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Scheduling multiprocessor tasks  An overview
 EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
, 1996
"... Multiprocessor tasks require more than one processor at the same moment of time. This relatively new concept in scheduling theory emerged with the advent of parallel computing systems. In this work we present the state of the art for multiprocessor task scheduling. We show the rationale behind the c ..."
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Cited by 49 (3 self)
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Multiprocessor tasks require more than one processor at the same moment of time. This relatively new concept in scheduling theory emerged with the advent of parallel computing systems. In this work we present the state of the art for multiprocessor task scheduling. We show the rationale behind the concept of multiprocessor tasks. The standard threefield notation is extended to accommodate multiprocessor tasks. The main part of the work is presentation of the results in multiprocessor tasks scheduling both for parallel and for dedicated processors.
Scheduling workflow applications on processors with different capabilities
, 2006
"... Efficient scheduling of workflow applications represented by weighted directed acyclic graphs (DAG) on a set of heterogeneous processors is essential for achieving high performance. The optimization problem is NPcomplete in general. A few heuristics for scheduling on heterogeneous systems have been ..."
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Cited by 26 (1 self)
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Efficient scheduling of workflow applications represented by weighted directed acyclic graphs (DAG) on a set of heterogeneous processors is essential for achieving high performance. The optimization problem is NPcomplete in general. A few heuristics for scheduling on heterogeneous systems have been proposed recently. However, few of them consider the case where processors have different capabilities. In this paper, we present a novel list scheduling based algorithm to deal with this situation. The algorithm (SDC) has two distinctive features. First, the algorithm takes into account the effect of Percentage of Capable Processors (PCP) when assigning the task node weights. For two task nodes with same average computation cost, our weight assignment policy tends to give higher weight to the task with small PCP. Secondly, during the processor selection phase, the algorithm adjusts the effective Earliest Finish Time strategy by incorporating the average communication cost between the current scheduling node and its children. Comparison study shows that our algorithm performs better than related work overall.
www.elsevier.com/locate/fgcs Complete and fragmented replica selection and retrieval in Data Grids
, 2006
"... Data Grids support dataintensive applications in wide area Grid systems. They utilize local storage systems as distributed data stores by replicating datasets. Replication is a commonly used technique in a distributed environment. The motivation of replication is that replication can improve data a ..."
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Cited by 7 (0 self)
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Data Grids support dataintensive applications in wide area Grid systems. They utilize local storage systems as distributed data stores by replicating datasets. Replication is a commonly used technique in a distributed environment. The motivation of replication is that replication can improve data availability, data access performance, and load balancing. Usually a complete file is copied to many Grid sites for local access. However, a site may only need parts of a replica. Therefore, to use the storage systems efficiently, it is necessary for a Grid site to store only parts of a replica. In this paper, we propose a concept called fragmented replicas. That is, when doing replication, a site can store only some partial contents needed locally. It can greatly save the storage space wasted in storing unused data. We also propose a block mapping procedure to determine the distribution of blocks in every available server for later replica retrieval. According to this procedure, a server can provide its available partial replica contents for other members in the Grid system to access. On the other hand, a client can retrieve a fragmented replica directly by using the block mapping procedure. After the block mapping procedure, some coallocation schemes can be used to retrieve data sets from the available servers. The simulation shows that the coallocation schemes also improve download performance in a fragmented replication system. c ○ 2006 Elsevier B.V. All rights reserved.
Scheduling With Constrained Processor Allocation for Interval Orders
 Computers in Operations Research 20
, 1993
"... We consider a generalization of the precedence constrained scheduling problem of a set of unit execution time (UET) jobs on a set of processors or machines. Each job is associated a subset P (j) of the processors, and a job can only be executed on one of the processors in P (j). First, we show that ..."
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Cited by 4 (1 self)
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We consider a generalization of the precedence constrained scheduling problem of a set of unit execution time (UET) jobs on a set of processors or machines. Each job is associated a subset P (j) of the processors, and a job can only be executed on one of the processors in P (j). First, we show that this problem is NPcomplete for interval orders. Next, the problem can be solved in polynomial time for interval orders, if the deadline is constant. Last, we give a heuristic for the scheduling problem restricted to interval orders with approximation ratio O(log(jP j)).
MinimumHotSpot Query Trees for Wireless Sensor Networks
"... Weproposeadistributedalgorithmtoconstructabalancedcommunication tree that serves in gathering data from the network nodes toasink. Ouralgorithmconstructsanearoptimallybalancedcommunication tree with minimum overhead. The balancing of the nodedegreesresultsintheminimizationofpacketcollisionsduring q ..."
