|
Skip Graph
Skip graphs are a kind of distributed data structure based on skip lists. They were invented in 2003 by James Aspnes and Gauri Shah. A nearly identical data structure called SkipNet was independently invented by Nicholas Harvey, Michael Jones, Stefan Saroiu, Marvin Theimer and Alec Wolman, also in 2003. Skip graphs have the full functionality of a balanced tree in a distributed system. Skip graphs are mostly used in searching peer-to-peer networks. As they provide the ability to query by key ordering, they improve over search tools based on the hash table functionality only. In contrast to skip lists and other tree data structures, they are very resilient and can tolerate a large fraction of node failures. In addition, constructing, inserting, searching, and repairing a skip graph that was disturbed by failing nodes can be done by straightforward algorithms. Description A skip graph is a distributed data structure based on skip lists designed to resemble a balanced search tr ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Skip List
In computer science, a skip list (or skiplist) is a probabilistic data structure that allows \mathcal(\log n) average complexity for search as well as \mathcal(\log n) average complexity for insertion within an ordered sequence of n elements. Thus it can get the best features of a sorted array (for searching) while maintaining a linked list-like structure that allows insertion, which is not possible with a static array. Fast search is made possible by maintaining a linked hierarchy of subsequences, with each successive subsequence skipping over fewer elements than the previous one (see the picture below on the right). Searching starts in the sparsest subsequence until two consecutive elements have been found, one smaller and one larger than or equal to the element searched for. Via the linked hierarchy, these two elements link to elements of the next sparsest subsequence, where searching is continued until finally searching in the full sequence. The elements that are skipped ov ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Data Structure
In computer science, a data structure is a data organization, management, and storage format that is usually chosen for Efficiency, efficient Data access, access to data. More precisely, a data structure is a collection of data values, the relationships among them, and the functions or operations that can be applied to the data, i.e., it is an algebraic structure about data. Usage Data structures serve as the basis for abstract data types (ADT). The ADT defines the logical form of the data type. The data structure implements the physical form of the data type. Different types of data structures are suited to different kinds of applications, and some are highly specialized to specific tasks. For example, Relational database, relational databases commonly use B-tree indexes for data retrieval, while compiler Implementation, implementations usually use hash tables to look up identifiers. Data structures provide a means to manage large amounts of data efficiently for uses such a ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Doubly Linked List
In computer science, a doubly linked list is a linked data structure that consists of a set of sequentially linked records called nodes. Each node contains three fields: two link fields (references to the previous and to the next node in the sequence of nodes) and one data field. The beginning and ending nodes' previous and next links, respectively, point to some kind of terminator, typically a sentinel node or null, to facilitate traversal of the list. If there is only one sentinel node, then the list is circularly linked via the sentinel node. It can be conceptualized as two singly linked lists formed from the same data items, but in opposite sequential orders. The two node links allow traversal of the list in either direction. While adding or removing a node in a doubly linked list requires changing more links than the same operations on a singly linked list, the operations are simpler and potentially more efficient (for nodes other than first nodes) because there is no ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Adversary Model
In computer science, an online algorithm measures its competitiveness against different adversary models. For deterministic algorithms, the adversary is the same as the adaptive offline adversary. For randomized online algorithms competitiveness can depend upon the adversary model used. Common adversaries The three common adversaries are the oblivious adversary, the adaptive online adversary, and the adaptive offline adversary. The oblivious adversary is sometimes referred to as the weak adversary. This adversary knows the algorithm's code, but does not get to know the randomized results of the algorithm. The adaptive online adversary is sometimes called the medium adversary. This adversary must make its own decision before it is allowed to know the decision of the algorithm. The adaptive offline adversary is sometimes called the strong adversary. This adversary knows everything, even the random number generator. This adversary is so strong that randomization does not help agains ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Tapestry (DHT)
Tapestry is a peer-to-peer overlay network which provides a distributed hash table, routing, and multicasting infrastructure for distributed applications.{{cite journal , last=Zhao , first=Ben Y. , last2=Huang , first2=Ling , last3=Stribling , first3=Jeremy , last4=Rhea , first4=Sean C. , last5=Joseph , first5=Anthony D. , last6=Kubiatowicz , first6=John D., date=2004 , title=Tapestry: A Resilient Global-scale Overlay for Service Deployment , url=http://pdos.csail.mit.edu/~strib/docs/tapestry/tapestry_jsac03.pdf , journal=IEEE Journal on Selected Areas in Communications , volume=22 , issue=1 , pages=41–53 , doi=10.1109/JSAC.2003.818784 , access-date=13 January 2015, citeseerx=10.1.1.71.2718 The Tapestry peer-to-peer system offers efficient, scalable, self-repairing, location-aware routing to nearby resources. Introduction The first generation of peer-to-peer applications, including Napster, Gnutella, had restricting limitations such as a central directory for Napster and scoped ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Chord (peer-to-peer)
