McKee, DW orcid.org/0000-0002-9047-7990, Clement, SJ orcid.org/0000-0003-2918-5881, Xu, J et al. (1 more author) (2017) n-Dimensional QoS Framework for Real-Time Service-Oriented Architectures. In: 2nd IEEE International Symposium on Real-time Data Processing for Cloud Computing. RTDPCC 2017: 2nd International Symposium on Real-time Data Processing for Cloud Computing, 21-23 Jun 2017, Exeter, UK. IEEE Computer Society Press
Abstract
Service-Orientation has long provided an effective mechanism to integrate heterogeneous systems in a loosely coupled fashion as services. However, with the emergence of Internet of Things (IoT) there is a growing need to facilitate the integration of real-time services executing in non-controlled, non-real-time, environments such as the Cloud. With the need to integrate both cyberphysical systems as hardware-in-the-loop (HIL) components and also with Simulation as a Service (SIMaaS) the execution performance and response-times of the services must be managed. This paper presents a mathematical framework that captures the relationship between the host execution environment and service performance allowing the estimation of Quality of Service (QoS) under dynamic Cloud workloads. A formal mathematical definition is provided and this is evaluated against existing techniques from both the Cloud and Real-Time Service Oriented Architecture (RT-SOA) domains. The proposed approach is evaluated against the existing techniques through simulation and demonstrates a reduction of QoS violation percentage by 22% with respect to response-times as well as reducing the number of Micro-Service (uS) instances with QoS violations by 27%.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © IEEE. This is an author produced version of a paper published in 2nd IEEE International Symposium on Real-time Data Processing for Cloud Computing. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works. Uploaded in accordance with the publisher’s self-archiving policy. |
Keywords: | Real-Time; QoS; Services; SOA; Micro-Services; Schedulability; Resource Modelling; IoT; IoS; SIMaaS; Cloud |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Computing (Leeds) |
Funding Information: | Funder Grant number EPSRC EP/K014226/1 |
Depositing User: | Symplectic Publications |
Date Deposited: | 18 Jul 2017 09:47 |
Last Modified: | 28 Feb 2024 14:46 |
Status: | Published |
Publisher: | IEEE Computer Society Press |
Identification Number: | 10.1109/ithings-greencom-cpscom-smartdata.2017.34 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:119121 |