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http://dx.doi.org/10.3837/tiis.2017.05.001

Service Architecture Models For Fog Computing: A Remedy for Latency Issues in Data Access from Clouds  

Khalid, Adnan (Government College University)
Shahbaz, Muhammad (University of Engineering and Technology)
Publication Information
KSII Transactions on Internet and Information Systems (TIIS) / v.11, no.5, 2017 , pp. 2310-2345 More about this Journal
Abstract
With the emergence of the Internet of Things (IoT) the world is projecting towards a scenario where every object in the world (including humans) acts as a sender and receiver of data and if we were to see that concept mature we would soon be talking of billions more users of the cloud networks. The cloud technology is a very apt alternative to permanent storage when it comes to bulk storage and reporting. It has however shown weaknesses concerning real-time data accessibility and processing. The bandwidth availability of the cloud networks is limited and combined with the highly centralized storage structure and geographical vastness of the network in terms of distance from the end user the cloud just does not seem like a friendly environment for real-time IOT data. This paper aims at highlighting the importance of Flavio Bonomi's idea of Fog Computing which has been glamorized and marketed by Cisco but has not yet been given a proper service architecture that would explain how it would be used in terms of various service models i-e IaaS, PaaS and SaaS, of the Cloud. The main contribution of the paper would be models for IaaS, PaaS and SaaS for Fog environments. The paper would conclude by highlighting the importance of the presented models and giving a consolidated overview of how they would work. It would also calculate the respective latencies for fog and cloud to prove that our models would work. We have used CloudSim and iFogSim to show the effectiveness of the paradigm shift from traditional cloud architecture to our Fog architecture.
Keywords
Fog Computing; Service Architecture; Cloud Computing; Internet of Things; Distributed computing; Grid computing;
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