CONTENTS -- PREFACE -- WORKSHOP COMMITTEES -- Grid Scheduling and Filesystem -- An Advance Reservation-Based Computation Resource Manager for Global Scheduling H. Nakada, A. Takefusa, K. Ookubo, T. Kudoh, Y. Tanaka and S. Sekiguchi -- 1. Introduction -- 2. Coallocation and Two-Phase Commit Protocol -- 3. Design of PluS -- 3.1. Generic Design of Batch Queuing Systems -- 3.2. Job Queue -- 3.3. Implementation Methods for Advance Reservation -- 4. Implementation of PluS -- 4.1. Overview of the PluS Reservation Manager -- 4.2. Advance Reservation Policy in PluS -- 4.3. PluS for TORQUE -- 4.4. PluS for Grid Engine -- 5. Evaluation -- 5.1. Evaluation Based on Lines of Codes -- 5.2. Time to Make/Cancel Reservations -- 6. Related Work -- 7. Conclusion -- Acknowledgement -- References -- Reputation Based Job Scheduling in Desktop Grids X. Liu, C. Jiang, C. Wang and Y. Zhao -- 1. Introduction -- 2. Related Works -- 3. Computational Model of Reputation -- 3.1. Assumptions -- 3.2. Computational Model of Reputation -- 3.3. Scheduling Algorithm -- 4. Simulation Results -- 5. Conclusions and Future Work -- Acknowledgments -- References -- A Dataflow Model for .Net-Based Grid Computing Systems C. Jin, R. Buyya, L. Stein and Z. Zhang -- 1. Introduction -- 2. Related Work -- 3. Programming Model -- 3.1. Namespace for Vertices -- 3.2. Dataflow Library API -- 3.2.1. Specifying Execution Module -- 3.2.2. Composing Dataflow Graph -- 3.3. Example -- 4. Architecture and Design -- 4.1. System Overview -- 4.2. The Structure of the Master -- 4.3. The Structure of a Worker -- 4.4. System Interaction -- 4.5. Fault Tolerance -- 4.5.1. Worker Failure -- 4.5.2. Master Failure -- 4.6. Scheduling -- 5. Performance Evaluation -- 5.1. Environment Configuration -- 5.2. Testing Benchmarks -- 5.3. Scalability of Performance -- 5.4. Handling Worker Failure -- 6. Conclusion.

Acknowledgments -- References -- Performance Evaluation of Gfarm Version 1.4 as a Cluster Filesystem Y. Tanimura, Y. Tanaka, S. Sekiguchi and O. Tatebe -- 1. Introduction -- 2. Related Work -- 3. Design of Gfarm Version 1.4 -- 3.1. Overview and Updates -- 3.2. Improvement of Metadata Access -- 3.3. Implementation of UNIX Command Access -- 4. Performance Evaluation -- 4.1. Performance Comparison of UNIX Command Access -- 4.2. Scalability of Metadata Access -- 4.2.1. Basic Performance of the Metadata Server and the Gfarm Agent -- 4.2.2. Scalability of the Metadata Access with Multiple Gfarm Agents -- 4.3. Scalability of the Total I/O Throughput -- 5. Discussion -- 6. Summary -- Acknowledgements -- References -- Grid Workflow -- Temporal Decomposition and Scheduling of Grid Workflow F. Long and H. K. Pung -- 1. Introduction -- 2. RelatedWork -- 3. System Models -- 3.1. Workflow Model -- 3.2. Optimal Objective -- 4. Our Proposal -- 4.1. Maximum Parallel Tasks -- 4.2. Scheduling Algorithm -- 5. Numerical Results -- 5.1. Simulation Scenario -- 6. Conclusion -- References -- A Flow Model of Web Services for the Grid E. P. Sulaiman, Y. S. Ong, M. S. Habibullah and T. Hung -- 1. Introduction -- 2. The Definition of a Flow -- 3. The Concept of Normal Forms -- 4. Comparisons with Other Works -- 5. Conclusion -- Acknowledgments -- References -- A Comparison Study Between Distributed and Centralized Job Workflow Execution Models Y. Feng and W. Cai -- 1. Introduction -- 2. MCCF -- 2.1. MCCF Overview -- 2.2. System Design and Implementation -- 3. Job Workflow Execution on DAGMan and MCCF -- 4. Performance Evaluation -- 4.1. Testbed Configuration -- 4.2. Simulated Job Workflow -- 4.3. Experiment Results -- 5. Conclusion -- References -- Grid Environment and Programming.

