Performance Modeling And Engineering
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Performance Modeling and Engineering
Author: Zhen Liu
language: en
Publisher: Springer Science & Business Media
Release Date: 2008-04-12
With the fast development of networking and software technologies, information processing infrastructure and applications have been growing at an impressive rate in both size and complexity, to such a degree that the design and development of high performance and scalable data processing systems and networks have become an ever-challenging issue. As a result, the use of performance modeling and m- surementtechniquesas a critical step in designand developmenthas becomea c- mon practice. Research and developmenton methodologyand tools of performance modeling and performance engineering have gained further importance in order to improve the performance and scalability of these systems. Since the seminal work of A. K. Erlang almost a century ago on the mod- ing of telephone traf c, performance modeling and measurement have grown into a discipline and have been evolving both in their methodologies and in the areas in which they are applied. It is noteworthy that various mathematical techniques were brought into this eld, including in particular probability theory, stochastic processes, statistics, complex analysis, stochastic calculus, stochastic comparison, optimization, control theory, machine learning and information theory. The app- cation areas extended from telephone networks to Internet and Web applications, from computer systems to computer software, from manufacturing systems to s- ply chain, from call centers to workforce management.
Performance Engineering
Author: Reiner Dumke
language: en
Publisher: Springer Science & Business Media
Release Date: 2001-05-23
Initially, computer systems performance analyses were carried out primarily because of limited resources. Due to ever increasing functional complexity of computational systems and user requirements, performance engineering continues to play a major role in software development. This book assesses the state of the art in performance engineering. Besides revised chapters drawn from two workshops on performance engineering held in 2000, additional chapters were solicited in order to provide complete coverage of all relevant aspects. The first part is devoted to the relation between software engineering and performance engineering; the second part focuses on the use of models, measures, and tools; finally, case studies with regard to concrete technologies are presented. Researchers, professional software engineers, and advanced students interested in performance analysis will find this book an indispensable source of information and reference.
Performance Modeling and Engineering
With the fast development of networking and software technologies, information processing infrastructure and applications have been growing at an impressive rate in both size and complexity, to such a degree that the design and development of high performance and scalable data processing systems and networks have become an ever-challenging issue. As a result, the use of performance modeling and m- surementtechniquesas a critical step in designand developmenthas becomea c- mon practice. Research and developmenton methodologyand tools of performance modeling and performance engineering have gained further importance in order to improve the performance and scalability of these systems. Since the seminal work of A. K. Erlang almost a century ago on the mod- ing of telephone traf c, performance modeling and measurement have grown into a discipline and have been evolving both in their methodologies and in the areas in which they are applied. It is noteworthy that various mathematical techniques were brought into this eld, including in particular probability theory, stochastic processes, statistics, complex analysis, stochastic calculus, stochastic comparison, optimization, control theory, machine learning and information theory. The app- cation areas extended from telephone networks to Internet and Web applications, from computer systems to computer software, from manufacturing systems to s- ply chain, from call centers to workforce management.