Distributed AlgorithmsElsevier, 16.04.1996 - 904 Seiten In Distributed Algorithms, Nancy Lynch provides a blueprint for designing, implementing, and analyzing distributed algorithms. She directs her book at a wide audience, including students, programmers, system designers, and researchers. Distributed Algorithms contains the most significant algorithms and impossibility results in the area, all in a simple automata-theoretic setting. The algorithms are proved correct, and their complexity is analyzed according to precisely defined complexity measures. The problems covered include resource allocation, communication, consensus among distributed processes, data consistency, deadlock detection, leader election, global snapshots, and many others. The material is organized according to the system model—first by the timing model and then by the interprocess communication mechanism. The material on system models is isolated in separate chapters for easy reference. The presentation is completely rigorous, yet is intuitive enough for immediate comprehension. This book familiarizes readers with important problems, algorithms, and impossibility results in the area: readers can then recognize the problems when they arise in practice, apply the algorithms to solve them, and use the impossibility results to determine whether problems are unsolvable. The book also provides readers with the basic mathematical tools for designing new algorithms and proving new impossibility results. In addition, it teaches readers how to reason carefully about distributed algorithms—to model them formally, devise precise specifications for their required behavior, prove their correctness, and evaluate their performance with realistic measures. |
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... simulations. An invariant assertion is a property that is true of all reachable states of a system. Assertions are generally proved by induction on the number of steps in a system execution. A simulation is a formal relationship between ...
... simulations. Roughly speaking, the goal is to show that one synchronous algorithm A “implements” another synchronous ... relation. As for invariant assertions, simulation relationships are generally proved by induction on the number of ...
... simulation relation, which is just an invariant assertion that involves the states of both algorithms after the same number of rounds. Assertion 4.1.7 For any r, 0 < r < diam, after r rounds, the values of the u, mat-uid, status, and ...
... relating it to FloodSet using a simulation relation (a similar strategy was used in Section 4.1.3 to prove correctness of OptPloodMax by relating it to FloodMaw). This requires first filling in the details in the description of ...
... relating it to EIGStop using a simulation relation. The proof is similar to the proof of correctness of OptPloodSet. Alternatively, a correctness proof that relates OptEIGStop to OptiPloodSet can be given. Details are left for exercises ...
Inhalt
1 | |
15 | |
Asynchronous Algorithms | 197 |
Asynchronous Shared Memory Algorithms | 235 |
Asynchronous Network Algorithms | 455 |
Partially Synchronous Algorithms | 733 |
Bibliography | 829 |
Index | 857 |
Related Titles from Morgan Kaufmann | 873 |
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Reasoning About Knowledge Ronald Fagin,Joseph Y. Halpern,Yoram Moses,Moshe Vardi Eingeschränkte Leseprobe - 2004 |