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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 .
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 [50] was originally presented as a parallel algorithm, but the same technique can also be used directly as a distributed algorithm.
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
The distributed minimum spanning tree (MST) problem involves the construction of a minimum spanning tree by a distributed algorithm, in a network where nodes communicate by message passing. It is radically different from the classical sequential problem, although the most basic approach resembles Borůvka's algorithm .
The Lamport timestamp algorithm is a simple logical clock algorithm used to determine the order of events in a distributed computer system.As different nodes or processes will typically not be perfectly synchronized, this algorithm is used to provide a partial ordering of events with minimal overhead, and conceptually provide a starting point for the more advanced vector clock method.
In computer networking and databases, the three-phase commit protocol (3PC) [1] is a distributed algorithm which lets all nodes in a distributed system agree to commit a transaction. It is a more failure-resilient refinement of the two-phase commit protocol (2PC).
Distributed tree search (DTS) algorithm is a class of algorithms for searching values in an efficient and distributed manner.Their purpose is to iterate through a tree by working along multiple branches in parallel and merging the results of each branch into one common solution, in order to minimize time spent searching for a value in a tree-like data structure.
MapReduce is a programming model and an associated implementation for processing and generating big data sets with a parallel and distributed algorithm on a cluster. [1] [2] [3]A MapReduce program is composed of a map procedure, which performs filtering and sorting (such as sorting students by first name into queues, one queue for each name), and a reduce method, which performs a summary ...