• DocumentCode
    7023
  • Title

    Enabling persistent queries for cross-aggregate performance monitoring

  • Author

    Mandal, Avirup ; Baldin, Ivan ; Yufeng Xin ; Ruth, Paul ; Heerman, Chris

  • Author_Institution
    Rice Univ., Houston, TX, USA
  • Volume
    52
  • Issue
    5
  • fYear
    2014
  • fDate
    May-14
  • Firstpage
    157
  • Lastpage
    164
  • Abstract
    It is essential for distributed, data-intensive applications to monitor the performance of the underlying network, storage, and computational resources. Increasingly, distributed applications need performance information from multiple aggregates, and tools need to make real-time steering decisions based on the performance feedback. With increasing scale and complexity, the volume and velocity of monitoring data is increasing, posing scalability challenges. In this work, we have developed a persistent query agent (PQA) that provides real-time application and network performance feedback to clients/ applications, thereby enabling dynamic adaptations. The PQA enables federated performance monitoring by interacting with multiple aggregates and performance monitoring sources. Using a publish-subscribe framework, it sends triggers asynchronously to applications/clients when relevant performance events occur. The applications/clients register their events of interest using declarative queries and get notified by the PQA. The PQA leverages a complex event processing (CEP) framework for managing and executing the queries expressed in a standard SQL-like query language. Instead of saving all monitoring data for future analysis, PQA observes performance event streams in real time, and runs continuous queries over streams of monitoring events. In this work, we present the design and architecture of the PQA, and describe some relevant use cases.
  • Keywords
    computer network management; computer network performance evaluation; query languages; software agents; PQA; SQL-like query language; complex event processing; computational resource monitoring; cross aggregate performance monitoring; data intensive applications; distributed applications; network performance feedback; network resource monitoring; performance monitoring source; persistent query agent; real time application; storage resource monitoring; Distributed processing; Information retrieval; Internet; Java; Performance evaluation; Query processing; Real-time systems; Search methods;
  • fLanguage
    English
  • Journal_Title
    Communications Magazine, IEEE
  • Publisher
    ieee
  • ISSN
    0163-6804
  • Type

    jour

  • DOI
    10.1109/MCOM.2014.6815907
  • Filename
    6815907