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A generic stochastic model for resource availability in fog computing environments

Citation

Battula, SK and O'Reilly, MM and Garg, S and Montgomery, J, A generic stochastic model for resource availability in fog computing environments, IEEE Transactions on Parallel and Distributed Systems, 32, (4) pp. 960-974. ISSN 1045-9219 (2021) [Refereed Article]

Copyright Statement

Copyright 2020 IEEE

DOI: doi:10.1109/TPDS.2020.3037247

Abstract

Fog computing is an increasingly popular method with which to process the huge amount of data generated by the Internet of Things (IoT) devices and applications at the edge-level, using the heterogeneous autonomous end-devices of the participating users. To meet the requirements of the IoT and time-sensitive applications, a Fog computing platform needs to select appropriate resources, the availability of which can be guaranteed during the execution of the application. For the proper selection of resources, the platform must be able to predict future availability. Hence, a proper resource availability model which provides knowledge about the future availability of resources in the Fog computing environment is required. However, designing an efficient resource availability model, in a highly distributed and mobile environment like the Fog, is a complex task due to the multidimensional characteristics of Fog devices, such as mobility, lack of centralised control, limited resources, and being battery powered. Existing resource availability models did not consider all the characteristics of a real Fog environment. Therefore, this study aims to provide a generic continuous-time Markov chain (CTMC), based resource availability model for Fog computing environments. The applicability of the model is shown by integrating the model input with the nearest-location best fit (NLBF) and Best-Fit resource selection policies.

Item Details

Item Type:Refereed Article
Keywords:fog computing, resource availability, stochastic model, Markov chain, mobility and Internet of Things, edge computing, distributed system
Research Division:Information and Computing Sciences
Research Group:Distributed computing and systems software
Research Field:Distributed systems and algorithms
Objective Division:Information and Communication Services
Objective Group:Information systems, technologies and services
Objective Field:Computer systems
UTAS Author:Battula, SK (Mr Sudheer Kumar Battula)
UTAS Author:O'Reilly, MM (Associate Professor Malgorzata O'Reilly)
UTAS Author:Garg, S (Dr Saurabh Garg)
UTAS Author:Montgomery, J (Dr James Montgomery)
ID Code:142773
Year Published:2021
Web of Science® Times Cited:3
Deposited By:Information and Communication Technology
Deposited On:2021-02-11
Last Modified:2021-08-04
Downloads:0

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