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14
How to Allocate Network Centers
 J. Algorithms
, 1992
"... This paper deals with the issue of allocating and utilizing centers in a distributed network, in its various forms. The paper discusses the significant parameters of center allocation, defines the resulting optimization problems, and proposes several approximation algorithms for selecting centers ..."
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Cited by 73 (4 self)
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This paper deals with the issue of allocating and utilizing centers in a distributed network, in its various forms. The paper discusses the significant parameters of center allocation, defines the resulting optimization problems, and proposes several approximation algorithms for selecting centers and for distributing the users among them. We concentrate mainly on balanced versions of the problem, i.e., in which it is required that the assignment of clients to centers be as balanced as possible. The main results are constant ratio approximation algorithms for the balanced centers and balanced weighted centers problems, and logarithmic ratio approximation algorithms for the aedominating set and the ktolerant set problems. School of Library and Information, The Hebrew University, Jerusalem 9xxxx, Israel. This work was carried out while the author was with the Department of Applied Mathematics and Computer Science, The Weizmann Institute of Science. y Department of Applied M...
Compact and Localized Distributed Data Structures
 JOURNAL OF DISTRIBUTED COMPUTING
, 2001
"... This survey concerns the role of data structures for compactly storing and representing various types of information in a localized and distributed fashion. Traditional approaches to data representation are based on global data structures, which require access to the entire structure even if the sou ..."
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Cited by 72 (23 self)
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This survey concerns the role of data structures for compactly storing and representing various types of information in a localized and distributed fashion. Traditional approaches to data representation are based on global data structures, which require access to the entire structure even if the sought information involves only a small and local set of entities. In contrast, localized data representation schemes are based on breaking the information into small local pieces, or labels, selected in a way that allows one to infer information regarding a small set of entities directly from their labels, without using any additional (global) information. The survey focuses on combinatorial and algorithmic techniques, and covers complexity results on various applications, including compact localized schemes for message routing in communication networks, and adjacency and distance labeling schemes.
Fast Distributed Construction of Small kDominating Sets and Applications
, 2000
"... This paper presents a fast distributed algorithm to compute a small kdominating set D (for any xed k) and its induced graph partition (breaking the graph into radius k clusters centered around the vertices of D). The time complexity of the algorithm is O(k log n). ..."
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Cited by 56 (8 self)
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This paper presents a fast distributed algorithm to compute a small kdominating set D (for any xed k) and its induced graph partition (breaking the graph into radius k clusters centered around the vertices of D). The time complexity of the algorithm is O(k log n).
A distributed databalanced dictionary based on the blink tree
 in Proceeding of IPPS’92
, 1992
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A Distributed, Replicated, DataBalanced Search Structure
 International Journal of High Speed Computing
, 1994
"... Many concurrent dictionary data structures have been proposed, but usually in the context of shared memory multiprocessors. In this paper, we present an algorithm for a concurrent distributed Btree that can be implemented on message passing computer systems. Our distributed Btree (the dBtree) ..."
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Cited by 6 (1 self)
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Many concurrent dictionary data structures have been proposed, but usually in the context of shared memory multiprocessors. In this paper, we present an algorithm for a concurrent distributed Btree that can be implemented on message passing computer systems. Our distributed Btree (the dBtree) replicates the interior nodes in order to improve parallelism and reduce message passing. The dBtree stores some redundant information in its nodes to permit the use of lazy updates to maintain replica coherency. We show how the dBtree algorithm can be used to build an efficient implementation of a highly parallel, databalanced distributed dictionary, the dEtree. Keywords: Concurrent dictionary data structures, Message passing multiprocessor systems, Balanced search trees, Blink trees, Replica coherency. 1. Introduction. We introduce a new balanced search tree algorithm for distributed memory architectures. The search tree uses the Blink tree [27] as a base, and distributes ow...
Highly Scalable Data Balanced Distributed Btrees
, 1995
"... Scalable distributed search structures are needed to maintain large volumes of data and for parallel databases. In this paper, we analyze the performance of two large scale databalanced distributed search structures, the dBtree and the dEtree. The dBtree is a distributed Btree that replicates i ..."