In computing, Chord is a protocol and algorithm for a peer-to-peer distributed hash table. A distributed hash table stores key-value pairs by assigning keys to different computers (known as "nodes"); a node will store the values for all the keys for which it is responsible. Chord specifies how keys are assigned to nodes, and how a node can discover the value for a given key by first locating the node responsible for that key. Chord is one of the four original distributed hash table protocols, along with CAN, Tapestry, and Pastry. It was introduced in 2001 by Ion Stoica, Robert Morris, David Karger, Frans Kaashoek, and Hari Balakrishnan, and was developed at MIT. The 2001 Chord paper won a ACM SIGCOMM Test of Time award in 2011. Subsequent research by Pamela Zave has shown that the original Chord algorithm (as specified in the 2001 SIGCOMM paper, the 2001 Technical report, the 2002 PODC paper, and the 2003 TON paper ) can mis-order the ring, produce several rings, and break ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Distributed Hash Table
A distributed hash table (DHT) is a 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. The main advantage of a DHT is that nodes can be added or removed with minimum work around re-distributing keys. ''Keys'' are unique identifiers which map to particular ''values'', which in turn can be anything from addresses, to documents, to arbitrary data. 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 ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Search Tree
In computer science, a search tree is a tree data structure used for locating specific keys from within a set. In order for a tree to function as a search tree, the key for each node must be greater than any keys in subtrees on the left, and less than any keys in subtrees on the right. The advantage of search trees is their efficient search time given the tree is reasonably balanced, which is to say the leaves at either end are of comparable depths. Various search-tree data structures exist, several of which also allow efficient insertion and deletion of elements, which operations then have to maintain tree balance. Search trees are often used to implement an associative array. The search tree algorithm uses the key from the key–value pair to find a location, and then the application stores the entire key–value pair at that particular location. Types of Trees Binary search tree A Binary Search Tree is a node-based data structure where each node contains a key and two ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Skip Lists
In computer science, a skip list (or skiplist) is a probabilistic data structure that allows \mathcal(\log n) average complexity for search as well as \mathcal(\log n) average complexity for insertion within an ordered sequence of n elements. Thus it can get the best features of a sorted array (for searching) while maintaining a linked list-like structure that allows insertion, which is not possible with a static array. Fast search is made possible by maintaining a linked hierarchy of subsequences, with each successive subsequence skipping over fewer elements than the previous one (see the picture below on the right). Searching starts in the sparsest subsequence until two consecutive elements have been found, one smaller and one larger than or equal to the element searched for. Via the linked hierarchy, these two elements link to elements of the next sparsest subsequence, where searching is continued until finally searching in the full sequence. The elements that are skipped ove ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Distributed Computing
A distributed system is a system whose components are located on different networked computers, which communicate and coordinate their actions by passing messages to one another from any system. Distributed computing is a field of computer science that studies distributed systems. The components of a distributed system interact with one another in order to achieve a common goal. Three significant challenges of distributed systems are: maintaining concurrency of components, overcoming the lack of a global clock, and managing the independent failure of components. When a component of one system fails, the entire system does not fail. Examples of distributed systems vary from SOA-based systems to massively multiplayer online games to peer-to-peer applications. A computer program that runs within a distributed system is called a distributed program, and ''distributed programming'' is the process of writing such programs. There are many different types of implementations for ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Balanced Tree
In computer science, a self-balancing binary search tree (BST) is any node-based binary search tree that automatically keeps its height (maximal number of levels below the root) small in the face of arbitrary item insertions and deletions.Donald Knuth. ''The Art of Computer Programming'', Volume 3: ''Sorting and Searching'', Second Edition. Addison-Wesley, 1998. . Section 6.2.3: Balanced Trees, pp.458–481. These operations when designed for a self-balancing binary search tree, contain precautionary measures against boundlessly increasing tree height, so that these abstract data structures receive the attribute "self-balancing". For height-balanced binary trees, the height is defined to be logarithmic \mathcal O(\log n) in the number n of items. This is the case for many binary search trees, such as AVL trees and red–black trees. Splay trees and treaps are self-balancing but not height-balanced, as their height is not guaranteed to be logarithmic in the number of items. Sel ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Node (graph Theory)
In discrete mathematics, and more specifically in graph theory, a vertex (plural vertices) or node is the fundamental unit of which graphs are formed: an undirected graph consists of a set of vertices and a set of edges (unordered pairs of vertices), while a directed graph consists of a set of vertices and a set of arcs (ordered pairs of vertices). In a diagram of a graph, a vertex is usually represented by a circle with a label, and an edge is represented by a line or arrow extending from one vertex to another. From the point of view of graph theory, vertices are treated as featureless and indivisible objects, although they may have additional structure depending on the application from which the graph arises; for instance, a semantic network is a graph in which the vertices represent concepts or classes of objects. The two vertices forming an edge are said to be the endpoints of this edge, and the edge is said to be incident to the vertices. A vertex ''w'' is said to be adj ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
