A new book, entitled Data Engineering: Mining, Information and Intelligence, has just been published by Springer as part of the International Series in Operations Research & Management Science. Dr. Doug L. Hoffman was lead author on the Performance Modeling of Enterprise Grid Systems chapter of the newly published text book. The work is aimed at academics, students and industrial researchers in computer science and information systems.

DATA ENGINEERING: Mining, Information, and Intelligence describes applied research aimed at the task of collecting data and distilling useful information from that data. Most of the work presented emanates from research completed through collaborations between Acxiom Corporation and its academic research partners under the aegis of the Acxiom Laboratory for Applied Research (Dr. Hoffman is an ALAR Research Committee Member and Associate ALAR Director). Chapters are roughly ordered to follow the logical sequence of the transformation of data from raw input data streams to refined information. Four discrete sections cover Data Integration and Information Quality; Grid Computing; Data Mining; and Visualization. Additionally, exercises are included at the end of each chapter.

The primary audience for this book is the broad base of anyone interested in data engineering, whether from academia, market research firms, or business-intelligence companies. The volume is ideally suited for researchers, practitioners, and postgraduate students alike. With its focus on problems arising from industry rather than a basic research perspective, combined with its intelligent organization, extensive references, and subject and author indices, it can serve the academic, research, and industrial audiences. Significant features include:

• First volume to organize data mining, management, and warehousing into the systematic structure of Data Engineering.
  
  
• Focuses on recent applied research results applicable to a broad industry-research-academic market.
  
  
• End-of-chapter exercises for classroom use.
  
  

Chapter 9, Performance Modeling of Enterprise Grid Systems, was written by Doctors Doug L. Hoffman, Amy Apon, Larry Dowdy, and Baochuan Lu, with Nathan Hamm, Linh Ngo and Hung Bui. The chapter abstract reads as follows:

Modeling has long been recognized as an invaluable tool for predicting the performance behavior of computer systems. Modeling software, both commercial and open source, is widely used as a guide for the development of new systems and the upgrading of exiting ones. Unfortunately, no set of comprehensive tools exists for modeling complex distributed computing environments such as the ones found in emerging grid deployments. This chapter addresses concepts, methodologies, and tools that are useful when designing, implementing, and tuning the performance in grid and cluster environments.

The chapter's table of contents are shown below:

9 Performance Modeling of Enterprise Grids ........................... 169
   9.1 Introduction and Background ................................... 169
      9.1.1 Performance Modeling...................................... 169
      9.1.2 Capacity Planning Tools and Methodology .................. 171
   9.2 Measurement Collection and Preliminary Analysis................ 173
   9.3 Workload Characterization ..................................... 174
      9.3.1 K-means Clustering........................................ 176
      9.3.2 Hierarchical Workload Characterization.................... 181
      9.3.3 Other Issues in Workload Characterization................. 182
   9.4 Baseline System Models and Tool Construction .................. 184
      9.4.1 Analytic Models .......................................... 184
      9.4.2 Simulation Tools for Enterprise Grid Systems.............. 191
   9.5 Enterprise Grid Capacity Planning Case Study .................. 192
      9.5.1 Data Collection and Preliminary Analysis ................. 194
      9.5.2 Workload Characterization................................. 194
      9.5.3 Development and Validation of the Baseline Model.......... 195
      9.5.4 Model Predictions ........................................ 196
   9.6 Summary........................................................ 199
   9.7 Exercises...................................................... 199
   9.8 References .................................................... 200

The book was edited by Yupo Chan, University of Arkansas at Little Rock; John Talburt, University of Arkansas at Little Rock; and Terry M. Talley, Acxiom Corporation, Conway, AR, USA. More information is available from the Springer web site, http://www.springer.com. 447 p. 147 illus., Hardcover, ISBN: 978-1-4419-0175-0. Online version available.