Distributed Systems: Principles and ParadigmsPearson Prentice Hall, 2007 - 686 Seiten Virtually every computing system today is part of a distributed system. Programmers, developers, and engineers need to understand the underlying principles and paradigms as well as the real-world application of those principles. Now, internationally renowned expert Andrew S. Tanenbaum with colleague Martin van Steen presents a complete introduction that identifies the seven key principles of distributed systems, with extensive examples of each. Adds a completely new chapter on architecture to address the principle of organizing distributed systems. Provides extensive new material on peer-to-peer systems, grid computing and Web services, virtualization, and application-level multicasting. Updates material on clock synchronization, data-centric consistency, object-based distributed systems, and file systems and Web systems coordination. For all developers, software engineers, and architects who need an in-depth understanding of distributed systems." |
Im Buch
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Seite 277
... store . A data store may be physically distributed across multiple machines . In particular , each process that can access data from the store is assumed to have a local ( or nearby ) copy available of the entire store . Write op ...
... store . A data store may be physically distributed across multiple machines . In particular , each process that can access data from the store is assumed to have a local ( or nearby ) copy available of the entire store . Write op ...
Seite 288
... data items . A consis- tency model describes what can be expected with respect to that set when multi- ple processes ... store . An important assumption is that concurrent processes may be simultaneously updating the data store , and ...
... data items . A consis- tency model describes what can be expected with respect to that set when multi- ple processes ... store . An important assumption is that concurrent processes may be simultaneously updating the data store , and ...
Seite 301
... store a copy of the data it has just requested . In principle , managing the cache is left entirely to the client . The data store from where the data had been fetched has nothing to do with keep- ing cached data consistent . However ...
... store a copy of the data it has just requested . In principle , managing the cache is left entirely to the client . The data store from where the data had been fetched has nothing to do with keep- ing cached data consistent . However ...
Inhalt
SYNCHRONIZATION | 6 |
ARCHITECTURES | 33 |
PROCESSES | 67 |
Urheberrecht | |
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Distributed Systems: Principles and Paradigms: Pearson New International Edition Andrew S. Tanenbaum,Maarten Van Steen Keine Leseprobe verfügbar - 2013 |
Distributed Systems: Principles and Paradigms Andrew S. Tanenbaum,Maarten van Steen Keine Leseprobe verfügbar - 2013 |
Distributed Systems: Principles and Paradigms Andrew S. Tanenbaum,Maarten van Steen Keine Leseprobe verfügbar - 2007 |
Häufige Begriffe und Wortgruppen
algorithm Alice allow application approach architecture assume cache called Chap client stub client-server clock communication components consider consistency models coordinator copy CORBA crashes data item data store database discussed distributed file systems distributed systems document domain encrypted entity example executed fault tolerance Figure file system global handle host identifier implemented important interface Internet invocation issues JavaSpace layer LDAP lookup machine message broker message-queuing systems middleware migration multicast name resolution name server name space object operating system organization overlay network packets path name peer-to-peer performance PlanetLab problem protocol queue manager receiver reference remote remote procedure calls replication request requires resource routing scalability sender sequential consistency server stub shared shown in Fig simple single solution specific stream synchronization thread timestamp tion transparency tuple updates write operations