Development of an enhanced check pointing technique in grid computing using programmer level controls
Table Of Contents
Chapter ONE
1.1 Introduction 1.2 Background of Study
1.3 Problem Statement
1.4 Objective of Study
1.5 Limitation of Study
1.6 Scope of Study
1.7 Significance of Study
1.8 Structure of the Research
1.9 Definition of Terms
Chapter TWO
2.1 Overview of Grid Computing 2.2 Evolution of Checkpointing Techniques
2.3 Types of Checkpointing in Grid Computing
2.4 Challenges in Existing Checkpointing Techniques
2.5 Theoretical Frameworks in Checkpointing
2.6 State-of-the-Art Technologies in Grid Checkpointing
2.7 Best Practices in Grid Checkpointing
2.8 Comparative Analysis of Checkpointing Techniques
2.9 Future Trends in Grid Checkpointing
2.10 Summary of Literature Review
Chapter THREE
3.1 Research Design 3.2 Population and Sampling Techniques
3.3 Data Collection Methods
3.4 Data Analysis Procedures
3.5 Research Instrumentation
3.6 Ethical Considerations
3.7 Reliability and Validity of Research
3.8 Limitations of Research Methodology
Chapter FOUR
4.1 Data Analysis and Interpretation 4.2 Demographic Analysis of Participants
4.3 Checkpointing Performance Metrics
4.4 Comparison with Existing Techniques
4.5 Impact of Programmer Level Controls
4.6 Case Studies and Use Cases
4.7 Discussion on Findings
4.8 Recommendations for Implementation
Chapter FIVE
5.1 Conclusion and Summary 5.2 Summary of Findings
5.3 Contributions to Knowledge
5.4 Implications for Future Research
5.5 Practical Applications of Enhanced Checkpointing
Project Abstract
Grid computing is a collection of computer resources from multiple locations assembled to provide computational services, storage, data or application services. Grid computing users gain access to computing resources with little or no knowledge of where those resources are located or what the underlying technologies, hardware, operating system, and so on are. Reliability and performance are among the key challenges to deal with in grid computing environments. Accordingly, grid scheduling algorithms have been proposed to reduce the likelihood of resource failure and to reduce the overhead of recovering from resource failure. Checkpointing is one of the faulttolerance techniques when resources fail. This technique reduces the work lost due to resource faults but can introduce significant runtime overhead. This research provided an enhanced checkpointing technique that extends a recent research and aims at lowering the runtime overhead of checkpoints. The results of the simulation using GridSim showed that keeping the number of resources constant and varying the number of gridlets, improvements of up to 9%, 11%, and 11% on throughput, makespan and turnaround time, respectively, were achieved while varying the number of resources and keeping the number of gridlets constant, improvements of up to 8%, 11%, and 9% on throughput, makespan and turnaround time, respectively, were achieved. These results indicate the potential usefulness of our research contribution to applications in practical grid computing environments.
Project Overview
INTRODUCTION
1.1 Background of the Study
1.2 Motivation
The ability to checkpoint a running application and restart it later can provide many useful benefits like fault recovery, advanced resource sharing, dynamic load balancing and improved service availability. A fault-tolerant service is essential to satisfy QoS requirements in grid computing. However, excessive checkpointing results in performance degradation. Thus there is the need to improve the performance by reducing the number of times that checkpointing is invoked.
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