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Cited by 4 (2 self)
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Weproposeadistributedalgorithmtoconstructabalancedcommunication tree that serves in gathering data from the network nodes toasink. Ouralgorithmconstructsanearoptimallybalancedcommunication tree with minimum overhead. The balancing of the nodedegreesresultsintheminimizationofpacketcollisionsduring query execution, that would otherwise require numerous retransmissions and reduce the lifetime of the network. We compare our simple distributed algorithm against previous work and a centralizedsolutionandshowthatformostnetworklayoutsitoutperforms competition and achieves tree balance very close to the centralized algorithm. Italsohasthesmallestenergyoverheadpossibletoconstructthe tree, increasing the lifetime of the network even more.
The \betaAssignment Problem in General Graphs
"... We study a variation of the assignment problem in operations research and formulate it in terms of graphs as follows. Suppose G = (V; E) is a graph and U a subset of V. A fiassignment of G with respect to U is an edge set X such that deg X (v) = 1 for all vertices v in U , where deg X (v) is the d ..."
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Cited by 1 (0 self)
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We study a variation of the assignment problem in operations research and formulate it in terms of graphs as follows. Suppose G = (V; E) is a graph and U a subset of V. A fiassignment of G with respect to U is an edge set X such that deg X (v) = 1 for all vertices v in U , where deg X (v) is the degree of v in the subgraph of G induced by the edge set X. The fiassignment problem is to find a fiassignment X such that fi(X) j maxfdeg X (v) : v 2 V \Gamma Ug is minimum. The purpose of this paper is to give an O(n 3 )time algorithm for the fiassignment problem in general graphs. As byproducts, we also get a duality theorem as well as a necessary and sufficient condition for the existence of a fiassignment for a general graph. The latter result is a generalization of Tutte's theorem for the existence of a perfect matching of a general graph.
The betaAssignment Problems
 International J. Math
, 1993
"... Suppose G = (S; T; E) is a bipartite graph, where (S; T ) is a bipartition of the vertex set. A fiassignment is an edge set X ` E such that deg X (i) = 1 for all i 2 S. The cardinality fiassignment problem is to find a fiassignment X which minimizes fi(X) = max j2T deg X (j). Suppose we associat ..."
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Suppose G = (S; T; E) is a bipartite graph, where (S; T ) is a bipartition of the vertex set. A fiassignment is an edge set X ` E such that deg X (i) = 1 for all i 2 S. The cardinality fiassignment problem is to find a fiassignment X which minimizes fi(X) = max j2T deg X (j). Suppose we associate every edge with a weight which is a real number. The bottleneck fi assignment problem is to find a fiassignment X that minimizes fi(X) and maximizes the minimum edge weight on X. The weighted fiassignment problem is to find a fiassignment X that minimizes fi(X) and maximizes the total weights of edges in X. This paper presents O(jSjjEj)time algorithms for the cardinality and the bottleneck fiassignment problems and an O(jSj 2 jT j + jSjjT j 2 )time algorithm for the weighted fiassignment problem. Key words. assignment, bottleneck, augmenting path, label 1. Introduction Chang and Lee [3] posed the following kind of assignment problem. Suppose there is a set S of n jobs an...
Università di Salerno
"... We study a version of the βassignment problem [3] on asynchronous rings: consider a set of items and a set of m colors, where each item is associated to one color. Consider also n computational agents connected by an asynchronous ring. Each agent holds a subset of the items, where initially differe ..."
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We study a version of the βassignment problem [3] on asynchronous rings: consider a set of items and a set of m colors, where each item is associated to one color. Consider also n computational agents connected by an asynchronous ring. Each agent holds a subset of the items, where initially different agents might hold items associated to the same color. We analyze the problem of distributively assigning colors to agents in such a way that (a) each color is assigned to one agent and (b) the number of different colors assigned to each agent is minimum. Since any color assignment requires that the items be distributed according to it (e.g. all items of the same color are to be held by only one agent), we define the cost of a color assignment as the amount of items that need to be moved, given an initial allocation. We first show that any distributed algorithm for this problem on the ring requires a communication complexity of Ω(n · m) and then we exhibit a polynomial time distributed algorithm with message complexity matching the bound, that determines a color assignment with cost at most (2 + ɛ) times the optimal cost, for any 0 <ɛ<1. Work supported in part by the European RTN Project under contract HPRNCT200200278, COMBSTRU. 1.