Thomas G. Robertazzi

This revised textbook, intended for use in undergraduate/graduate courses on computer networking, computer systems/architecture and performance evaluation, presents a host of new and revised content and ancillaries. This text presents a balanced approach between technology and mathematical modeling. It covers networking algorithms (routing, error codes, protocol verification, line codes, network coding and quantum encryption) and analysis (probability for networking with technological examples, queueing models, divisible load scheduling theory and Amdahl’s Law). There is also a tutorial chapter providing insights into machine learning for networking, the cutting edge of networking technology.This self-contained text progresses systematically and gives students numerous examples at the end of each chapter. Students in electrical engineering, computer engineering and computer science departments will benefit from this book as will engineers and computer scientists workingin relevant fields.Maintains a balanced approach between technology and mathematical modelingFeatures new and revised content covering the latest advances in the field since the original publicationIncludes a host of classroom material for students and instructors

This revised textbook, intended for use in undergraduate/graduate courses on computer networking, computer systems/architecture and performance evaluation, presents a host of new and revised content and ancillaries. This text presents a balanced approach between technology and mathematical modeling. It covers networking algorithms (routing, error codes, protocol verification, line codes, network coding and quantum encryption) and analysis (probability for networking with technological examples, queueing models, divisible load scheduling theory and Amdahl’s Law). There is also a tutorial chapter providing insights into machine learning for networking, the cutting edge of networking technology.This self-contained text progresses systematically and gives students numerous examples at the end of each chapter. Students in electrical engineering, computer engineering and computer science departments will benefit from this book as will engineers and computer scientists workingin relevant fields.Maintains a balanced approach between technology and mathematical modelingFeatures new and revised content covering the latest advances in the field since the original publicationIncludes a host of classroom material for students and instructors

This book gives a broad look at both fundamental networking technology and new areas that support it and use it. It is a concise introduction to the most prominent, recent technological topics in computer networking. Topics include network technology such as wired and wireless networks, enabling technologies such as data centers, software defined networking, cloud and grid computing and applications such as networks on chips, space networking and network security. The accessible writing style and non-mathematical treatment makes this a useful book for the student, network and communications engineer, computer scientist and IT professional.

This book gives a broad look at both fundamental networking technology and new areas that support it and use it. It is a concise introduction to the most prominent, recent technological topics in computer networking. Topics include network technology such as wired and wireless networks, enabling technologies such as data centers, software defined networking, cloud and grid computing and applications such as networks on chips, space networking and network security. The accessible writing style and non-mathematical treatment makes this a useful book for the student, network and communications engineer, computer scientist and IT professional.

Statistical performance evaluation has assumed an increasing amount of importance as we seek to design more and more sophisticated communication and information processing systems. The ability to predict a proposed system's per­ formance before one constructs it is an extremely cost effective design tool. This book is meant to be a first-year graduate level introduction to the field of statistical performance evaluation. It is intended for people who work with sta­ tistical performance evaluation including engineers, computer scientists and applied mathematicians. As such, it covers continuous time queueing theory (chapters 1-4), stochastic Petri networks (chapter 5), discrete time queueing theory (chapter 6) and recent network traffic modeling work (chapter 7). There is a short appendix at the end of the book that reviews basic probability theory. This material can be taught as a complete semester long course in performance evalua­ tion or queueing theory. Alternatively, one may teach only chapters 2 and 6 in the first half of an introductory computer networking course, as is done at Stony Brook. The second half of the course could use a more protocol oriented text such as ones by Saadawi [SAAD] or Stallings [STALl What is new in the third edition of this book? In addition to the well received material of the second edition, this edition has three major new features.

This useful volume adopts a balanced approach between technology and mathematical modeling in computer networks, covering such topics as switching elements and fabrics, Ethernet, and ALOHA design. The discussion includes a variety of queueing models, routing, protocol verification and error codes and divisible load theory, a new modeling technique with applications to grids and parallel and distributed processing. Examples at the end of each chapter provide ample material for practice. This book can serve as an text for an undergraduate or graduate course on computer networks or performance evaluation in electrical and computer engineering or computer science.

Statistical performance evaluation has assumed an increasing amount of importance as we seek to design more and more sophisticated communication and information processing systems. The ability to predict a proposed system's per­ formance before one constructs it is an extremely cost effective design tool. This book is meant to be a first-year graduate level introduction to the field of statistical performance evaluation. It is intended for people who work with sta­ tistical performance evaluation including engineers, computer scientists and applied mathematicians. As such, it covers continuous time queueing theory (chapters 1-4), stochastic Petri networks (chapter 5), discrete time queueing theory (chapter 6) and recent network traffic modeling work (chapter 7). There is a short appendix at the end of the book that reviews basic probability theory. This material can be taught as a complete semester long course in performance evalua­ tion or queueing theory. Alternatively, one may teach only chapters 2 and 6 in the first half of an introductory computer networking course, as is done at Stony Brook. The second half of the course could use a more protocol oriented text such as ones by Saadawi [SAAD] or Stallings [STALl What is new in the third edition of this book? In addition to the well received material of the second edition, this edition has three major new features.

Electrical Engineering Planning Telecommunication Networks The ever-growing number of new telecommunications technologies, along with the rapid growth of data networks and cable television systems has created a demand for sound network planning. In one concise volume, this book offers telecommunications professionals and graduate students an introduction to the theory underlying the interdisciplinary field of network planning, a critical aspect of network management that integrates planning telecommunications and data networks. In planning Telecommunication Networks you will learn about the mathematical theory behind network planning, including an accessible treatment of linear programming and graph algorithms. Other featured topics cover:*Reliability theory for network planning*Recent software advances in databases, expert systems, object-oriented programming, data mining, and data visualization*Latest developments in new optimization techniques such as tabu research, simulated annealing, genetic algorithms, and neural networksComplete with homework problems, this text offers you a broad overview of network planning to begin your exploration of this emerging field.

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