Multi-class queuing networks models for energy optimization

The increase of energy consumption and the related costs in large data centers has stimulated new researches on techniques to optimize the power consumption of the servers. In this paper we focus on systems that should process a peak workload consisting of different classes of applications. The objective is to implement a policy of load control which allows an efficient use of the power deployed to the resources. The proposed strategy controls the workload mix in order to achieve the maximum utilization of all the resources allocated. As a consequence, the power provision will be fully utilized and the throughput maximized. Thus, the costs to execute a given workload will be minimized, together with its energy consumption, since the required processing time is decreased

Learning performance engineering through applications

In 1986 D. Ferrari, in a position paper published on IEEE Transactions on Software Engineering, emphasized that the field of Computer Systems Performance Evaluation (CSPE) since its birth had grown in isolation from the other areas of computer science. It was pointed out that the drawbacks of such insularity outweigh its advantages. Some urgent actions to improve the situation were listed. Among them, on the educational side, the integration of performance evaluation concepts in the computer systems basic courses and a more application-oriented approach of the teaching have been advocated. Another problem highlighted was the existence of a time lag between the available performance evaluation techniques and the type of problems created by the new system architectures. In 2003 Ferrari revisited and updated the concepts described in the first paper. Some limited positive results have been perceived. But, what has happened during the last 14 years, about these and other problems related to the education and practice of performance engineering? The old problems, at least partially, have been solved? What are the new problems that arose?

Construction and Use of Multiclass Workload Models

Although the performance of a system is determined by the characteristics of the load being processed, much more care is usually devoted to the construction of a detailed system model than to an accurate definition of the workload model. A precise description of actual workloads is obtained with multiclass workload models. Major difficulties on their implementation are related to the identification of the classes and to the reproduction of the dynamic behavior of the load. Small relative errors in estimating the average resource demands of a class lead to larger errors in the performance indices of that class. The proposed multi-step methodology allows the construction of multiclass workload models which preserve, when used as system model parameters, both the static and dynamic characteristics of the original load. 1 Introduction A critical problem in the performance evaluation of multiprogrammed systems is the development of accurate models of their workload. Actual workloads consis..

Bottlenecks Identification in Multiclass Queueing Networks Using Convex Polytopes

It is known that the resources that limit the overall performance of the system are the congested ones, referred to as bottlenecks. From the knowledge of the bottleneck stations with a limited computational effort it is possible to derive asymptotic values of several performance indices. While identifying the bottleneck stations under a singleclass workload is a well-established practice, no simple methodology for multiclass models exists. In this paper we present new algorithms for identifying the bottlenecks in multiclass queueing networks with constant-rate servers. We show how the application of assessed techniques, such as the ones related to the convex polytopes, can provide insights on the performance of a queueing network. The application of our techniques to the asymptotic analysis of closed product-form networks is also investigated