Network Performance Modeling and SimulationThis book makes the argument that performance modeling and simulation have become central issues in computer science and engineering, in part due to applications to the structures comprising the Internet. Dealing primarily with theory, tools and techniques as related to communications systems, the volume provides tutorials and surveys and relates new important research results. Each chapter presents background information, describes and analyzes important work done in the field and provides direction to the reader on future work and further readings. The topics covered include traffic models for A TM networks, simulation environments, analytical methods, interprocessor communications, and an evaluation of process architectures. |
No grāmatas satura
1.5. rezultāts no 32.
ix. lappuse
These reduction methods , we are told , result in a lumped Markov chain by eliminating immediate transitions in GSPNs and also by simplifying the color structure in SWNs . In chapter 4 Carey Williamson describes traffic models for MPEG ...
These reduction methods , we are told , result in a lumped Markov chain by eliminating immediate transitions in GSPNs and also by simplifying the color structure in SWNs . In chapter 4 Carey Williamson describes traffic models for MPEG ...
14. lappuse
In PCS , data flits do not immediately follow the header into the network . The header travels alone to find the path to its destination . When the header finally reaches the destination , an acknowledge flit returns to the source .
In PCS , data flits do not immediately follow the header into the network . The header travels alone to find the path to its destination . When the header finally reaches the destination , an acknowledge flit returns to the source .
19. lappuse
... E R ( di , n ) for some destination neN } E = We call the above definition of channel dependency direct dependency because we can use c ; immediately after Ci to transmit data by the path ( Ci , Cj , ... ) to the destination n .
... E R ( di , n ) for some destination neN } E = We call the above definition of channel dependency direct dependency because we can use c ; immediately after Ci to transmit data by the path ( Ci , Cj , ... ) to the destination n .
60. lappuse
Esat sasniedzis šīs grāmatas aplūkošanas reižu limitu.
Esat sasniedzis šīs grāmatas aplūkošanas reižu limitu.
61. lappuse
Esat sasniedzis šīs grāmatas aplūkošanas reižu limitu.
Esat sasniedzis šīs grāmatas aplūkošanas reižu limitu.
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Saturs
| 1 | |
2 Reusability Techniques for Building a Simulation Environment and Modeling Communications Systems | 39 |
An Overview and an Example of Application | 59 |
4 Traffic Modeling for ATM Networks | 105 |
5 An Overview of Source Characterization in ATM Networks | 123 |
6 Procedures for Estimating and Guaranteeing Delays in High Speed Communication Networks | 151 |
7 BMAP Modeling of a Correlated Queue | 177 |
8 Hierarchical Performance Modeling of Computer Communication Systems | 197 |
9 A Framework for Measuring the Performance of Alternative Process Architectures for Parallelizing Communication Systems | 219 |
A Prototyping and Modeling Tool for Communication Networks and Protocols | 255 |
11 Network Reliability Evaluation | 275 |
Notes on the Contributors | 303 |
Author Index | 311 |
Subject Index | 313 |
Citi izdevumi - Skatīt visu
Network Performance Modeling and Simulation Jean Walrand,Kallol Bagchi,George Zobrist Ierobežota priekšskatīšana - 1998 |
Network Performance Modeling and Simulation Jean Walrand,Kallol Bagchi,George Zobrist Ierobežota priekšskatīšana - 2019 |
Bieži izmantoti vārdi un frāzes
adaptive aggregate algorithm analysis application approach approximation arrival associated batch behavior bound buffer called cell channel chapter color communication complete components Computer Condition connection consider context corresponding customers defined delay dependency described direct distribution equal evaluation example execution extended Figure flow frame function given graph GSPN IEEE immediate implemented increases input instance interarrival interface interval Italy layer length mean measured messages method Module nodes objects observed obtained operation output packet Parallelism parameters path performance period possible present probability process architectures protocol stack queue reduction reliability represents respect routing rule selection server shown shows simulation single solution specific station step Stream structure submodel SunOS switch synchronization tasks techniques tokens traffic transitions University virtual waiting
Bibliogrāfiskā informācija
| Nosaukums | Network Performance Modeling and Simulation |
| Redaktori | Jean Walrand, Kallol Bagchi, George Zobrist |
| Izdevējs | CRC Press, 2019 |
| ISBN | 100071750X, 9781000717501 |
| Apjoms | 332 lappuses |
| Eksportēt avotu | BiBTeX EndNote RefMan |