Adaptive Speculation for Efficient Internetware Application Execution in Clouds

Ouyang, Xue and Garraghan, Peter and Primas, Bernhard and McKee, David and Townend, Paul and Xu, Jie (2018) Adaptive Speculation for Efficient Internetware Application Execution in Clouds. ACM Transactions on Internet Technology, 18 (2). ISSN 1533-5399

[img]
Preview
PDF (Adaptive Speculation for Efficient Internetware Application Execution in Clouds)
Adaptive_Speculation_for_Efficient_Internetware_Application_Execution_in_Clouds.pdf - Accepted Version
Available under License Creative Commons Attribution-NonCommercial.

Download (1MB)

Abstract

Modern Cloud computing systems are massive in scale, featuring environments that can execute highly dynamic Internetware applications with huge numbers of interacting tasks. This has led to a substantial challenge−the straggler problem, whereby a small subset of slow tasks significantly impede parallel job completion. This problem results in longer service responses, degraded system performance, and late timing failures that can easily threaten Quality of Service (QoS) compliance. Speculative execution (or speculation) is the prominent method deployed in Clouds to tolerate stragglersbycreatingtaskreplicasatruntime.Themethoddetectsstragglersbyspecifyingapredefinedthresholdtocalculate the difference between individual tasks and the average task progression within a job. However, such a static threshold debilitates speculation effectiveness as it fails to capture the intrinsic diversity of timing constraints in Internetware applications, as well as dynamic environmental factors such as resource utilization. By considering such characteristics, different levels of strictness for replica creation can be imposed to adaptively achieve specified levels of QoS for different applications. In this paper we present an algorithm to improve the execution efficiency of Internetware applications by dynamically calculating the straggler threshold, considering key parameters including job QoS timing constraints, task execution progress, and optimal system resource utilization. We implement this dynamic straggler threshold into the YARN architecture to evaluate it’s effectiveness against existing state-of-the-art solutions. Results demonstrate that the proposed approach is capable of reducing parallel job response times by up to 20% compared to the static threshold, as well as a higher speculation success rate, achieving up to 66.67% against 16.67% in comparison to the static method.

Item Type:
Journal Article
Journal or Publication Title:
ACM Transactions on Internet Technology
Additional Information:
©ACM, 2018. This is the author's version of the work. It is posted here for your personal use. Not for redistribution. The definitive Version of Record was published in ACM Transactions on Internet Technology (TOIT) http://dx.doi.org/10.1145/3093896
Uncontrolled Keywords:
/dk/atira/pure/subjectarea/asjc/1700/1705
Subjects:
ID Code:
86303
Deposited By:
Deposited On:
13 May 2017 02:36
Refereed?:
Yes
Published?:
Published
Last Modified:
01 Dec 2020 04:39