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A Practical Minimum Spanning Tree Algorithm Using the Cycle Property
 IN 11TH EUROPEAN SYMPOSIUM ON ALGORITHMS (ESA), NUMBER 2832 IN LNCS
, 2003
"... We present a simple new (randomized) algorithm for computing minimum spanning trees that is more than two times faster than the best previously known algorithms (for dense, "difficult" inputs). It is of conceptual interest that the algorithm uses the property that the heaviest edge in a cy ..."
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We present a simple new (randomized) algorithm for computing minimum spanning trees that is more than two times faster than the best previously known algorithms (for dense, "difficult" inputs). It is of conceptual interest that the algorithm uses the property that the heaviest edge in a cycle can be discarded. Previously this has only been exploited in asymptotically optimal algorithms that are considered impractical. An additional advantage is...
A Parallel Tabu Search Alglorithm for the Quadratic Assignment Problem
"... A parallel version of the tabu search algorithm is implemented and used to optimize the solutions for a quadratic assignment problem (QAP). The instances are taken from the qaplib website 1 and we mainly concentrate on solving and optimizing the instances announced by Sergio Carvalho derived from th ..."
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A parallel version of the tabu search algorithm is implemented and used to optimize the solutions for a quadratic assignment problem (QAP). The instances are taken from the qaplib website 1 and we mainly concentrate on solving and optimizing the instances announced by Sergio Carvalho derived from the “Microarray Placement Problem ” 2 where one wants to find an arrangement of the probes (small DNA fragments) on specific locations of a microarray chip. We briefly explain combinatorics including graph theory and also the theory behind combinatorial optimization, heuristics and metaheuristcs. A description of some network optimization problems are also introduced before we apply our parallel tabu search algorithm to the quadratic assignment problem. Different approaches like Boltzmann selection procedure and random restarts are used to optimize the solutions. Through our experiments, we show that our parallel version of tabu Search do indeed manage to further optimize and even find better solutions found so far in the litterature. We try out a communication protocol based on sequentially generating graphs, where each node in the graph corresponds to a CPU or tabu search thread. One of the main goals is to find out if communication helps to further optimize the best known solution found so far for each instace.
A NOVEL ALGORITHM FOR CENTRAL CLUSTER USING MINIMUM SPANNING TREE
"... The minimum spanning tree clustering algorithm is capable of detecting clusters with irregular boundaries. In this paper we propose a novel minimum spanning tree based clustering algorithm. The algorithm produces k clusters with center and guaranteed intracluster similarity. The algorithm uses divi ..."
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The minimum spanning tree clustering algorithm is capable of detecting clusters with irregular boundaries. In this paper we propose a novel minimum spanning tree based clustering algorithm. The algorithm produces k clusters with center and guaranteed intracluster similarity. The algorithm uses divisive approach to produce k number of clusters. The center points are considered as representative points for each cluster. These center points are connected and again minimum spanning tree is constructed. Using eccentricity of points the central cluster is identified from k number of clusters
Transactional Support in MapReduce for Speculative Parallelism
"... MapReduce has emerged as a popular programming model for largescale distributed computing. Its framework enforces strict synchronization between successive map and reduce phases and limited datasharing within a phase. Use of keyvalue based persistent storage with MapReduce presents intriguing opp ..."
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MapReduce has emerged as a popular programming model for largescale distributed computing. Its framework enforces strict synchronization between successive map and reduce phases and limited datasharing within a phase. Use of keyvalue based persistent storage with MapReduce presents intriguing opportunities and challenges. These challenges relate primarily to semantic inconsistencies arising from the different faulttolerant mechanisms employed by the execution environment and the underlying storage medium. We define formal transactional semantics for MapReduce over reliable keyvalue stores. With minimal performance overhead and no increase in program complexity, our solutions support broad classes of distributed applications hitherto infeasible in MapReduce. Specifically, this paper (i) motivates the use of keyvalue stores as the underlying storage for MapReduce, (ii) defines transactional semantics for MapReduce to address any inconsistencies, (iii) demonstrates broader application scope enabled by data sharing within and across jobs, and (iv) presents a detailed evaluation demonstrating the low overhead of our proposed semantics. 1.