Identifying heavy hitters in high-speed network monitoring

Identifying heavy hitters in a network traffic stream is important for a variety of network applications ranging from traffic engineering to anomaly detection such as detection of denial-of-service attacks. Existing methods generally examine newly arriving items in the stream, perform a small number of operations using a small amount of memory, and still provide guarantees on the identifying accuracy. In high-speed network monitoring, the update speed per item is extremely critical. However, so far as we kn...     

Weighted random sampling with a reservoir

In this work, a new algorithm for drawing a weighted random sample of size m from a population of n weighted items, where m?n, is presented. The algorithm can generate a weighted random sample in one-pass over unknown populations.     

Mining frequent itemsets in data streams using the weighted sliding window model

In recent years, data stream mining has become an important research topic. With the emergence of new applications, the data we process are not again static, but the continuous dynamic data stream. Examples include network traffic analysis, Web click stream mining, network intrusion detection, and on-line transaction analysis. In this paper, we propose a new framework for data stream mining, called the weighted sliding window model. The proposed model allows the user to specify the number of windows for mining, the size of a window, and the weight for each window. Thus users can specify a higher weight to a more significant data section, which will make the mining result closer to user’s requirements. Based on the weighted sliding window model, we propose a single pass algorithm, called WSW, to efficiently discover all the frequent itemsets from data streams. By analyzing data characteristics, an improved algorithm, called WSW-Imp, is developed to further reduce the time of deciding whether a candidate itemset is frequent or not. Empirical results show that WSW-Imp outperforms WSW under the weighted sliding window model.     

变频调速系统中过程监控模块的设计

变频调速系统的安全性往往依赖于变频器,虽然变频器具有一定的保护功能,但主要保护的是变频器本身,很难实现对不确定的马达和未知的负载实现过程监控。设计了一个可嵌入在系统中的监控模块,采用粗糙集理论,建立预警报警决策表,初步解决了变频调速系统的过程监控的问题,实际应用结果表明,该方法有一定的可行性和有效性。