Distributed and Parallel Computing

1. Front Matter

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2. Improving Concurrent Write Scheme in File Server Group

   • Fengjung Liu, Chu-sing Yang

   Pages 1-10

3. A Comparative Performance Study of Distributed Mutual Exclusion Algorithms with a Class of Extended Petri Nets

   • Alexander Kostin, Ljudmila Ilushechkina, Erhan Basri

   Pages 11-22

4. A Practical Comparison of Cluster Operating Systems Implementing Sequential and Transactional Consistency

   • Stefan Frenz, Renaud Lottiaux, Michael Schoettner, Christine Morin, Ralph Goeckelmann, Peter Schulthess

   Pages 23-33

5. Clock Synchronization State Graphs Based on Clock Precision Difference

   • Ying Zhao, Wanlei Zhou, Yingying Zhang, E. J. Lanham, Jiumei Huang

   Pages 34-39

6. A Recursive-Adjustment Co-allocation Scheme in Data Grid Environments

   • Chao-Tung Yang, I-Hsien Yang, Kuan-Ching Li, Ching-Hsien Hsu

   Pages 40-49

7. Reducing the Bandwidth Requirements of P2P Keyword Indexing

   • John Casey, Wanlei Zhou

   Pages 50-59

8. A Deadline and Budget Constrained Scheduling Algorithm for eScience Applications on Data Grids

   • Srikumar Venugopal, Rajkumar Buyya

   Pages 60-72

9. A Survivability Model for Cluster System

   • Khin Mi Mi Aung, Kiejin Park, Jong Sou Park

   Pages 73-82

10. Localization Techniques for Cluster-Based Data Grid

    • Ching-Hsien Hsu, Guan-Hao Lin, Kuan-Ching Li, Chao-Tung Yang

    Pages 83-92

11. GridFTP and Parallel TCP Support in NaradaBrokering

    • Sang Boem Lim, Geoffrey Fox, Ali Kaplan, Shrideep Pallickara, Marlon Pierce

    Pages 93-102

12. 2-Layered Metadata Service Model in Grid Environment

    • Muzhou Xiong, Hai Jin, Song Wu

    Pages 103-111

13. pKSS: An Efficient Keyword Search System in DHT Peer-to-Peer Network

    • Yin Li, Fanyuan Ma, Liang Zhang

    Pages 112-117

14. A Comparative Study at the Logical Level of Centralised and Distributed Recovery in Clusters

    • Andrew Maloney, Andrzej Goscinski

    Pages 118-124

15. Toward Self Discovery for an Autonomic Cluster

    • Eric Dines, Andrzej Goscinski

    Pages 125-131

16. Mining Traces of Large Scale Systems

    • Christophe Cérin, Michel Koskas

    Pages 132-138

17. Setup Algorithm of Web Service Composition

    • YanPing Yang, QingPing Tan, Yong Xiao

    Pages 139-148

18. Self Healing and Self Configuration in a WSRF Grid Environment

    • Michael Messig, Andrzej Goscinski

    Pages 149-158

19. Study on Life Cycle Model of Dynamic Composed Web Services

    • Chen Yanping, Li Zengzhi, Jin Qinxue, Wang Chuang

    Pages 159-164

20. Fault-Tolerant Dynamic Job Scheduling Policy

    • J. H. Abawajy

    Pages 165-173

There are many applications that require parallel and distributed processing to allow complicated engineering, business and research problems to be solved in a reasonable time. Parallel and distributed processing is able to improve company profit, lower costs of design, production, and deployment of new technologies, and create better business environments. The major lesson learned by car and aircraft engineers, drug manufacturers, genome researchers and other specialist is that a computer system is a very powerful tool that is able to help them solving even more complicated problems. That has led computing specialists to new computer system architecture and exploiting parallel computers, clusters of clusters, and distributed systems in the form of grids. There are also institutions that do not have so complicated problems but would like to improve profit, lower costs of design and production by using parallel and distributed processing on clusters. In general to achieve these goals, parallel and distributed processing must become the computing mainstream. This implies a need for new architectures of parallel and distributed systems, new system management facilities, and new application algorithms. This also implies a need for better understanding of grids and clusters, and in particular their operating systems, scheduling algorithms, load balancing, heterogeneity, transparency, application deployment, which is of the most critical importance for their development and taking them by industry and business.

• DJ
• Monitor
• Multithreading
• Performance
• Simulation
• algorithm
• algorithms
• cluster computing
• grid computing
• high performance computing
• load computing
• mobile computing
• network computing
• operating system
• security
• algorithm analysis and problem complexity

• School of Information Technology, Geelong, Deakin University, Australia

  Michael Hobbs

• School of Engineering and Information Technology, Deakin University, Geelong

  Andrzej M. Goscinski

• Deakin University, Melbourne, Australia

  Wanlei Zhou

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