A hierarchical peer-to-peer(P2P) model and a data fusion method for network security situation awareness system are proposed to improve the efficiency of distributed security behavior monitoring network. The single point failure of data analysis nodes is avoided by this P2P model, in which a greedy data forwarding method based on node priority and link delay is devised to promote the efficiency of data analysis nodes. And the data fusion method based on repulsive theory-Dumpster/Shafer(PSORT-DS) is used to deal with the challenge of multi-source alarm information. This data fusion method debases the false alarm rate. Compared with improved Dumpster/Shafer(DS) theoretical method based on particle swarm optimization(PSO) and classical DS evidence theoretical method, the proposed model reduces false alarm rate by 3% and 7%,respectively, whereas their detection rate increases by 4% and 16%, respectively.
目的:为提供持续性的按需服务,移动云计算系统必须确保在任何时间和任何地点的可用性。然而当系统规模巨大、关联关系复杂时,如何实现移动云计算系统可用性的快速分析,是本领域一项富有挑战性的工作。本文目的是利用最近提出的流近似(fluid-flow approximation)技术来实现一种能应用于移动云计算系统部署之前的、快速的服务可用性分析方法。创新点:由于移动云计算系统负载水平不同、配置部署不同和随机干扰因素,基于实测的方法很难具有代表性;基于随机模拟的方法会随着模拟规模增大和精度提升而计算时间剧增;基于状态空间的方法在系统规模巨大时将面临严重的状态空间爆炸问题。本文方法通过将状态空间转化为常微分方程组求解,可以避免状态空间爆炸,实现移动云计算系统可用性的快速分析。方法:定义了包括服务反应时间(response time of service)、节点最小感知时间(minimum sensing time of devices)、最少选取节点数量(minimum number of nodes chosen)、动作吞吐量(action throughput)等四个关键指标。通过上述指标来分析移动云计算系统服务可用性的变化,并对系统初始条件、模型核心参数的影响进行讨论。结论:本文提出的服务可用性分析方法能够适用于移动云计算系统完全部署之前,可以用于系统设计阶段的改进。并且与基于随机模拟方法和状态空间方法相比,时耗更低。
Hong-wu LV Jun-yu LIN Hui-qiang WANG Guang-sheng FENG Mo ZHOU
