以小世界模型为理论基础,以 Region 为基本逻辑管理单位,按用户需求和共享目的组织 Region。提出了基于 Region 的多层结构 Peer-to-Peer 网络模型和构造规则,给出了 Region 的划分策略和数学模型,证明了模型的正确和合理性;对模型中的...以小世界模型为理论基础,以 Region 为基本逻辑管理单位,按用户需求和共享目的组织 Region。提出了基于 Region 的多层结构 Peer-to-Peer 网络模型和构造规则,给出了 Region 的划分策略和数学模型,证明了模型的正确和合理性;对模型中的层和域、中心节点、普通节点和汇聚点进行了明确的定义,给出了节点加入、离开、中心节点选取策略和算法描述;使定位某种服务的工作量和查询范围从网络中的所有结点数降低到 Region 的节点数,有效地防止了恶意请求引发的洪,网络系统开销为常数。模拟分析表明,该模型可有效解决可扩展性、性能与效率不高问题,且网络规模越大,其综合性能的优越性越明显,因此,模型是合理有效的。展开更多
The continuous emerging of peer-to-peer(P2P) applications enriches resource sharing by networks, but it also brings about many challenges to network management. Therefore, P2 P applications monitoring, in particular,P...The continuous emerging of peer-to-peer(P2P) applications enriches resource sharing by networks, but it also brings about many challenges to network management. Therefore, P2 P applications monitoring, in particular,P2 P traffic classification, is becoming increasingly important. In this paper, we propose a novel approach for accurate P2 P traffic classification at a fine-grained level. Our approach relies only on counting some special flows that are appearing frequently and steadily in the traffic generated by specific P2 P applications. In contrast to existing methods, the main contribution of our approach can be summarized as the following two aspects. Firstly, it can achieve a high classification accuracy by exploiting only several generic properties of flows rather than complicated features and sophisticated techniques. Secondly, it can work well even if the classification target is running with other high bandwidth-consuming applications, outperforming most existing host-based approaches, which are incapable of dealing with this situation. We evaluated the performance of our approach on a real-world trace. Experimental results show that P2 P applications can be classified with a true positive rate higher than 97.22% and a false positive rate lower than 2.78%.展开更多
文摘以小世界模型为理论基础,以 Region 为基本逻辑管理单位,按用户需求和共享目的组织 Region。提出了基于 Region 的多层结构 Peer-to-Peer 网络模型和构造规则,给出了 Region 的划分策略和数学模型,证明了模型的正确和合理性;对模型中的层和域、中心节点、普通节点和汇聚点进行了明确的定义,给出了节点加入、离开、中心节点选取策略和算法描述;使定位某种服务的工作量和查询范围从网络中的所有结点数降低到 Region 的节点数,有效地防止了恶意请求引发的洪,网络系统开销为常数。模拟分析表明,该模型可有效解决可扩展性、性能与效率不高问题,且网络规模越大,其综合性能的优越性越明显,因此,模型是合理有效的。
基金supported by the National Natural Science Foundation of China(Nos.61170286 and 61202486)
文摘The continuous emerging of peer-to-peer(P2P) applications enriches resource sharing by networks, but it also brings about many challenges to network management. Therefore, P2 P applications monitoring, in particular,P2 P traffic classification, is becoming increasingly important. In this paper, we propose a novel approach for accurate P2 P traffic classification at a fine-grained level. Our approach relies only on counting some special flows that are appearing frequently and steadily in the traffic generated by specific P2 P applications. In contrast to existing methods, the main contribution of our approach can be summarized as the following two aspects. Firstly, it can achieve a high classification accuracy by exploiting only several generic properties of flows rather than complicated features and sophisticated techniques. Secondly, it can work well even if the classification target is running with other high bandwidth-consuming applications, outperforming most existing host-based approaches, which are incapable of dealing with this situation. We evaluated the performance of our approach on a real-world trace. Experimental results show that P2 P applications can be classified with a true positive rate higher than 97.22% and a false positive rate lower than 2.78%.
