• Title of article

    Seeing through black boxes: Tracking transactions through queues under monitoring resource constraints

  • Author/Authors

    Anandkumar، نويسنده , , Animashree and He، نويسنده , , Ting and Bisdikian، نويسنده , , Chatschik and Agrawal، نويسنده , , Dakshi، نويسنده ,

  • Issue Information
    روزنامه با شماره پیاپی سال 2013
  • Pages
    21
  • From page
    1090
  • To page
    1110
  • Abstract
    The problem of optimal allocation of monitoring resources for tracking transactions progressing through a distributed system, modeled as a queueing network, is considered. Two forms of monitoring information are considered, viz., locally unique transaction identifiers, and arrival and departure timestamps of transactions at each processing queue. The timestamps are assumed to be available at all the queues but in the absence of identifiers, only enable imprecise tracking since parallel processing can result in out-of-order departures. On the other hand, identifiers enable precise tracking but are not available without proper instrumentation. Given an instrumentation budget, only a subset of queues can be selected for the production of identifiers, while the remaining queues have to resort to imprecise tracking using timestamps. The goal is then to optimally allocate the instrumentation budget to maximize the overall tracking accuracy. The challenge is that the optimal allocation strategy depends on accuracies of timestamp-based tracking at different queues, which has complex dependencies on the arrival and service processes, and the queueing discipline. We propose two simple heuristics for allocation by predicting the order of timestamp-based tracking accuracies of different queues. We derive sufficient conditions for these heuristics to achieve optimality through the notion of the stochastic comparison of queues. Simulations show that our heuristics are close to optimality, even when the parameters deviate from these conditions.
  • Keywords
    Probabilistic transaction monitoring , queueing networks , Bipartite matching , Stochastic comparison
  • Journal title
    Performance Evaluation
  • Serial Year
    2013
  • Journal title
    Performance Evaluation
  • Record number

    1733398