentially, and generating huge amounts of data that IoT nodes cannot handle. The centralized cloud architecture can process this enormous IoT data but fails to offer quality of service (QoS) due to high transmission latency, network congestion, and bandwidth. The fog paradigm has evolved that bring computing resources at the network edge for offering services to latency-sensitive IoT applications. Still, offloading decision, heterogeneous fog network, diverse workload, security issues, energy consumption, and expected QoS is significant challenges in this area. Hence, we have proposed a Blockchain-enabled Intelligent framework to tackle the mentioned issues and allocate the optimal resources for upcoming IoT requests in a collaborative cloud fog environment. The proposed framework is integrated with an Artificial Intelligence (AI) based meta-heuristic algorithm that has a high convergence rate, and the capability to take the offloading decision at run time, leading to improved results quality. Blockchain technology secures IoT applications and their data from modern attacks. The experimental results of the proposed framework exhibit significant improvement by up to 20% in execution time and cost and up to 18% in energy consumption over other meta-heuristic approaches under similar experimental environments.</p>","PeriodicalId":54817,"journal":{"name":"Journal of Grid Computing","volume":"7 1","pages":""},"PeriodicalIF":3.6000,"publicationDate":"2023-11-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Grid Computing","FirstCategoryId":"94","ListUrlMain":"https://doi.org/10.1007/s10723-023-09694-7","RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"COMPUTER SCIENCE, INFORMATION SYSTEMS","Score":null,"Total":0}
引用次数: 0
Abstract
The role of Internet of Things (IoT) applications has increased tremendously in several areas like healthcare, agriculture, academia, industries, transportation, smart cities, etc. to make human life better. The number of IoT devices is increasing exponentially, and generating huge amounts of data that IoT nodes cannot handle. The centralized cloud architecture can process this enormous IoT data but fails to offer quality of service (QoS) due to high transmission latency, network congestion, and bandwidth. The fog paradigm has evolved that bring computing resources at the network edge for offering services to latency-sensitive IoT applications. Still, offloading decision, heterogeneous fog network, diverse workload, security issues, energy consumption, and expected QoS is significant challenges in this area. Hence, we have proposed a Blockchain-enabled Intelligent framework to tackle the mentioned issues and allocate the optimal resources for upcoming IoT requests in a collaborative cloud fog environment. The proposed framework is integrated with an Artificial Intelligence (AI) based meta-heuristic algorithm that has a high convergence rate, and the capability to take the offloading decision at run time, leading to improved results quality. Blockchain technology secures IoT applications and their data from modern attacks. The experimental results of the proposed framework exhibit significant improvement by up to 20% in execution time and cost and up to 18% in energy consumption over other meta-heuristic approaches under similar experimental environments.
期刊介绍:
Grid Computing is an emerging technology that enables large-scale resource sharing and coordinated problem solving within distributed, often loosely coordinated groups-what are sometimes termed "virtual organizations. By providing scalable, secure, high-performance mechanisms for discovering and negotiating access to remote resources, Grid technologies promise to make it possible for scientific collaborations to share resources on an unprecedented scale, and for geographically distributed groups to work together in ways that were previously impossible. Similar technologies are being adopted within industry, where they serve as important building blocks for emerging service provider infrastructures.
Even though the advantages of this technology for classes of applications have been acknowledged, research in a variety of disciplines, including not only multiple domains of computer science (networking, middleware, programming, algorithms) but also application disciplines themselves, as well as such areas as sociology and economics, is needed to broaden the applicability and scope of the current body of knowledge.