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computational grids in action: the National Fusion Collaboratory

FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE 2002年第8期18卷 1005-1015页

作者： Keahey, K Fredian, T Peng, Q Schissel, DP Thompson, M Foster, I Greenwald, M McCune, D Argonne Natl Lab Div Math & Comp Sci Argonne IL 60439 USA MIT Plasma Sci & Fus Ctr Cambridge MA 02139 USA Gen Atom Co San Diego CA 92186 USA Lawrence Berkeley Natl Lab Berkeley CA 94720 USA Univ Chicago Dept Comp Sci Chicago IL 60657 USA Princeton Plasma Phys Lab Princeton NJ 08543 USA

The National Fusion Collaboratory (NFC) project was created to advance scientific understanding and innovation in magnetic fusion research by enabling more efficient use of existing experimental facilities through more effective integration of experiment, theory, and modeling. To achieve this objective, NFC introduced the concept of "network services", which build on top of computational grids, and provide Fusion codes, together with their maintenance and hardware resources as a service to the community. This mode of operation requires the development of new authorization and enforcement capabilities. In addition, the nature of Fusion experiments places strident quality of service requirements on codes run during the experimental cycle. In this paper, we describe Grid computing requirements of the Fusion community, and present our first experiments in meeting those requirements. Published by Elsevier Science B.V.

关键词： computational grids network services distributed computing fusion collaboratory

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Knowledge discovery for scheduling in computational grids

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WILEY INTERDISCIPLINARY REVIEWS-DATA MINING AND KNOWLEDGE DISCOVERY 2012年第4期2卷 287-297页

作者： Foelling, Alexander Lepping, Joachim Grenoble Univ INRIA Rhone Alpes Montbonnot St Martin France TU Dortmund Univ Robot Res Inst Dortmund Germany

Scheduling in computational grids addresses the allocation of computing jobs to globally distributed compute resources. In a frequently changing resource environment, scheduling decisions have to be made rapidly. Depending on both the job properties and the current state of the resources, those decisions are different. Thus, the performance of grid scheduling systems highly depends on their adaptivity and flexibility in changing environments. Under these conditions, methods from knowledge discovery yielded significant success to augment and substitute conventional grid scheduling techniques. This paper presents a survey on approaches to extract, represent, and utilize knowledge to improve the grid scheduling performance. It aims to give researchers insight into techniques used for knowledge-supported scheduling in large-scale distributed computing environments. (c) 2012 Wiley Periodicals, Inc.

关键词： current status data mining large sizes Changing environments computational grids allocation

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APPLYING AN IMPROVED FAST ANT SYSTEM TO DAG SCHEDULING FOR computational grids

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JOURNAL OF THE CHINESE INSTITUTE OF ENGINEERS 2008年第7期31卷 1113-1125页

作者： Chiang, Chuan-Wen Natl KaohSiung First Univ Sci & Technol Dept Comp & Commun Engn Kaohsiung 811 Taiwan

computational grids have recently attracted considerable attention as cost-effective platforms for parallel processing. Generally a parallel program carried Out Oil such a platform can he characterized as a directed acyclic graph (DAG). To take full advantage of available resources in,rids and achieve hi( h computational performance, all effective DAG scheduling algorithm is indispensable. This study presents a novel constructive algorithm based oil the Fast Ant System (FANT). The proposed algorithm. namely. the Fast Ant System for Task Matching and Scheduling (FANT-TMS) algorithm. determines the scheduling order of all tasks in it parallel program and, then, allocates these tasks to appropriate processing elements in a computational grid, thereby minimizing total completion time of the parallel program. Performance of the FANT-TMS algorithm is demonstrated by comparison with a genetic algorithm (GA)-based scheduling technique ill terms of overall schedule length of randomly generated DAGs. Experimental results demonstrate that the proposed algorithm Outperforms file conventional GA-based approach. Additionally, a novel local search strategy is devised that further enhances solution quality obtained with the FANT-TMS algorithm.

