Skip navigation
  • Home
  • Browse
    • Communities
      & Collections
    • Browse Items by:
    • Publication Date
    • Author
    • Title
    • Subject
    • Department
  • Sign on to:
    • My MacSphere
    • Receive email
      updates
    • Edit Profile


McMaster University Home Page
  1. MacSphere
  2. Open Access Dissertations and Theses Community
  3. Open Access Dissertations and Theses
Please use this identifier to cite or link to this item: http://hdl.handle.net/11375/18196
Title: Performance Models for Legacy System Migration and Multi-core Computers - an MVA Approach
Authors: Zhang, Lei
Advisor: Down, Douglas G.
Al-Azzoni, Issam
Department: Computing and Software
Publication Date: Nov-2015
Abstract: Computer system architecture and design have witnessed continual change, with resulting challenges for performance modeling. In this thesis, we explore performance evaluation and modeling using queueing networks and Mean Value Analysis (MVA) approaches. We first investigate scenarios where legacy systems are migrated to newer platforms. We apply a novel MVA-based method - PELE - to address performance evaluation for the migrations. We extend the applicability of PELE with several case studies. Through the experiments, we demonstrate that the MVA algorithm is an efficient technique for computer system performance modeling. However, we find that it fails to address some features of multi-core platforms. To solve those problems, we present another MVA-based method - APEM. In APEM, we propose an approximation to estimate service demands, and use a flow-equivalent aggregation technique to approximate non-product-form networks. To validate the application of our method, we investigate three case studies of a closed, an open and a semi-open system, respectively. We show that our method achieves better accuracy compared with other commonly used MVA algorithms. In addition, we propose an approximate MVA algorithm - SMVA - to address the numerical instability of MVA that we encountered in previous case studies. Future research may use SMVA as a starting point to continue improvement of numerically stable MVA algorithms.
URI: http://hdl.handle.net/11375/18196
Appears in Collections:Open Access Dissertations and Theses

Files in This Item:
File Description SizeFormat 
Zhang_Lei_finalsubmission201509_PhD.pdf
Open Access
1.06 MBAdobe PDFView/Open
Show full item record Statistics


Items in MacSphere are protected by copyright, with all rights reserved, unless otherwise indicated.

Sherman Centre for Digital Scholarship     McMaster University Libraries
©2022 McMaster University, 1280 Main Street West, Hamilton, Ontario L8S 4L8 | 905-525-9140 | Contact Us | Terms of Use & Privacy Policy | Feedback

Report Accessibility Issue