基于拥塞控制的非结构化P2P网络的路由负载均衡策略

非结构化P2P(unstructured peer-to-peer network)对等网络中的节点资源定位的路由查询是对等网络研究中的一个主要难题,特别是当网络中客户端节点由于其频繁加入、离开导致网络结构动态变化所带来的资源查询难题.提出了一种新的基于拥塞控制的路由查询方法来实现动态网络下的资源查询.该方法分两部分实现:首先是网络资源的分组与节点重连策略.该策略使得具有同等资源的节点相互连接,并周期性地调整节点上的节点连接数量以减少同组资源节点上的负载.通过以上策略,使得网络的拓扑结构自动地从随机网络结构进化到以资源组为单位的聚类网络,从而使得网络中形成网络资源组间的查询负载均衡.另一方面,组内的节点之间的路由负载均衡是通过节点间协同学习实现的.采用协同Q-学习方法,所研究的方法不仅从节点上学习其处理能力、连接数和资源的个数等参数,还将节点的拥塞状态作为协同Q-学习的重要参数,并建立模型.通过这种技术,同一组节点上的资源查询被有目的地引导,以避开那些组内拥塞的节点,从而最终实现资源组内节点之间的查询均衡.仿真实验结果表明,相比常用的random walk资源查找方法,该研究所实现的资源定位方法能够更迅速地实现网络的资源查询.仿真结果还表明,相比random walk方法,所提出的方法在网络高强度查询和网络节点动态加入和退出的情况下进行查询具有更高的鲁棒性和适应性.

Congestion Control Based Load Balancing Routing in Unstructured P2P Networks

Query routing among peers to locate resources is a main issue discussed in Peer-to-Peer (P2P) networks, especially in unstructured P2P networks. This issue becomes even worse when frequent join and departure or failure of client peers happen in the networks. This paper proposes a new churn-resilient protocol to assure alternating routing path to balance query among peers under network churn. The proposed protocol uses two strategies to make queries balancing among inter-and intra-group peers. First a resource grouping and rewiring strategy is provided to periodically cluster peers having same set of resources. This grouping strategy makes locating resources more efficient in the inter-group peers, for it makes the network overlay topology evolve from a random network to a clustered network. The rewiring strategy also alleviates loads among over-loaded peers. Meanwhile, load balancing routing among the intragroup peers is achieved by collaborative Q-learning among peers. The collaborative Q-learning method not only learns from such parameters as processing capacity, number of connections and number of resources in peers, but also learns their state of congestion. Using this technique, queries are guided to avoid forwarding to those congested peers. Thus, query routing forwarding is balanced among intra-group peers. Simulation results show that the desired resources are located more quickly and queries in the whole network are balanced. The results also show that queries by the proposed method exhibit more robustness and adaptability under network attacking, high query workloads, and high network churns than queries by random walk method.