Fault Tolerant Operating Systems
ACM Computing Surveys (CSUR)
Reliability Issues in Computing System Design
ACM Computing Surveys (CSUR)
High Performance Cluster Computing: Architectures and Systems
High Performance Cluster Computing: Architectures and Systems
Four Multi-agent Architectures for Intelligent Network Load Management
MATA '02 Proceedings of the 4th International Workshop on Mobile Agents for Telecommunication Applications
A Multi-Agent Negotiation Algorithm for Load Balancing in CORBA-Based Environment
IDEAL '00 Proceedings of the Second International Conference on Intelligent Data Engineering and Automated Learning, Data Mining, Financial Engineering, and Intelligent Agents
AOM: An Agent Oriented Middleware Based on Java
ICSC '99 Proceedings of the 5th International Computer Science Conference on Internet Applications
Customized dynamic load balancing for a network of workstations
HPDC '96 Proceedings of the 5th IEEE International Symposium on High Performance Distributed Computing
AAMAS '03 Proceedings of the second international joint conference on Autonomous agents and multiagent systems
Scientific Programming - Distributed Computing and Applications
Messor: load-balancing through a swarm of autonomous agents
AP2PC'02 Proceedings of the 1st international conference on Agents and peer-to-peer computing
A distributed collaborative design framework for multidisciplinary design optimization
CSCWD'05 Proceedings of the 9th international conference on Computer Supported Cooperative Work in Design II
Load balancing using mobile agent and a novel algorithm for updating load information partially
ICCNMC'05 Proceedings of the Third international conference on Networking and Mobile Computing
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Resource management is one of the key research issues for multi-agent systems. Aside from increasing the system reliability, the load balancer is also able to schedule incoming tasks to the available machines. This paper introduces a load balancing strategy algorithm which can optimize the utilization of several different resources (CPU, memory, etc.) by migrating mobile agents and their tasks to the best alternative nodes. In the course of the research, a few scenarios were simulated and analyzed. In the paper the scenarios along with initial experiment results are presented.