Performance analysis of the reactor pattern in network services

  • Authors:

  • Swapna Gokhale;Aniruddha Gokhale;Jeff Gray;Paul Vandal;Upsorn Praphamontripong

  • Affiliations:

  • University of Connecticut, Dept. of Computer Science and Engineering, Storrs, CT;Vanderbilt University, Dept. of Electrical Engineering and Computer Science, Nashville, TN;University of Alabama at Birmingham, Dept of Computer and Information Science, Birmingham, AL;University of Connecticut, Dept. of Computer Science and Engineering, Storrs, CT;University of Connecticut, Dept. of Computer Science and Engineering, Storrs, CT

  • Venue:
  • IPDPS'06 Proceedings of the 20th international conference on Parallel and distributed processing
  • Year:
  • 2006

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Abstract

The growing reliance on services provided by software applications places a high premium on the reliable and efficient operation of these applications. A number of these applications follow the event-driven software architecture style since this style fosters evolvability by separating event handling from event demultiplexing and dispatching functionality. The event demultiplexing capability, which appears repeatedly across a class of event-driven applications, can be codified into a reusable pattern, such as the Reactor pattern. In order to enable performance analysis of event-driven applications at design time, a model is needed that represents the event demultiplexing and handling functionality that lies at the heart of these applications. In this paper, we present a model of the Reactor pattern based on the well-established Stochastic Reward Net (SRN) modeling paradigm. We discuss how the model can be used to obtain several performance measures such as the throughput, loss probability and upper and lower bounds on the response time. We illustrate how the model can be used to obtain the performance metrics of a Virtual Private Network (VPN) service provided by a Virtual Router (VR). We validate the estimates of the performance measures obtained from the SRN model using simulation.