一种利用分布式遗传算法的P2P负载均衡方法

A Load Balancing Approach for P2P Systems on the Basis of Distributed Genetic Algorithm

摘要: 采用Gossip协议,利用节点之间周期性的拓扑维护消息交换负载信息,提出了一种基于分布式遗传算法的负载均衡算法。在适应度的评估中,结合网络的物理拓扑,以最小化虚拟节点迁移开销,并利用P2P节点并行处理种群,以克服遗传算法计算量过大的缺点。实验结果表明,该算法在求解速度与质量上都取得了较大的改善。

Abstract: Currently, in the highly dynamic and heterogeneous P2P systems, load balancing, as one of the core issues of performance improvement, faces increasingly serious challenges.Based on Gossip protocol, we use topology maintenance messages among nodes to exchange load information periodically, present a load balancing solution based on the distributed genetic algorithm. This solution evaluates the fitness with the physical network topology to minimize the cost of virtual nodes migration. Sub\|populations are processed in parallel by P2P nodes to overcome the disadvantages of excessive computation of the genetic algorithm. The experimental results show that our approach has made great improvements in the speed and the quality of solution.