Rendering-On-Demand Service Across Heterogeneous Grid Environment B. S. Lee, A. Sourin, C. L. Tien, K. Y. Chan, T. Hung, Q. T. Ho, J. Wei, D. Oh, S. Miller, J. Zhang, A. Chong and K. Levinski -- 1. Introduction -- 2. R-o-D System Overview -- 3. System Description -- 3.1. Rendering Portal -- 3.2. Information and Execution Management -- 3.3. Resource Matching -- 3.4. Pricing Module -- 4. Conclusion -- Acknowledgment -- References -- Collaborative Workspace Over Service-Oriented Grid Z. Shen, H. Shen, C. Miao, Z. Yang, R. Gay and G. Zhao -- 1. Introduction -- 2. Collaborative Workspace -- 2.1. Goal Oriented Process Modeling and Scheduling -- 2.2. Collaboration Workspace and Transparent Collaborative Tools -- 2.3. Trust Management -- 3. Community Portal -- 3.1. Collaborative Workspace Architecture -- 3.2. Implementation -- 3.3. Applications -- 4. Conclusions -- Acknowledgement -- References -- Opal OP: An Extensible Grid-Enabling Wrapping Tool for Legacy Applications K. Ichikawa, S. Date, S. Krishnan, W. Li, K. Nakata, Y. Yonezawa, H. Nakamura and S. Shimojo -- 1. Introduction -- 2. Related Works and Our Focus -- 3. Opal Operation Provider (Opal OP) -- 3.1. Operation Provider -- 3.2. Opal OP and Opal OP Toolkit -- 4. Examples of Applications Using Opal OP -- 4.1. QM/MM Hybrid Simulation System -- 4.2. Protein Structure Similarity-Search System and Drug-Docking Simulation System -- 5. Conclusions -- References -- Security Monitoring Extension for MOGAS S. Takeda, S. Date, J. Zhang, B. S. Lee and S. Shimojo -- 1. Introduction -- 2. Related Works -- 3. Design and Implementation -- 4. Visualization of Security Information -- 5. An Experiment on the PRAGMA Grid Test-bed -- 6. Conclusion and Future Works -- Acknowledgments -- References -- Grid Applications.

Distributed Automatic Frame Generation for Cartoon Animation H. S. Seah, F. Tian, Y. Lu, J. Qiu and Q. Chen -- 1. Introduction -- 2. Stroke Representation with Disk B-Spine Curve and Inbetweening -- 3. Frame Generation Framework -- 3.1. Rendering Algorithm and Complexity -- 3.2. Distributed Rendering Algorithm -- 4. Experimental Results -- 4.1 Sample Output -- 4.1.1 Tukasa Rendering Case -- 4.1.2 Sayuri Readering Case -- 5. Conclusion and Future Work -- References -- Phenotype Genotype Exploration on a Desktop GPU Grid C. Chen, A. Singh, W. Liu, K. W. Müller-Wittig, W. Mitchell and B. Schmidt -- 1. Introduction -- 2. Design of Phenotype Genotype Explorer -- 3. Mapping of Comparative Genomics onto the Hybrid Grid Architecture -- 3.1. Task Parallelization Using BOINC -- 3.2. Data Parallelization on a GPU -- 3.3. CPU Computation -- 4. Performance Evaluation -- 5. Comparative Genomics Study Using Possession of tRNA Substrate -- 6. Conclusion -- References -- Digital Media Portal for the Grid B. S. Lee, M. Tang and J. Zhang -- 1. Introduction -- 2. RelatedWork -- 3. Media Grid Portal Architecture -- 3.1. Meta-Scheduler -- 3.2. Pixie Rendering Application -- 3.3. Other Digital Media Applications -- 4. Performance Optimization and Fault-Tolerance -- 5. Conclusion -- Acknowledgements -- References -- Poster Papers -- Exploring the PC Grid Technology for Research Computation - The NUS Experience C. C. Tan and J. Wang -- 1. Introduction -- 2. PC Grid Computing -- 3. References -- 4. Implementation at NUS -- 5. Comparison with Other Grid Solutions -- 6. Return of Investment -- 7. Case Studies -- 8. A Platform for Sharing and Collaboration -- 9. Conclusion -- References -- Grid Computing for Stochastic Super-Resolution Imaging: Fundamentals and Algorithms J. Tian and K. K. Ma -- 1. Introduction -- 2. Stochastic Super-Resolution Imaging.

2.1. The Mathematical Framework of the SR Problem -- 2.2. Bayesian Inference -- 3. Grid Computing for Stochastic Super-resolution Imaging -- 4. Experimental Results -- 5. Conclusions -- Acknowledgement -- References -- Supporting Large-Scale Collaborative Virtual Environment in Grid L. Zhang, Q. Lin, H. K. Neo, G. Huang, R. Gay and G. Feng -- 1. Introduction -- 2. Grid-Based MACVE Architecture -- 2.1. Grid-Based Mobile Agent Environment -- 2.1.1. Agent Management Service -- 2.1.2. Agent Messaging Service -- 2.1.3. MAE Monitoring Service -- 2.2. Resource Discovery and Monitoring -- 2.3. MACVE Scheduling and Load Balancing -- 3. Implementation and Evaluation -- 4. Conclusions -- References -- Designing an Experimental Gaming Platform for Trading Grid Resources D. Oh, S. F. Cheng, M. Dan and R. Bapna -- 1. Introduction -- 2. Motivation -- 3. Design Science Approach -- 4. Research Contributions -- 5. Market Game Simulation Platform -- 6. Market and Pricing Models -- 7. Conclusion -- References.