loading...
 This Article 
   
 Share 
   
 Bibliographic References 
   
 Add to: 
 
Digg
Furl
Spurl
Blink
Simpy
Google
Del.icio.us
Y!MyWeb
 
 Search 
   
First International Conference on Autonomic Computing (ICAC'04)
Assessing the Robustness of Self-Managing Computer Systems under Highly Variable Workloads
New York, New York
May 17-May 18
ISBN: 0-7695-2114-2
Mohamed N. Bennani, George Mason University
Daniel A. Menascé, George Mason University
Computer systems are becoming extremely complex due to the large number and heterogeneity of their hardware and software components, the multi-layered architecture used in their design, and the unpredictable nature of their workloads. Thus, performance management becomes difficult and expensive when carried out by human beings. A new approach, called self-managing computer systems, is to build into the systems the mechanisms required to self-adjust configuration parameters so that the Quality of Service requirements of the system are constantly met. In this paper, we evaluate the robustness of such methods when the workload exhibits high variability in terms of the inter-arrival time and service times of requests. Another contribution of this paper is the assessment of the use of workload forecasting techniques in the design of QoS controllers.
Citation:
Mohamed N. Bennani, Daniel A. Menascé, "Assessing the Robustness of Self-Managing Computer Systems under Highly Variable Workloads," icac, pp.62-69, First International Conference on Autonomic Computing (ICAC'04), 2004
Usage of this product signifies your acceptance of the Terms of Use.