This article defines computer capacity planning and proposes a four-phased model for computer capacity planning (CCP). The model contains the major steps needed for developing a comprehensive computer capacity plan. The requirements for capacity .
Automated composition of Web Services can be achieved by using AI planning techniques. Hierarchical Task Network (HTN) planning is especially well-suited for this task. In this paper, we describe how HTN planning system SHOP2 can be used with OWL-S Web .
Reviewer: Wei-Ming Hu
The authors apply performance and capacity planning techniques to Web serving. Their overall approach is to first cover general performance and capacity issues, and then show how these principles apply to Web serving. The book starts with an overview of performance issues in traditional client/server applications and the approach taken there. A detailed discussion of capacity planning in client/server systems covers workloads and models. This is then followed by a chapter on characterizing the workload; the authors give good examples of how they model and characterize Web requests. In the following chapter, on benchmarks, the authors cover both system-level benchmarks (such as TPC-C) and benchmarks designed to model Web server performance (WebStone and SPECweb). The last part of the book discusses performance modeling. It describes how to model a system using queueing theory and then applies this approach to Web performance. An accompanying CD-ROM contains the formulas and algorithms described in the book, a workload sample, and a data reduction utility. The greatest strength of the book is the way in which it places Web server performance analysis within the context of the general system performance problem. The authors show how to approach performance problems in general and how to adapt this approach to Web server performance problems. Their analytical approach allows the reader to gain more insight into what the key Web server performance and workload issues are.
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