Maria Carla Calzarossa

Workload characterization: a survey

The performance of a system is determined by its characteristics as well as by the composition of the load being processed. Hence, its quantitative description is a fundamental part of all performance evaluation studies. Several methodologies for the construction of workload models, which are functions of the objective of the study, of the architecture of the system to be analyzed, and of the techniques adopted, are presented. A survey of a few applications of these methodologies to various types of systems (i.e., batch, interactive, database, network-based, parallel, supercomputer), is given. >

Performance Tools and Applications to Networked Systems

Content Delivery Networks (CDN) aim at overcoming the inherent limitations of the Internet. The main concept at the basis of this technology is the delivery at edge points of the network, in proximity to the request areas, to improve the user’s perceived performance while limiting the costs. This paper focuses on the main research areas in the field of CDN, pointing out the motivations, and analyzing the existing strategies for replica placement and management, server measurement, best fit replica selection and request redirection.

Workload Characterization Issues and Methodologies

The performance of any type of system cannot be determined without knowing the workload, that is, the requests being processed. Workload characterization consists of a description of the workload by means of quantitative parameters and functions; the objective is to derive a model able to show, capture, and reproduce the behavior of the workload and its most important features.

A hierarchical approach to workload characterization for parallel systems

Performance evaluation studies are to be an integral part of the design and tuning of parallel applications. We propose a hierarchical approach to the systematic characterization of the workload of a parallel system, to be kept as modular and flexible as possible. The methodology is based on three different, but related, layers: the application, the algorithm, and the routine layer. For each of these layers different characteristics representing functional, sequential, parallel, and quantitative descriptions have been identified. These characteristics are specified in a system independent way to clearly separate between the workload description and the architecture description. Taking also architectural and mapping features into consideration, the hierarchical workload characterization can be applied to any type of performance studies.

Medea: a tool for workload characterization of parallel systems

The Medea (MEasurements Description, Evaluation and Analysis) software tool provides a user-friendly environment for systematically applying workload characterization techniques to raw data produced by monitoring parallel programs. Medeas models are especially useful for program tuning and performance debugging, for testing alternative system configurations and for supporting benchmarking studies. >

Models of mail server workloads

Abstract Electronic mail has become an integral part of our daily lives. With this trend, mail servers have to provide a fast, highly available, reliable and secure service. Hence, workload characterization and performance evaluation of mail servers are to be addressed as primary issues. This paper deals with a detailed characterization of mail server workloads. Our study is based on the analysis of a large set of measurements collected on various mail servers. We analyze SMTP and POP3 requests and we obtain models able to capture and reproduce their behavior and most relevant characteristics. These models represent the basis for the definition of the workload of SPECmail2001, a benchmark currently under development within SPEC to assess the ability of a system to act as a mail server.

Construction and use of multiclass workload models

Abstract 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.

System performance with user behavior graphs

Abstract Workload characterization is known to be a difficult and yet a very important facet of performance modeling. User behavior graphs have been advocated as a practical means of workload characterization. Performance modeling with user behavior graphs is for the most part carried out using costly simulations. We present inexpensive and yet accurate analytic performance models based on user behavior graphs.

Workload Characterization: A Survey Revisited

Workload characterization is a well-established discipline that plays a key role in many performance engineering studies. The large-scale social behavior inherent in the applications and services being deployed nowadays leads to rapid changes in workload intensity and characteristics and opens new challenging management and performance issues. A deep understanding of user behavior and workload properties and patterns is therefore compelling. This article presents a comprehensive survey of the state of the art of workload characterization by addressing its exploitation in some popular application domains. In particular, we focus on conventional web workloads as well as on the workloads associated with online social networks, video services, mobile apps, and cloud computing infrastructures. We discuss the peculiarities of these workloads and present the methodological approaches and modeling techniques applied for their characterization. The role of workload models in various scenarios (e.g., performance evaluation, capacity planning, content distribution, resource provisioning) is also analyzed.

A methodology towards automatic performance analysis of parallel applications

Tuning and debugging the performance of parallel applications is an iterative process consisting of several steps dealing with identification and localization of inefficiencies, repair, and verification of the achieved performance. In this paper, we address the analysis of the performance of parallel applications from a methodological viewpoint with the aim of identifying and localizing inefficiencies. Our methodology is based on performance metrics and criteria that highlight the properties of the applications and the load imbalance and dissimilarities in the behavior of the processors. A few case studies illustrate the application of the methodology.