Elastic CPU Cap Mechanism for Timely Dataflow Applications

HoseinyFarahabady, M, Farhangsadr, N, Zomaya, A, Tari, Z and Khan, S 2018, 'Elastic CPU Cap Mechanism for Timely Dataflow Applications', in Yong Shi, Haohuan Fu, Yingjie Tian, Valeria V. Krzhizhanovskaya, Michael Harold Lees, Jack Dongarra, Peter M. A. Sloot (ed.) Proceedings of the 18th International Conference Computational Science (ICCS 2018) Part I, Wuxi, China, 11-13 June 2018, pp. 554-568.


Document type: Conference Paper
Collection: Conference Papers

Title Elastic CPU Cap Mechanism for Timely Dataflow Applications
Author(s) HoseinyFarahabady, M
Farhangsadr, N
Zomaya, A
Tari, Z
Khan, S
Year 2018
Conference name ICCS 2018: Science at the Intersection of Data, Modelling and Computation - LNCS 10860
Conference location Wuxi, China
Conference dates 11-13 June 2018
Proceedings title Proceedings of the 18th International Conference Computational Science (ICCS 2018) Part I
Editor(s) Yong Shi, Haohuan Fu, Yingjie Tian, Valeria V. Krzhizhanovskaya, Michael Harold Lees, Jack Dongarra, Peter M. A. Sloot
Publisher Springer
Place of publication Cham, Switzerland
Start page 554
End page 568
Total pages 15
Abstract Sudden surges in the incoming workload can cause adverse consequences on the run-time performance of data-flow applications. Our work addresses the problem of limiting CPU associated with the elastic scaling of timely data-flow (TDF) applications running in a shared computing environment while each application can possess a different quality of service (QoS) requirement. The key argument here is that an unwise consolidation decision to dynamically scale up/out the computing resources for responding to unexpected workload changes can degrade the performance of some (if not all) collocated applications due to their fierce competition getting the shared resources (such as the last level cache). The proposed solution uses a queue-based model to predict the performance degradation of running data-flow applications together. The problem of CPU cap adjustment is addressed as an optimization problem, where the aim is to reduce the quality of service violation incidents among applications while raising the CPU utilization level of server nodes as well as preventing the formation of bottlenecks due to the fierce competition among collocated applications. The controller uses and efficient dynamic method to find a solution at each round of the controlling epoch. The performance evaluation is carried out by comparing the proposed controller against an enhanced QoS-aware version of round robin strategy which is deployed in many commercial packages. Experimental results confirmed that the proposed solution improves QoS satisfaction by near to 148% on average while it can reduce the latency of processing data records for applications in the highest QoS classes by near to 19% during workload surges.
Subjects Distributed and Grid Systems
Keyword(s) Shared resource interference
Distributed stream processing
Scheduling and resource allocation algorithms
DOI - identifier 10.1007/978-3-319-93698-7_42
Copyright notice © Springer International Publishing AG, part of Springer Nature 2018
ISBN 9783319936970
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