Solving Scheduling Problems in Grid Resource Management Using an Evolutionary Algorithm

Stucky, Karl-Uwe; Jakob, Wilfried; Quinte, Alexander; Süß, Wolfgang

doi:10.1007/11914952_14

Cited by 9 publications

(7 citation statements)

References 19 publications

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“…Berman et al proposed a complex adaptive scheduling algorithm and dynamic resource selection method that can be performed automatically as well as co-allocation of data and computing (Berman et al, 2005). In addition, Stucky et al studied the evolution of GA-based grid resource scheduling problems (Stucky et al, 2006).…”

Section: K 435mentioning

confidence: 99%

A service oriented manufacturing grid system with uncertain information

et al. 2014

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Purpose -The increase in demand variability created by manufacturing enterprises presents new challenges for increasing resource usage and sharing flexibility. For this reason, it is of great importance to research manufacturing grids and their service modes. The purpose of this paper is to establish a systematic strategy and a system tool for manufacturing grid systems. Design/methodology/approach -A manufacturing service oriented manufacturing grid (MSoMG) system is presented with open grid service architecture as the system architecture and GT3.9 as a development tool. A framework is proposed to support MSoMG by providing advisory tools and methods for uncertain information analysis and processing, multi-objective decision making of manufacturing grid service execution, manufacturing grid service performance prediction based on knowledge template, and flexible manufacturing grid service scheduling and solution. The methodology of the adopted rough set is discussed in detail. Finally, the design support strategies for MSoMG are investigated to guide the coordination of manufacturing activities. Findings -Many conventional methods and models become very limited for manufacturing grid service with uncertain information. The processing of uncertain information and reasonable application flow can help to improve the completion rate and reliability of manufacturing grid services. Practical implications -This research provides a solid foundation for manufacturing gird operations and can promote the use of a manufacturing grid mode. Originality/value -A MSoMG system is presented. The manufacturing grid service with uncertain information is considered as well as design support strategies.

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Section: K 435mentioning

confidence: 99%

A service oriented manufacturing grid system with uncertain information

et al. 2014

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“…For example, when several virtual machines are dispatched to same physical machine, system performance of the latter would be greatly slowed or even cause meltdown. Hence algorithms on virtualization level resource load allocation becomes an active research theme [19] [20].…”

Section: Cloud Virtuliza Tl On and Load Balancementioning

confidence: 99%

Cloud and SNS supported collaboration in AEC industry

Jiao

Wang²,

Yuan³

et al. 2012

Proceedings of the 2012 IEEE 16th International Conference on Computer Supported Cooperative Work in Design (CSCWD)

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The intrinsic construction project nature of one-of-a kind and the requirement of massive data exchange make collaboration one of the critical factors towards success. However, due to the complexity of multiple phases and multi-disciplinary participants in project life cycle, industry level collaboration in Architecture, Engineering, and Construction (AEC) sector remains a challenge. This paper proposes an integrated solution based mainly on social network services (SNS) and cloud computing. We present a novel platform named Construction Business Social Network Service (CBSNS), which is promising to be adopted as an industrial scope collaboration cloud. We describe its main functions as well as its privacy control mechanism. To better support its deployment as a community cloud, a three-pass load balance algorithm is proposed. The first pass sorts initial virtual machines (VMs) and physical machines (PMs) using bubble algorithm, during which parameters such as hungry threshold are considered. The second pass builds mappings between allocable PM queue and requesting VM queue using first come first served strategy, and groups Non-allocable VMs after designated time slice.The third pass handles possible exceptions when finally such ones existing. The actual time complexity of the algorithm is O(n) .While the commercial implementation of the algorithm is ongoing, the proposed CBSNS has been developed and used in real life application.

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“…Both CCS and GORBA re‐compute the schedule from scratch when a dynamic change such as job arrival or machine failure appears. Although it helps to keep the schedule up to date, for large number of jobs this approach may be quite time consuming as was discussed in the case of GORBA (Stucky et al 2006). Several papers (Abraham, Buyya, and Nath 2000; Subrata, Zomaya, and Landfeldt 2007) propose local search‐based methods to solve Grid scheduling problems without total re‐computation; however, no experimental evaluation was presented in Abraham et al (2000), and (Subrata et al 2007) does include resource changes but no dynamic job arrivals.…”

Section: Introductionmentioning

confidence: 99%

“…Notably these authors are not aware of any earlier work in the context of Grid scheduling which would concentrate on incremental application of local search or schedule‐based methods and study its impact on running time of scheduling algorithms. Because re‐computation from scratch was discussed to be time consuming (Stucky et al 2006), our goal is to concentrate on these issues.…”

Section: Introductionmentioning

confidence: 99%

Efficient Grid Scheduling Through the Incremental Schedule‐based Approach

Klusáček¹,

Rudová²

2011

Computational Intelligence

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Although Grid users demand good performance for their jobs, this requirement is often not satisfied by the widely used queue-based scheduling approaches. This article concentrates on the application of schedule-based methods that improve on both the service delivered to the user and the traditional objective of machine usage. Importantly, the interaction between the incremental application of these methods and the dynamic character of the problem allows reasonable runtimes to be achieved. Two new schedule-based methods that are designed to schedule dynamically arriving jobs on machines in a computational Grid are formally described in the article. The Earliest Gap -Earlier Deadline First (EG-EDF) policy fills the earliest gap in the known schedule with newly arriving jobs, incrementally building a new schedule. If the gap is not suitable for an incoming job, the EDF policy is used to modify the existing schedule. A Tabu search algorithm is used to further optimize the schedule by moving selected jobs into the earliest suitable gaps. The proposed incremental schedule-based methods are compared with some of the most common queue-based scheduling algorithms such as FCFS (First Come First Served), EASY backfilling (Extensible Argonne Scheduler sYstem), Flexible backfilling as well as with the nonincremental version of the EG-EDF schedule-based policy.

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Solving Scheduling Problems in Grid Resource Management Using an Evolutionary Algorithm

Cited by 9 publications

References 19 publications

A service oriented manufacturing grid system with uncertain information

A service oriented manufacturing grid system with uncertain information

Cloud and SNS supported collaboration in AEC industry

Efficient Grid Scheduling Through the Incremental Schedule‐based Approach

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