A multi-agent system based on specific-profile for efficient distributed computing

Authors:
Youn-Gyou Kook;Woon-Yong Kim;Young-Keun Choi
Affiliations:
Dept. of Computing Science, Kwangwoon University, Seoul, Korea;Dept. of Computing Science, Kwangwoon University, Seoul, Korea;Dept. of Computing Science, Kwangwoon University, Seoul, Korea
Venue:
ICAI'05/MCBC'05/AMTA'05/MCBE'05 Proceedings of the 6th WSEAS international conference on Automation & information, and 6th WSEAS international conference on mathematics and computers in biology and chemistry, and 6th WSEAS international conference on acoustics and music: theory and applications, and 6th WSEAS international conference on Mathematics and computers in business and economics
Year:
2005

Citing 6
Cited 0

Java Web Services: For Java Programmers

Java Web Services: For Java Programmers
Optimizing the Dissemination of Mobile Agents for Distributed Information Filtering

IEEE Concurrency
Fault-Tolerant Mobile Agent Execution

IEEE Transactions on Computers
A Performance Analysis Framework for Mobile-Agent Systems

Revised Papers from the International Workshop on Infrastructure for Multi-Agent Systems: Infrastructure for Agents, Multi-Agent Systems, and Scalable Multi-Agent Systems
Agent Migration Between Incompatible Agent Platforms

ICDCS '00 Proceedings of the The 20th International Conference on Distributed Computing Systems ( ICDCS 2000)
A Mobile Agent Framework for Follow-Me Applications in Ubiquitous Computing Environment

ICDCSW '01 Proceedings of the 21st International Conference on Distributed Computing Systems

Quantified Score

Hi-index	0.00

Visualization

Abstract

We propose the multi agent system based on profiling specifics for the distributed system, SPMaS. The job scheduling and the path finding on the distributed computing are important factors for the reliable system and running time reduction. The factors which affect the entire performance of scheduling and path finding are node's capability (CPU, memory), network state (speed, traffic frequency) and usage patterns (average available resource, connection lasting time, job request frequency, job execution frequency and error frequency). SPMaS analyses the characters of node by using agent and composes node history. The node history helps system allocate the best-suitable job for each node during job scheduling. In addition, managing groups based on the node history makes effective handling for the load balance and defect of transmission.