关键词： computational grids task matching and scheduling ant search techniques Globus toolkit

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On the performance-driven load distribution for heterogeneous computational grids

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JOURNAL OF COMPUTER AND SYSTEM SCIENCES 2007年第8期73卷 1191-1206页

作者： Lu, Kai Subrata, Riky Zomaya, Albert Y. Univ Sydney Sch Informat Technol Networks & Syst Lab Sydney NSW 2006 Australia

Load balancing has been a key concern for traditional multiprocessor systems. The emergence of computational grids extends this challenge to deal with more serious problems, such as scalability, heterogeneity of computing resources and considerable transfer delay. In this paper, we present a dynamic and decentralized load balancing algorithm for computationally intensive jobs on a heterogeneous distributed computing platform. The time spent by a job in the system is considered as the main issue that needs to be minimized. Our main contributions are: (1) Our algorithm uses site desirability for processing power and transfer delay to guide load assignment and redistribution, (2) Our transfer and location policies are a combination of two specific strategies that are performance driven to minimize execution cost. These two policies are the Instantaneous Distribution Policy (IDP) and the Load Adjustment Policy (LAP), (3) The communication overhead involved in information collection is reduced using mutual information feedback. The simulation results show that our proposed algorithm outperforms conventional approaches over a wide range of system parameters. Crown Copyright (C) 2007 Published by Elsevier Inc. All rights reserved.

关键词： computational grids load balancing distributed computing heterogeneity migration

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System design and implementation of digital-image processing using computational grids

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COMPUTERS & GEOSCIENCES 2005年第5期31卷 619-630页

作者： Shen, ZF Luo, JC Zhou, CH Huang, GY Ma, WF Ming, DP Chinese Acad Sci IGSNRR State Key Lab Resource & Environm Informat Syst LREIS Beijing 100101 Peoples R China Chinese Acad Sci Grad Sch Beijing 100101 Peoples R China China Univ Geosci Beijing 100083 Peoples R China Zhejiang Univ Technol Hangzhou 310014 Peoples R China

As a special type of digital image, remotely sensed images are playing increasingly important roles in our daily lives. Because of the enormous amounts of data involved, and the difficulties of data processing and transfer, an important issue for current computer and geo-science experts is developing internet technology to implement rapid remotely sensed image processing. computational grids are able to solve this problem effectively. These networks of computer workstations enable the sharing of data and resources, and are used by computer experts to solve imbalances of network resources and lopsided usage. In China, computational grids combined with spatial-information-processing technology have formed a new technology: namely, spatial-information grids. In the field of remotely sensed images, spatial-information grids work more effectively for network computing, data processing, resource sharing, task cooperation and so on. This paper focuses mainly on the application of computational grids to digital-image processing. Firstly, we describe the architecture of digital-image processing on the basis of computational grids, its implementation is then discussed in detail with respect to the technology of middleware. The whole network-based intelligent image-processing system is evaluated on the basis of the experimental analysis of remotely sensed image-processing tasks;the results confirm the feasibility of the application of computational grids to digital-image processing. (c) 2005 Elsevier Ltd. All rights reserved.

关键词： computational grids digital-image processing middleware remotely sensed image spatial-information grid

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An auction method for resource allocation in computational grids

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FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE 2010年第2期26卷 228-235页

作者： Izakian, Hesam Abraham, Ajith Ladani, Behrouz Tork MIR Labs Sci Network Innovat & Res Excellence Auburn WA 98071 USA Univ Isfahan Fac Engn Dept Comp Engn Esfahan Iran

A computational grid is composed of a set of resource consumers and resources providers. Usually these entities are independent and making decisions autonomously based on their policies and resource allocation in such systems is a challenging problem. in such systems using market-like techniques for this problem regulates the supply and demand for resources, provides an incentive for providers, and motivates the users to trade-off between deadline, budget, and the required level of quality of service. In this paper, we introduce a continuous double auction method (CDA) for grid resource allocation in which resources are considered as provider agents and users as consumer agents. In our proposed method these entities are allowed to participate in a grid independently and make decisions autonomously. We study this method in terms of economic efficiency and system performance. Experimental results illustrate that the proposed method is efficient in terms of successful execution rates, resource utilization rates and fair profit allocation. (C) 2009 Elsevier B.V. All rights reserved.

关键词： computational grids Resource allocation Auction

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Mapping of hierarchical parallel genetic algorithms for protein folding onto computational grids

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IEICE TRANSACTIONS ON INFORMATION AND SYSTEMS 2006年第2期E89D卷 589-596页

作者： Liu, WG Schmidt, B Nanyang Technol Univ Sch Comp Engn Singapore 639798 Singapore

Genetic algorithms are a general problem-solving technique that has been widely used in computational biology. In this paper, we present a framework to map hierarchical parallel genetic algorithms for protein folding problems onto computational grids. By using this framework, the two level communication parts of hierarchical parallel genetic algorithms are separated. Thus both parts of the algorithm can evolve independently. This permits users to experiment with alternative communication models on different levels conveniently. The underlying programming techniques are based on generic programming, a programming technique suited for the generic representation of abstract concepts. This allows the framework to be built in a generic way at application level and thus provides good extensibility and flexibility. Experiments show that it can lead to significant runtime savings on PC clusters and computational grids.

