Advanced Search
CS Search Google Search
Subscribers, please login

Published Articles >> Table of Contents >> Abstract

Sixth IEEE International Symposium on Network Computing and Applications (NCA 2007)   pp. 25-32
Approximate Analytical Models for Networked Servers Subject to MMPP Arrival Processes

Full Article Text: Download PDF of full textBuy this articleGet full text from IEEE Xplore

DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/NCA.2007.7
Send link to a friend

Abstract
Input characterization to describe the flow of incoming traffic in network systems, such as the GRID and the WWW, is often performed by using Markov Modulated Poisson Processes (MMPP). Therefore, to enact capacity planning and Quality-of-Service (QoS) oriented design, the model of the hosts that receive the incoming traffic is often described as a MMPP/M/1 queue. The drawback of this model is that no closed form for its solution has been derived. This means that evaluating even the simplest output statistics of the model, such as the average response times of the queue, is a computationally intensive task and its usage in the above contexts is often unadvisable. In this paper we discuss the possibility to approximate the behavior of a MMPP/M/1 queue with a computational effective analytical approximation, thus saving the large amount of calculations required to evaluate the same data by other means. The employed method consists in approximating theMMPP/M/1 queue as a weighted superposition of different M/M/1 queues. The analysis is validated by comparing the results of a discrete event simulator with those obtained from the proposed approximations, in the context of a real case study involving a GRID networked server.
Additional Information

Citation:  1 Ciciani, 1 Santoro, 1 Romano, "Approximate Analytical Models for Networked Servers Subject to MMPP Arrival Processes," nca, pp. 25-32,  Sixth IEEE International Symposium on Network Computing and Applications (NCA 2007),  2007

Similar Articles

Abstract Contents
Abstract
Citation




Free access to

  • Abstracts
  • Selected PDFs

Electronic subscribers login to:

  • Access HTML/PDFs of full text articles

Subscription information

Get a Web account

PDFs require Adobe Acrobat Reader.

Peer Review Notice

Give us Feedback