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Cited by 2 (1 self)
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Scalable distributed search structures are needed to maintain large volumes of data and for parallel databases. In this paper, we analyze the performance of two large scale databalanced distributed search structures, the dBtree and the dEtree. The dBtree is a distributed Btree that replicates its interior nodes. The dEtree is a dBtree in which leaf nodes represent key ranges, and thus requires far fewer nodes to represent a distributed index. The performance of both algorithms depends on the method by which tree nodes are assigned to processors (i.e., the algorithm for performing data balancing). We present a simulation study of data balancing algorithms for the dBtree and the dEtree. We find that a simple distributed data balancing algorithm works well for the dBtree, requiring only a small space and message passing overhead. We compare three algorithms for data balancing in a dEtree, and find that the most aggressive of the algorithms makes the dEtree scalable. Using the ...
SelfOptimizing Distributed Trees
"... We present a novel protocol for restructuring a treebased overlay network in response to the workload of the application running over it. Through lowcost restructuring operations, our protocol incrementally adapts the tree so as to bring nodes that tend to communicate with one another closer togeth ..."
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We present a novel protocol for restructuring a treebased overlay network in response to the workload of the application running over it. Through lowcost restructuring operations, our protocol incrementally adapts the tree so as to bring nodes that tend to communicate with one another closer together in the tree. It achieves this while respecting degree bounds on nodes so that, e.g., no node degenerates into a “hub ” for the overlay. Moreover, it limits restructuring to those parts of the tree over which communication takes place, avoiding restructuring other parts of the tree unnecessarily. We show via experiments on PlanetLab that our protocol can significantly reduce communication latencies in workloads dominated by clusters of communicating nodes. 1.
SelfAdjusting Distributed Trees
, 2005
"... An object retrieval protocol that enforces mutually exclusive access to a shared object is an important primitive employed by many distributed applications including distributed directories, distributed resource sharing systems and ordered multicast protocols, to name a few. Most existing implementa ..."
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An object retrieval protocol that enforces mutually exclusive access to a shared object is an important primitive employed by many distributed applications including distributed directories, distributed resource sharing systems and ordered multicast protocols, to name a few. Most existing implementations of this object retrieval primitive use a tree as the underlying communication structure due to the simple acyclic nature of trees. The worst case performance of this primitive and of the large body of applications built upon it, is O(n) for n nodes sharing the object. In this paper, we present a novel distributed selfadjusting tree for object retrieval protocols that guarantees the message complexity per retrieval, averaged over the worst case sequence of retrievals, to be O(log n). In addition, our algorithm adjusts only portions of the tree in which retrievals occur; this is advantageous when the tree structure reflects network proximity. We implement best known techniques from the centralized setting and compare their performance with our algorithm. Results are presented from experiments carried out on PlanetLab to evaluate the performance of different schemes under different workloads. We also present extensions to our basic protocol allowing a wide range of distributed applications including atomic broadcast and content discovery to achieve better performance using our techniques. To our knowledge, this is the first attempt to reduce access costs in a distributed tree where the tree dynamically adjusts itself during use to achieve O(log n) performance for worst case workloads.
Proc. of the 19th Workshop on Combinatorial Mathematics and Computation Theory Distributed Algorithms of Finding the Unique Minimum Distance Dominating Set in Directed
"... A distancek dominating set S of a directed graph D is a set of vertices such that for every vertex v of D, there is a vertex u ∈ S at distance at most k from it. Minimum distancek dominating set is especially important in communication networks for distributed data structure and for server placeme ..."
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A distancek dominating set S of a directed graph D is a set of vertices such that for every vertex v of D, there is a vertex u ∈ S at distance at most k from it. Minimum distancek dominating set is especially important in communication networks for distributed data structure and for server placement. In this paper, we shall present simple distributed algorithms for finding the unique minimum distancek dominating set for k = 1, 2 in a directed splitstar, which has recently been developed as a new model of the interconnection network for parallel and distributed computing systems. 1
unknown title
, 1992
"... This paper deals with the issue of allocating and utilizing centers in a distributed network, in its various forms. The paper discusses the signicant parameters of center allocation, denes the resulting optimization problems, and proposes several approximation algorithms for selecting centers and f ..."
Abstract
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This paper deals with the issue of allocating and utilizing centers in a distributed network, in its various forms. The paper discusses the signicant parameters of center allocation, denes the resulting optimization problems, and proposes several approximation algorithms for selecting centers and for distributing the users among them. We concentrate mainly on balanced versions of the problem, i.e., in which it is required that the assignment of clients to centers be as balanced as possible. The main results are constant ratio approximation algorithms for the balanced centers and balanced weighted centers problems, and logarithmic ratio approximation algorithms for the dominating set and the ktolerant set problems.