Resource constrained scheduling on multiple machines

Remy, Jan

doi:10.1016/j.ipl.2004.04.009

Cited by 17 publications

(6 citation statements)

References 4 publications

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“…Our improved scheduling algorithm achieves better results than simple weighted scheduling algorithm. Developed platform will be used for the testing and implementation of, as described in [5] [10], [19] and [22], more efficient heuristic and exact scheduling algorithms.…”

Section: Test Resultsmentioning

confidence: 99%

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Scheduling algorithms for dedicated nodes in Alchemi grid

Stanfel

Martinović

Hocenski

2008

2008 IEEE International Conference on Systems, Man and Cybernetics

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Computational grids are useful tools for bringing supercomputing power to users by using idle resources in the network. In the following paper we give a short overview of architecture of the Alchemi grid developed on .Net platform. We created a grid application, which utilizes Rabin-Karp string searching algorithm to test Alchemi grid performances in situation when requests put diverse demands for computing resources to the different grid nodes. Scheduling and dispatching jobs to the computing resources is a critical activity of the grid software. We present a scheduling algorithm which showed performance improvements to the original algorithm shipped with Alchemi grid software.

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Section: Test Resultsmentioning

confidence: 99%

“…Similar algorithms are described in [19] and [20]. The jobs are sorted by the payload from the one with highest payload to the one with the lowest in a descending order.…”

Section: Weighted Matching Schedulermentioning

confidence: 99%

Scheduling algorithms for dedicated nodes in Alchemi grid

Stanfel

Martinović

Hocenski

2008

2008 IEEE International Conference on Systems, Man and Cybernetics

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“…Many scheduling problems can be formulated as a resource constrained scheduling problem where a set of n jobs should be scheduled on m machines with given capacities. However, as shown in [22] this problem is NP-complete even for m = 1. Recognizing the proven difficulty of solving such scheduling problems, many studies have been undertaken using genetic algorithms, simulated annealing, tabu search, and other integer and linear programming related techniques.…”

Section: Related Workmentioning

confidence: 95%

“…This problem can be formulated as a resource constrained scheduling problem where a set of n jobs should be scheduled on m machines with given capacities. However, as shown in [22] this problem is NPcomplete even for m = 1. We provide a general integer programming (IP) formulation of the backup job scheduling problem for multiple tape drives configuration.…”

Section: Introductionmentioning

confidence: 97%

DP+IP = design of efficient backup scheduling

Cherkasova

Zhang

2010

2010 International Conference on Network and Service Management

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Many industries experience an explosion in digital content. This explosion of electronic documents, along with new regulations and document retention rules, sets new requirements for performance efficiency of traditional data protection and archival tools. During a backup session a predefined set of objects (client filesystems) should be backed up. Traditionally, no information on the expected duration and throughput requirements of different backup jobs is provided. This may lead to a suboptimal job schedule that results in the increased backup session time. In this work, we characterize each backup job via two metrics, called job duration and job throughput. These metrics are derived from collected historic information about backup jobs during previous backup sessions. Our goal is to automate the design of a backup schedule that minimizes the overall completion time for a given set of backup jobs. This problem can be formulated as a resource constrained scheduling problem where a set of n jobs should be scheduled on m machines with given capacities. We provide an integer programming (IP) formulation of this problem and use available IP-solvers for finding an optimized schedule, called binpacking schedule. Performance benefits of the new bin-packing schedule are evaluated via a broad variety of realistic experiments using backup processing data from six backup servers in HP Labs. The new bin-packing job schedule significantly optimizes the backup session time (20%-60% of backup time reduction). HP Data Protector (DP) is HP's enterprise backup offering and it can directly benefit from the designed technique. Moreover, significantly reduced backup session times guarantee an improved resource/power usage of the overall backup solution.

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“…There are a lot of modelings for the RCPSP that use both makespan and the available resources. The reader is referred to [3], [4], [5], [7], [8], [9], [10], [11].…”

Section: Introductionmentioning

confidence: 99%

New sequential and parallel algorithm for Dynamic Resource Constrained Project Scheduling Problem

Silva

Ochi

2009

2009 IEEE International Symposium on Parallel &Amp; Distributed Processing

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This paper proposes a new Evolutionary Algorithm for the Dynamic Resource Constrained Project Scheduling Problem.This algorithm has new features that get around some problems like premature convergence and other ones. The indirect representation approach was used because it allows the construction of a feasible solution from any input priorities. A parallel version is also proposed, making good use of multicore processors available nowadays. The results of sequential and parallel versions were very significant, improving in almost all ways the best results present in literature.

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Resource constrained scheduling on multiple machines

Cited by 17 publications

References 4 publications

Scheduling algorithms for dedicated nodes in Alchemi grid

Scheduling algorithms for dedicated nodes in Alchemi grid

DP+IP = design of efficient backup scheduling

New sequential and parallel algorithm for Dynamic Resource Constrained Project Scheduling Problem

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