Journal of Parallel and Distributed Computing
Case-Based Reasoning: Experiences, Lessons and Future Directions
Case-Based Reasoning: Experiences, Lessons and Future Directions
Machine Learning
Incremental Iterative Retrieval and Browsingfor Efficient Conversational CBR Systems
Applied Intelligence
Predicting Queue Times on Space-Sharing Parallel Computers
IPPS '97 Proceedings of the 11th International Symposium on Parallel Processing
A Historical Application Profiler for Use by Parallel Schedulers
IPPS '97 Proceedings of the Job Scheduling Strategies for Parallel Processing
Predicting Application Run Times Using Historical Information
IPPS/SPDP '98 Proceedings of the Workshop on Job Scheduling Strategies for Parallel Processing
Feature Weighting in k-Means Clustering
Machine Learning
Grid Harvest Service: A System for Long-Term, Application-Level Task Scheduling
IPDPS '03 Proceedings of the 17th International Symposium on Parallel and Distributed Processing
Ta3: theory, implementation, and applications of similarity-based retrieval for case-based reasoning
Ta3: theory, implementation, and applications of similarity-based retrieval for case-based reasoning
A Comparison among Grid Scheduling Algorithms for Independent Coarse-Grained Tasks
SAINT-W '04 Proceedings of the 2004 Symposium on Applications and the Internet-Workshops (SAINT 2004 Workshops)
The Grid 2: Blueprint for a New Computing Infrastructure
The Grid 2: Blueprint for a New Computing Infrastructure
Intelligent decision support for protein crystal growth
IBM Systems Journal - Deep computing for the life sciences
Data Mining for Case-Based Reasoning in High-Dimensional Biological Domains
IEEE Transactions on Knowledge and Data Engineering
Data Mining: Concepts and Techniques
Data Mining: Concepts and Techniques
Scheduling functional regression tests for IBM DB2 products
CASCON '05 Proceedings of the 2005 conference of the Centre for Advanced Studies on Collaborative research
Nearest-Neighbor Methods in Learning and Vision: Theory and Practice (Neural Information Processing)
Nearest-Neighbor Methods in Learning and Vision: Theory and Practice (Neural Information Processing)
Efficient Response Time Predictions by Exploiting Application and Resource State Similarities
GRID '05 Proceedings of the 6th IEEE/ACM International Workshop on Grid Computing
Concurrency and Computation: Practice & Experience - Second International Workshop on Emerging Technologies for Next-generation GRID (ETNGRID 2005)
Predict task running time in grid environments based on CPU load predictions
Future Generation Computer Systems
Adaptive Hybrid Model for Long Term Load Prediction in Computational Grid
CCGRID '08 Proceedings of the 2008 Eighth IEEE International Symposium on Cluster Computing and the Grid
The Journal of Supercomputing
Scheduling parallel applications on utility grids: time and cost trade-off management
ACSC '09 Proceedings of the Thirty-Second Australasian Conference on Computer Science - Volume 91
Self-Optimization module for Scheduling using Case-based Reasoning
Applied Soft Computing
| Hi-index | 0.00 |
Grid scheduling performance is significantly affected by the accuracy of job runtime estimation. Since past performance is a good indicator of future trends, we use a case-based reasoning approach to predict the execution time, or run time, based on past experience. We first define the similarity of jobs and similarity of machines, and then determine which job and machine characteristics affect the run time the most by analyzing information from previous runs. We then create a case base to store historical data, and use the TA3 case-based reasoning system to fetch all relevant cases from the case base. We apply this approach to schedule Functional Regression Tests for IBM® DB2® Universal DatabaseTM (DB2 UDB) products. The results show that our approach achieves low runtime estimation errors and substantially improves grid scheduling performance.