AuthorsT. Dreibholz, S. Mazumdar, F. Zahid, A. Taherkordi, and E. G. Gran
TitleMobile Edge as Part of the Multi-Cloud Ecosystem: A Performance Study
AfilliationCommunication Systems
Project(s)MELODIC: Multi-cloud Execution-ware for Large-scale Optimised Data-Intensive Computing, NorNet, The Center for Resilient Networks and Applications, Simula Metropolitan Center for Digital Engineering
Publication TypeProceedings, refereed
Year of Publication2019
Conference NameProceedings of the 27th Euromicro International Conference on Parallel, Distributed and Network-Based ProcessingĀ (PDP)
Date Published02/2019
PublisherIEEE Computer Society
Place PublishedPavia, Lombardia/Italy
ISBN Number978-1-7281-1644-0
KeywordsCloud computing, latency, Mobile edge computing, Multi-Cloud, Performance

Cloud computing has revolutionized the way of application usage and deployment: applications run cost-effectively in remote data centers. With the increasing need for mobility and micro-services, particularly with the upcoming 5G mobile broadband networks, there is also a strong demand for mobile edge computing (MEC): applications run in small cloud systems in close proximity to the user, in order to minimize latencies. Both cloud and MEC have their advantages and disadvantages. Combining the two approaches in a unified multi-cloud, consisting of both traditional cloud services provisioned over heterogeneous cloud platforms and MEC systems, has the potential of obtaining the best out of both worlds. However, a comprehensive study is needed to evaluate the performance gains and the overheads involved for real-world cloud applications. In this paper, we introduce a baseline performance evaluation in order to identify the fallacies and pitfalls of combining multiple cloud systems and MEC into a unified MEC-multi-cloud platform. For this purpose, we analyze the basic, application-independent performance metrics of average round-trip time (RTT) and average application payload throughput in a setup consisting of two private and one public cloud systems. This baseline performance analysis confirms the feasibility of MEC-multi-cloud, and provides guidelines for designing an autonomic resource provisioning solutions, in terms of an extension proposed to our existing Melodic middleware platform for multi-cloud applications.

Citation Key PDP2019

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