Dynamic load balancing for distributed memory multiprocessors
Journal of Parallel and Distributed Computing
UNIX network programming
Coordination languages and their significance
Communications of the ACM
Strategies for Dynamic Load Balancing on Highly Parallel Computers
IEEE Transactions on Parallel and Distributed Systems
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When traditional IDS (Intrusion Detection System) is used to detect and analyze the great flow data transfer in high-speed network, it usually causes the computation bottleneck. This paper presents a new Mobile Agent Distributed IDS (MADIDS) system basing on the mobile agents. This system is specifically designed to process the great flow data transfer in high-speed network. In MADIDS, the agents that are set at each node process the data transfer by distributed computation. Meanwhile by using the reconfiguration quality of the mobile agents, the load balance of distributed computation can be dynamically implemented to gain the high-performance computing ability. This ability makes the processing of great flow data transfer possible. MADIDS can effectively solve the detection and analysis performance bottleneck caused by the great flow data transfer in high-speed network. And the performance of IDS is enhanced. In this paper, we construct the infrastructure and theoretical analysis model of MADIDS. The deficiencies of MADIDS and future research works are also indicated.