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On Uncoordinated Service Placement in Edge Clouds

Ascigil, A; Phan, TK; Sourlas, V; Psaras, I; Pavlou, G; (2017) On Uncoordinated Service Placement in Edge Clouds. In: Proceedings of the 2017 IEEE International Conference on Cloud Computing Technology and Science (CloudCom). IEEE: Hong Kong, China. Green open access

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Abstract

Edge computing has emerged as a new paradigm to bring cloud applications closer to users for increased performance. ISPs have the opportunity to deploy private edge-clouds in their infrastructure to generate additional revenue by providing ultra-low latency applications to local users. We envision a rapid increase in the number of such applications for “edge” networks in the near future with virtual/augmented reality (VR/AR), networked gaming, wearable cognitive assistance, autonomous driving and IoT analytics having already been proposed for edge- clouds instead of the central clouds to improve performance. This raises new challenges as the complexity of the resource allocation problem for multiple services with latency deadlines (i.e., which service to place at which node of the edge-cloud in order to satisfy the latency constraints) becomes significant. In this paper, we propose a set of practical, uncoordinated strategies for service placement in edge-clouds. Through extensive simulations using both synthetic and real-world trace data, we demonstrate that uncoordinated strategies can perform comparatively well with the optimal placement solution, which satisfies the maximum amount of user requests.

Type: Proceedings paper
Title: On Uncoordinated Service Placement in Edge Clouds
Event: IEEE International Conference on Cloud Computing Technology and Science
Location: Hong Kong
Dates: 11 December 2017 - 14 December 2017
ISBN-13: 978-1-5386-0692-6
Open access status: An open access version is available from UCL Discovery
DOI: 10.1109/CloudCom.2017.46
Publisher version: http://dx.doi.org/10.1109/CloudCom.2017.46
Language: English
Additional information: This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions.
Keywords: Cloud computing, Resource management, Delays, Quality of service, Processor scheduling, Peer-to-peer computing
UCL classification: UCL
UCL > Provost and Vice Provost Offices
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Electronic and Electrical Eng
URI: https://discovery.ucl.ac.uk/id/eprint/10027134
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