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A distributed algorithm is an algorithm designed to run on computer hardware constructed from interconnected processors. Distributed algorithms are used in different application areas of distributed computing , such as telecommunications , scientific computing , distributed information processing , and real-time process control .
Cannon's algorithm; Chandra–Toueg consensus algorithm; Chandy–Lamport algorithm; Chang and Roberts algorithm; Cole–Vishkin algorithm; Commitment ordering; Comparison of streaming media software; Conflict-free replicated data type; Content delivery network; Cristian's algorithm
While the field of parallel algorithms has a different focus than the field of distributed algorithms, there is much interaction between the two fields. For example, the Cole–Vishkin algorithm for graph coloring [52] was originally presented as a parallel algorithm, but the same technique can also be used directly as a distributed algorithm.
Deadlock prevention algorithms; Decentralized application; Decentralized autonomous organization; Decomposable aggregation function; Distributed algorithmic mechanism design; Distributed cache; Distributed Computing (journal) Distributed Computing Environment; Distributed Data Management Architecture; Distributed ledger; Double-spending
An algorithm is fundamentally a set of rules or defined procedures that is typically designed and used to solve a specific problem or a broad set of problems.. Broadly, algorithms define process(es), sets of rules, or methodologies that are to be followed in calculations, data processing, data mining, pattern recognition, automated reasoning or other problem-solving operations.
As of November 2024, Windows 11, accounting for 35% of Windows installations worldwide, [20] is the second most popular Windows version in use, with its predecessor Windows 10 still being the most used version in virtually all countries (with Guyana being an exception, where Windows 11 is the most used [21]), with it globally at over 2 times ...
Game theory and distributed computing both deal with a system with many agents, in which the agents may possibly pursue different goals. However they have different focuses. For instance one of the concerns of distributed computing is to prove the correctness of algorithms that tolerate faulty agents and agents performing actions concurrently.
Sardinas–Patterson algorithm; Sequential algorithm; Serial algorithm; Shapiro–Senapathy algorithm; Shuffling algorithm; Sieve of Eratosthenes; Sieve of Pritchard; Sikidy; Simulation algorithms for atomic DEVS; Simulation algorithms for coupled DEVS; Snap rounding; Sparse identification of non-linear dynamics; Spreading activation