Integration of admission, congestion, and peak power control in QoS-aware clusters

Ki Hwan Yum, Yuho Jin, Eun Jung Kim, Chita R. Das

Research output: Contribution to journalArticle

5 Scopus citations

Abstract

Admission, congestion, and peak power control mechanisms are essential parts of a cluster network design for supporting integrated traffic. While an admission control algorithm helps in delivering the assured performance, a congestion control algorithm regulates traffic injection to avoid network saturation. Peak power control forces to meet pre-specified power constraints while maintaining the service quality by regulating the injection of packets. In this paper, we propose these control algorithms for clusters, which are increasingly being used in a diverse set of applications that require QoS guarantees. The uniqueness of our approach is that we develop these algorithms for wormhole-switched networks, which have been used in designing clusters. We use QoS-capable wormhole routers and QoS-capable network interface cards (NICs), referred to as Host Channel Adapters (HCAs) in InfiniBand™ Architecture (IBA), to evaluate the effectiveness of these algorithms. The admission control is applied at the HCAs and the routers, while the congestion control and the peak power control are deployed only at the HCAs. A mixed workload consisting of best-effort, real-time, and control traffic is used to investigate the effectiveness of the proposed schemes. Simulation results with a single router (8-port) cluster and a 2-D mesh network cluster indicate that the admission, congestion, and peak power control algorithms are quite effective in delivering the assured performance. The proposed credit-based congestion control algorithm is simple and practical in that it relies on hardware already available in the HCA/NIC to regulate traffic injection.

Original languageEnglish (US)
Pages (from-to)1087-1099
Number of pages13
JournalJournal of Parallel and Distributed Computing
Volume70
Issue number11
DOIs
StatePublished - Nov 1 2010

All Science Journal Classification (ASJC) codes

  • Software
  • Theoretical Computer Science
  • Hardware and Architecture
  • Computer Networks and Communications
  • Artificial Intelligence

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