The Fog computing paradigm is becoming prominent in supporting time-sensitive applications that are related to the smart Internet of Things (IoT) services, such as smart city and smart healthcare. Although Cloud computing is a promising paradigm for IoT in data processing, due to the high latency limitation of the Cloud, it is unable to satisfy the requirements for time-sensitive applications. Resource allocation and provisioning in the Fog-Cloud environment, considering dynamic changes in user requirements and limited available resources in Fog devices, is a challenging task. Among dynamic changes in the parameters of user requirements, the deadline is the most important challenge in the Fog computing environment. Current works on Fog computing address the resource provisioning without considering the dynamic changes in users' requirements. To address the problem of satisfying deadline-based dynamic user requirements, we propose resource allocation and provisioning algorithms by using resource ranking and provision of resources in a hybrid and hierarchical fashion. The proposed algorithms are evaluated in a simulation environment by extending the CloudSim toolkit to simulate a realistic Fog environment. The experimental results indicate that the performance of the proposed algorithms is better compared with existing algorithms in terms of overall data processing time, instance cost and network delay, with the increasing number of application submissions. The average processing time and cost are decreased by 12% and 15% respectively, compared with existing solutions.

Item Type:	Refereed Article
Keywords:	fog computing, resource allocation, resource provisioning, users dynamic behaviour, fog device, IoT, resource ranking, IoT, big data
Research Division:	Information and Computing Sciences
Research Group:	Distributed computing and systems software
Research Field:	Cloud computing
Objective Division:	Information and Communication Services
Objective Group:	Information systems, technologies and services
Objective Field:	Computer systems
UTAS Author:	Naha, RK (Mr Ranesh Kumar Naha)
UTAS Author:	Garg, S (Dr Saurabh Garg)
UTAS Author:	Chan, A (Professor Andrew Chan)
UTAS Author:	Battula, SK (Mr Sudheer Kumar Battula)
ID Code:	142784
Year Published:	2020
Web of Science® Times Cited:	81
Deposited By:	Information and Communication Technology
Deposited On:	2021-02-11
Last Modified:	2021-06-30
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