Modelling of Computer and Communication Systems: 24 (Cambridge Computer Science Texts, Series Number 24)

Mitrani, I.

ISBN 10: 0521314224 / ISBN 13: 9780521314220

Published by Cambridge University Press, 1987

About this Item

This 1987 book is a self-contained text on the probabilistic modelling method. Series: Cambridge Computer Science Texts. Num Pages: 202 pages, bibliography, index. BIC Classification: PBKS. Category: (U) Tertiary Education (US: College). Dimension: 229 x 152 x 12. Weight in Grams: 300. . 1987. 1st Edition. paperback. . . . . Books ship from the US and Ireland.

Seller Inventory # V9780521314220

Bibliographic Details

• Title: Modelling of Computer and Communication Systems: 24 (Cambridge Computer Science Texts, Series Number 24)
• Publisher: Cambridge University Press
• Publication Date: 1987
• Language: English
• ISBN 10: 0521314224
• ISBN 13: 9780521314220
• Binding: Soft cover
• Condition: New

About this title

Synopsis

This 1987 book is a self-contained text on the probabilistic modelling method. It provides the reader with an understanding of the available results as well as with examples of their application. The only background assumed is a knowledge of basic calculus. The necessary fundamentals of probability are presented followed by an introduction to stochastic processes. The remainder of the book is devoted to the treatment of various single-station and their application to uni-programmed and multi-programmed systems and local and wide-area networks. Both exact and approximate solution methods are discussed, with as much emphasis on explaining the ideas and providing information, as on derivations and proofs. This book will still be of use for anyone with an interest in the history of computer science.

Book Description

This 1987 book is a self-contained text on the probabilistic modelling method. It provides the reader with an understanding of the available results as well as with examples of their application. The necessary fundamentals of probability are presented followed by an introduction to stochastic processes.