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Load Balancing of Distributed Systems Based on Multiple Ant Colonies Optimization | Science Publications

机译:多蚁群优化的分布式系统负载均衡科学出版物

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> Problem statement: Ant Colony Optimization (ACO) provides a meta-heuristic optimization tool and collective intelligence model to several applications such as routing and load balancing. A lot of work found in the literature on using ACO in load balancing. However, as far as our knowledge, there was no work relating load balancing in distributed systems with ACO. Approach: In this study, a proposed ACO algorithm for load balancing in distributed systems will be presented. This algorithm is fully distributed in which information is dynamically updated at each ant movement. Multiple colonies paradigm will be adopted such that each node will send a colored colony throughout the network. Results: In this study, colored ant colonies are used to prevent ants of the same nest from following the same route and hence enforcing them to be distributed all over the nodes in the system and each ant acts like a mobile agent that carries newly updated load balancing information to the next visited node. Conclusion: Finally, the performance of the proposed ACO algorithm is compared with the work-stealing approach for load balancing in distributed systems.
机译: > 问题陈述:蚁群优化(ACO)为多种应用程序(如路由和负载平衡)提供了一种元启发式优化工具和集体智能模型。关于在负载平衡中使用ACO的文献中有很多工作。但是,据我们所知,尚无与ACO的分布式系统中的负载平衡相关的工作。 方法:在这项研究中,将提出一种用于分布式系统中负载平衡的ACO算法。该算法是完全分布的,其中信息在每次蚂蚁运动时都会动态更新。将采用多个菌落范例,以便每个节点将在整个网络中发送彩色菌落。 结果:在这项研究中,有色蚂蚁菌落用于防止相同巢穴的蚂蚁遵循相同的路线,从而迫使它们分布在系统中的所有节点上,并且每个蚂蚁的行为都类似于将新更新的负载平衡信息携带到下一个访问的节点的移动代理。 结论:最后,将所提出的ACO算法的性能与分布式系统中负载均衡的工作窃取方法进行了比较。

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