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Workload modeling for computer systems performance evaluation /

"Reliable performance evaluations require the use of representative workloads. This is no easy task since modern computer systems and their workloads are complex, with many interrelated attributes and complicated structures. Experts often use sophisticated mathematics to analyze and describe wo...

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Bibliographic Details
Main Author: Feitelson, Dror G
Format: Printed Book
Published: New York: Cambridge University Press, 2015.
Subjects:
Online Access:https://books.google.co.in/books?id=_vkGBwAAQBAJ&pg=PR4&dq=9781107078239&hl=en&sa=X&ved=0ahUKEwiKv4KjkIbgAhWWfisKHSpcCsoQ6AEIKDAA#v=onepage&q=9781107078239&f=false
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100 1 |a Feitelson, Dror G  |9 87787 
245 1 0 |a Workload modeling for computer systems performance evaluation /  |c Dror G. Feitelson 
260 |a New York:  |b Cambridge University Press,  |c 2015. 
300 |a xv, 551 p. 
504 |a Includes bibliographical references and index. 
505 8 |a Machine generated contents note: 1. Introduction; 2. Workload data; 3. Statistical distributions; 4. Fitting distributions to data; 5. Heavy tails; 6. Correlations in workloads; 7. Self-similarity and long-range dependence; 8. Hierarchical generative models; 9. Case studies; 10. Summary and outlook. 
520 |a "Reliable performance evaluations require the use of representative workloads. This is no easy task since modern computer systems and their workloads are complex, with many interrelated attributes and complicated structures. Experts often use sophisticated mathematics to analyze and describe workload models, making these models difficult for practitioners to grasp. This book aims to close this gap by emphasizing the intuition and the reasoning behind the definitions and derivations related to the workload models. It provides numerous examples from real production systems, with hundreds of graphs. Using this book, readers will be able to analyze collected workload data and clean it if necessary, derive statistical models that include skewed marginal distributions and correlations, and consider the need for generative models and feedback from the system. The descriptive statistics techniques covered are also useful for other domains"-- 
650 0 |a Electronic digital computers  |9 88086 
650 0 |a Electronic digital computers  |9 88086 
650 7 |a COMPUTERS / General.  |9 88087 
856 |u https://books.google.co.in/books?id=_vkGBwAAQBAJ&pg=PR4&dq=9781107078239&hl=en&sa=X&ved=0ahUKEwiKv4KjkIbgAhWWfisKHSpcCsoQ6AEIKDAA#v=onepage&q=9781107078239&f=false 
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952 |0 0  |1 0  |4 0  |6 004_000000000000000_Q52  |7 0  |9 156509  |a MGUL  |b MGUL  |c GEN  |d 2018-05-05  |e Calicut Book Distributors  |g 3411.85  |l 0  |o 004 Q52  |p 59352  |r 2018-05-05  |w 2018-05-05  |y BK