基于智能体的多资源负载均衡新策略，提升复杂系统架构性能
A novel strategy for multi-resource load balancing in agent-based systems
- 利用智能体的社会行为与自适应能力实现负载均衡
- 支持智能体自我评估，动态优化资源配置
- 适用于复杂企业级系统架构设计，适合系统架构师参考
本文提出一种可在基于智能体的系统中应用的多资源负载均衡策略，有助于系统设计者优化复杂企业架构的结构。该方法利用智能体的社会行为及其自适应能力，为特定配置确定最优设置。所有机制均旨在实现智能体的自我评估。所提出的智能体系统已成功实现，并展示了实验结果。
原文摘要 · Abstract (English)
The paper presents a multi-resource load balancing strategy which can be utilised within an agent-based system. This approach can assist system designers in their attempts to optimise the structure for complex enterprise architectures. In this system, the social behaviour of the agent and its adaptation abilities are applied to determine an optimal setup for a given configuration. All the methods have been developed to allow the agent's self-assessment. The proposed agent system has been implemented and the experiment results are presented here.
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