Dr Varghese Presents Work on Fog Computing at ACM/IEEE Symposium, Washington D.C.
Fog computing is expected to become the next major computing paradigm that will change the way we use the Internet behind the scenes.
Dr Blesson Varghese, Lecturer at Queen’s University Belfast, led a research study with Jonathan McChesney (IBM, previously QUB), Nan Wang (Durham University, previously QUB), Ashish Tanwer (Cisco Systems, USA) and Eyal de Lara (University of Toronto) exploring Fog Computing Benchmarks.
This study presents the design and development of the first open-source Fog computing benchmarks. Fog computing is a disruptive computing paradigm that not only uses Cloud data centres for processing user data, but also uses the edge of the wired network to make the Internet faster and secure. These benchmarks provide valuable information to system architects and engineers to understand the performance of a Fog system when software changes or operating system changes have been made.
Dr Varghese presented the paper entitled ‘DeFog: Fog Computing Benchmarks’ on 7 November 2019 at the ACM/IEEE Symposium on Edge Computing, Washington D.C.
Paper Abstract: Fog computing envisions that deploying services of an application across resources in the cloud and those located at the edge of the network may improve the overall performance of the application when compared to running the application on the cloud. However, there are currently no benchmarks that can directly compare the performance of the application across the cloud-only, edge only and cloud-edge deployment platform to obtain any insight on performance improvement.
This paper proposes DeFog, a first Fog benchmarking suite to: (i) alleviate the burden of Fog benchmarking by using a standard methodology, and (ii) facilitate the understanding of the target platform by collecting a catalogue of relevant metrics for a set of benchmarks. The current portfolio of DeFog benchmarks comprises six relevant applications conducive to using the edge. Experimental studies are carried out on multiple target platforms to demonstrate the use of DeFog for collecting metrics related to application latencies (communication and computation), for understanding the impact of stress and concurrent users on application latencies, and for understanding the performance of deploying different combination of services of an application across the cloud and edge
You can view a preprint version here: https://arxiv.org/pdf/1907.10890.pdf
Dr Blesson Varghese
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