Matchmaking: Distributed Resource Management for High Throughput Computing
HPDC '98 Proceedings of the 7th IEEE International Symposium on High Performance Distributed Computing
Policy Driven Heterogeneous Resource Co-Allocation with Gangmatching
HPDC '03 Proceedings of the 12th IEEE International Symposium on High Performance Distributed Computing
Matchmaking frameworks for distributed resource management
Matchmaking frameworks for distributed resource management
Grid Computing: A Practical Guide to Technology and Applications
Grid Computing: A Practical Guide to Technology and Applications
Efficient Matchmaking and Directory Services
WI '03 Proceedings of the 2003 IEEE/WIC International Conference on Web Intelligence
Fuzzy Matchmaking for Web Services
AINA '05 Proceedings of the 19th International Conference on Advanced Information Networking and Applications - Volume 2
Flexible and Efficient Matchmaking and Ranking in Service Directories
ICWS '05 Proceedings of the IEEE International Conference on Web Services
A knowledge representation model for matchmaking systems in e-marketplaces
Proceedings of the 11th International Conference on Electronic Commerce
Federated management of the Future Internet: status and challenges
International Journal of Network Management
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One of the essential operations in a distributed computing is resource discovery. A resource discovery service provides mechanisms to identify the set of resources capable of satisfying the requirements of a job from a large collection of resources. The matchmaking framework provides a reasonable solution to resource management in a distributed environment; it is composed of four important components as classified advertisement (classad), matchmaker protocol, matchmaking algorithm and claiming protocols. Most of the time required to find a resource depends on the performance of the matchmaking algorithms. A distributed environment introduces a large set of heterogeneous resources which is always changing. The matchmaking algorithms should incorporate with this highly changing environment. In this paper we proposed a fast and efficient searching method for matchmaking algorithms which also deals with resource heterogeneity. The proposed approach reduces the searching time to a linear function from a cubic function proposed by R. Raman, M. Livny, and M. Solomon. We discuss briefly the working principles of the method and compare the experimental results of the proposed matchmaking algorithm with those of the existing algorithm.