Accelerating batch analytics with residual resources from interactive clouds

R. Benjamin Clay, Zhiming Shen, Xiaosong Ma

Research output: Chapter in Book/Report/Conference proceedingConference contribution

10 Citations (Scopus)

Abstract

The popularity of cloud-based interactive computing services (e.g., virtual desktops) brings new management challenges. Each interactive user leaves abundant but fluctuating residual resources while being intolerant to latency, precluding the use of aggressive VM consolidation. In this paper, we present the Resource Harvester for Interactive Clouds (RHIC), an autonomous management framework that harnesses dynamic residual resources aggressively without slowing the harvested interactive services. RHIC builds ad-hoc clusters for running throughput-oriented 'background' workloads using a hybrid of residual and dedicated resources. These hybrid clusters offer significant gains over normal dedicated clusters: 20-40% cost and 20-29% energy savings in our test bed. For a given background job, RHIC intelligently discovers and maintains the ideal cluster size and composition, to meet user-specified goals such as cost/energy minimization or deadlines. RHIC employs black-box workload performance modeling, requiring only system-level metrics and incorporating techniques to improve modeling accuracy with bursty and heterogeneous residual resources. We demonstrate the effectiveness and adaptivity of our RHIC prototype with two parallel data analytics frameworks, Hadoop and HBase. Our results show that RHIC finds near-ideal cluster sizes and compositions across a wide range of workload/goal combinations.

Original languageEnglish
Title of host publicationProceedings - IEEE Computer Society's Annual International Symposium on Modeling, Analysis, and Simulation of Computer and Telecommunications Systems, MASCOTS
Pages414-423
Number of pages10
DOIs
Publication statusPublished - 1 Dec 2013
Externally publishedYes
Event2013 IEEE 21st International Symposium on Modeling, Analysis and Simulation of Computer and Telecommunication, MASCOTS 2013 - San Francisco, CA, United States
Duration: 14 Aug 201316 Aug 2013

Other

Other2013 IEEE 21st International Symposium on Modeling, Analysis and Simulation of Computer and Telecommunication, MASCOTS 2013
CountryUnited States
CitySan Francisco, CA
Period14/8/1316/8/13

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Keywords

  • Adaptive systems
  • Distributed computing
  • Performance analysis

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Computer Networks and Communications
  • Software
  • Modelling and Simulation

Cite this

Clay, R. B., Shen, Z., & Ma, X. (2013). Accelerating batch analytics with residual resources from interactive clouds. In Proceedings - IEEE Computer Society's Annual International Symposium on Modeling, Analysis, and Simulation of Computer and Telecommunications Systems, MASCOTS (pp. 414-423). [6730798] https://doi.org/10.1109/MASCOTS.2013.63