Distributed Hash Table (DHT)
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A Distributed Hash Table (DHT) is a hash table that is a distributed object.
- Context:
- …
- Example(s):
- a Peer-to-Peer DHT.
- …
- Counter-Example(s):
- See: Anycast, Web Cache, Domain Name System, Instant Messaging, Multicast, Peer-to-Peer, Immutable Object.
References
2015
- (Wikipedia, 2015) ⇒ http://en.wikipedia.org/wiki/distributed_hash_table Retrieved:2015-6-19.
- A distributed hash table (DHT) is a class of a decentralized distributed system that provides a lookup service similar to a hash table: (key, value) pairs are stored in a DHT, and any participating node can efficiently retrieve the value associated with a given key. Responsibility for maintaining the mapping from keys to values is distributed among the nodes, in such a way that a change in the set of participants causes a minimal amount of disruption. This allows a DHT to scale to extremely large numbers of nodes and to handle continual node arrivals, departures, and failures.
DHTs form an infrastructure that can be used to build more complex services, such as anycast, cooperative Web caching, distributed file systems, domain name services, instant messaging, multicast, and also peer-to-peer file sharing and content distribution systems. Notable distributed networks that use DHTs include BitTorrent's distributed tracker, the Coral Content Distribution Network, the Kad network, the Storm botnet, the Tox instant messenger, Freenet and the YaCy search engine.
- A distributed hash table (DHT) is a class of a decentralized distributed system that provides a lookup service similar to a hash table: (key, value) pairs are stored in a DHT, and any participating node can efficiently retrieve the value associated with a given key. Responsibility for maintaining the mapping from keys to values is distributed among the nodes, in such a way that a change in the set of participants causes a minimal amount of disruption. This allows a DHT to scale to extremely large numbers of nodes and to handle continual node arrivals, departures, and failures.
- (Helland, 2015) ⇒ Pat Helland. (2015). “Immutability Changes Everything.” In: Proceedings of the Conference on Innovative Data Systems Research (CIDR-2015).
2005
- (Rodrigues & Liskov, 2005) ⇒ Rodrigo Rodrigues, and Barbara Liskov. (2005). “High Availability in DHTs: Erasure Coding Vs. Replication.” In: Proc. of the 4th International Workshop on Peer-to-Peer Systems. doi:10.1007/11558989_21
- QUOTE: High availability in peer-to-peer DHTs requires data redundancy. This paper compares two popular redundancy schemes: replication and reasure coding. Unlike previous comparisons, we take the characteristics of the nodes that comprise the overlay into account, and conclude that in some cases the benefits from coding are limited, and may not be worth its disadvantages.