关键词： protein folding HP lattice models hierarchical parallel genetic algorithms computational grids generic programming

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MODERN APPROACHES TO MODELING USER REQUIREMENTS ON RESOURCE AND TASK ALLOCATION IN HIERARCHICAL computational grids

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INTERNATIONAL JOURNAL OF APPLIED MATHEMATICS AND COMPUTER SCIENCE 2011年第2期21卷 243-257页

作者： Kolodziej, Joanna Xhafa, Fatos Univ Bielsko Biala Dept Math & Comp Sci PL-43309 Bielsko Biala Poland Univ Politecn Cataluna Dept Languages & Informat Syst Barcelona 08034 Spain

Tasks scheduling and resource allocation are among crucial issues in any large scale distributed system, including computational grids (CGs). These issues are commonly investigated using traditional computational models and resolution methods that yield near-optimal scheduling strategies. One drawback of such approaches is that they cannot effectively tackle the complex nature of CGs. On the one hand, such systems account for many administrative domains with their own access policies, user privileges, etc. On the other, CGs have hierarchical nature and therefore any computational model should be able to effectively express the hierarchical architecture in the optimization model. Recently, researchers have been investigating the use of game theory for modeling user requirements regarding task and resource allocation in grid scheduling problems. In this paper we present two general non-cooperative game approaches, namely, the symmetric non-zero sum game and the asymmetric Stackelberg game for modeling grid user behavior defined as user requirements. In our game-theoretic approaches we are able to cast new requirements arising in allocation problems, such as asymmetric users relations, security and reliability restrictions in CGs. For solving the games, we designed and implemented GA-based hybrid schedulers for approximating the equilibrium points for both games. The proposed hybrid resolution methods are experimentally evaluated through the grid simulator under heterogeneity, and large-scale and dynamics conditions. The relative performance of the schedulers is measured in terms of the makespan and flowtime metrics. The experimental analysis showed high efficiency of meta-heuristics in solving the game-based models, especially in the case of an additional cost of secure task scheduling to be paid by the users.

关键词： computational grids scheduling non-cooperative games user behavior security meta-heuristics

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A prototype of distributed molecular visualization on computational grids

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FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE 2004年第5期20卷 727-737页

作者： Zhu, HB Chun, TKY Wang, LZ Cai, WT See, S Nanyang Technol Univ Sch Comp Engn Singapore 639798 Singapore Sun Microsyst Inc Singapore 059567 Singapore

This paper presents a distributed rendering system for visualization of massive molecular data sets on computational grids. It is designed with the ability to animate molecular dynamics (MD) simulation trajectories imported from a simulation engine in a distributed environment. MD simulation and visualization are computationally intensive tasks and computational grids are promising technologies for these applications. The framework of the system is introduced and the grid technologies and the parallel rendering approach are discussed in this paper. (C) 2003 Elsevier B.V. All rights reserved.

关键词： molecular visualization parallel rendering load balance distributed rendering computational grids

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An efficient greedy task scheduling algorithm for heterogeneous inter-dependent tasks on computational grids

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INTERNATIONAL JOURNAL OF GRID AND UTILITY COMPUTING 2020年第5期11卷 587-601页

作者： Srinivas, D. B. Hegde, Sujay N. Rajan, M. A. Krishnappa, H. K. Nitte Meenakshi Inst Technol Dept Informat Sci & Engn Bangalore Karnataka India Nitte Meenakshi Inst Technol Informat Sci & Engn Bangalore Karnataka India TCS Res & Innovat Bangalore Karnataka India RV Coll Engn Dept Comp Sci & Engn Bangalore Karnataka India

Designing a task scheduling algorithm for precedence constrained task graphs is still a challenge due to its complexity (NP-complete). Hence the majority of the research in this area is devoted to designing optimal scheduler based on a plethora of techniques such as heuristic, greedy, genetic, game theory, bio-inspired, machine learning etc. for fully dependent or independent task graphs. Motivated by these works, we propose an efficient greedy task scheduling algorithm for precedence constrained task graphs with varied dependencies (no, partial and fully) on computational grids. Performance of the proposed task scheduling algorithm is compared with respect to Turn Around Time (TAT) and grid utilisation against Hungarian, Partial Precedence Constrained (P_PCS) and AND scheduling algorithms. Simulation results shows that the performance of the proposed scheduling algorithm is on a par with Hungarian, P_PCS and AND scheduling algorithms and the running time of proposed algorithm is better than Hungarian and is on a par with P_PCS algorithm.

关键词： task scheduling computational grids partial dependency turnaround time grid utilisation standard task graphs greedy task scheduling algorithm brute force scheduling algorithm fragmentation random task graph

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