Assessing the robustness of self-managing computer systems under highly variable workloads

Abstract

Computer systems are becoming extremely complex due to the large number and heterogeneity of their hardware and software components, the multilayered 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. An 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 interarrival 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.