Defending passive worms in unstructured P2P networks based on healthy file dissemination

Propagation of passive worms in unstructured peer-to-peer (P2P) networks can result in significant damages and the loss of network security. This paper obtains the average delay for all peers in the entire transmitting process, and proposes a mathematical model for simulating unstructured P2P networks-based passive worms' propagation taking into account network throughput. According to the file popularity which follows the Zipf distribution, we propose a new healthy file dissemination-based defense strategy. Some parameters related to the propagation of passive worms are studied based on the proposed model. Finally, the simulation results verify the effectiveness of our model, which can provide an important guideline in the control of passive worms in unstructured P2P networks.     

区分服务网络中SCTP协议的改进

针对双窗口算法难以判断包丢弃类型的问题,提出一种新的包丢弃类型判断方法,对SCTP协议的确认块进行扩展,从确认块中获取包丢弃类型信息。在NS2上进行仿真实验,实验结果表明,改进后的SCTP协议在吞吐率方面有显著提高。     

密集型无线传感器网络中功率可调节的跨层网络协议

针对无线传感器网络中节点密集的情况,提出了一个功率可调节的跨层网络策略.节点使用不同的发射功率,且使节点有事先规定数量的邻居节点,其中邻居节点数即为节点度.这样,既保证了网络的连通性,又能有效地降低节点间的竞争冲突.将网络中的节点按照层次划分,选择最小传输功率的上层节点作为父亲节点来构造路由树,计算出节点的候选父亲节点集,在父亲节点失效的情况下,选择候选集中的节点传输来解决.实验结果表明,通过这样的策略,可以提高网络的吞吐量,提高数据传输的速率.     

Using new scheduling heuristics based on resource consumption information for increasing throughput on rule‐based spam filtering systems

The large increase of spam deliveries since the first half of 2013 entailed hard to solve troubles in spam filters. In order to adequately fight spam, the throughput of spam filtering platforms should be necessarily increased. In this context, and taking into consideration the widespread utilization of rule‐based filtering frameworks in the spam filtering domain, this work proposes three novel scheduling strategies for optimizing the time needed to classify new incoming e‐mails through an intelligent management of computational resources depending on the Central Processing Unit (CPU) usage and Input/Output (I/O) delays. In order to demonstrate the suitability of our approaches, we include in our experiments a comparative study in contrast to other successful heuristics previously published in the scientific literature. Results achieved demonstrated that one of our alternative heuristics allows time savings of up to 10% in message filtering, while keeping the same classification accuracy. Copyright © 2015 John Wiley & Sons, Ltd.     

基于多频段传感器辅助认知无线电网络的高能效传感器调度算法

在传感器协助认知无线电网络中,传统的高能效传感器调度问题只考虑了一个频段。多频段的传感器调度问题有许多新的研究领域。建立了一种多频段传感器调度问题的模型,提出了一种用于提高认知网络通信容量的基于遗传算法的高能效调度算法。模型考虑了传感器切换频段的能量消耗。在问题模型中,认知基站基于提高能效的目标为每个频段分配一组传感器进行协作感知。基于遗传算法的高能效调度算法通过优化传感器的调度使认知网络达到最大的通信容量,从而达到高能效的目标。仿真结果表明,本文的算法可以比贪心算法以及其他算法取得更高的网络通信容量。     

TimeLapseAnalyzer: multi-target analysis for live-cell imaging and time-lapse microscopy

The direct observation of cells over time using time-lapse microscopy can provide deep insights into many important biological processes. Reliable analyses of motility, proliferation, invasive potential or mortality of cells are essential to many studies involving live cell imaging and can aid in biomarker discovery and diagnostic decisions. Given the vast amount of image- and time-series data produced by modern microscopes, automated analysis is a key feature to capitalize the potential of time-lapse imaging devices. To provide fast and reproducible analyses of multiple aspects of cell behaviour, we developed TimeLapseAnalyzer. Apart from general purpose image enhancements and segmentation procedures, this extensible, self-contained, modular cross-platform package provides dedicated modalities for fast and reliable analysis of multi-target cell tracking, scratch wound healing analysis, cell counting and tube formation analysis in high throughput screening of live-cell experiments. TimeLapseAnalyzer is freely available (MATLAB, Open Source) at http://www.informatik.uni-ulm.de/ni/mitarbeiter/HKestler/tla.     

卫星链路上的SR协议性能分析

选择重传ARQ协议兼顾了停等ARQ协议可靠性高、退后N ARQ协议传输能力强、应用广泛的优势.传统的选择重传ARQ协议模型没有考虑窗口大小对协议性能的影响,导致选择重传ARQ协议模型分析能力不足.为此,通过对选择重传ARQ协议的运行进行分析,建立了与选择重传ARQ协议运行一致的数学模型,并通过仿真验证了所建模型的合理性...     

基于星地通信系统的变速率通信质量控制方法

为有效地提高星地通信系统的通信质量,提出了一种改变信息传输速率的方法VCTRM。该方法根据当前星地信道状况自适应地改变调制方式和码元传输速率,克服了采用变调制方式传输时在低信噪比时不能满足系统误比特率的缺陷,同时又解决了采用变码元传输速率在高信噪比时不能提高系统吞吐量的问题。通过Matlab对变调制方式、变码率及VCTRM三种传输方式进行了仿真,结果表明,VCTRM在不同信道状况下均能满足系统对误比特率(BER)的要求,且获得的系统吞吐量明显高于其他方法。     

Towards More Complete Models of TCP Latency and Throughput

Recently, several researchers have developed equations for modeling TCP behaviors, such as the expected throughput or latency, based on Markov chains derived from TCP with additional simplifying assumptions. In this paper, we suggest new directions for Markov chain analyses of TCP. Our first contribution is to closely examine not just the expectation but the entire cumulative distribution function of transfer times under various models. Particularly for short or medium transfers, the distribution is likely to be more useful than the expectation in terms of measuring end-user satisfaction. We find that the shapes of TCP cumulative distribution functions are remarkably robust to small changes in the model. Our results suggest that simplifying Markov analyses can be extended to yield approximations for the entire distribution as well as for the expectation.Our second contribution is to consider correction procedures to enhance these models. A correction procedure is a rule of thumb that allows equations from one model to be used in other situations. As an example, several analyses use a Drop-Tail loss model. We determine correction procedures for the deviation between this model and other natural loss models based on simulations. The existence of a simple correction procedure in this instance suggests that the high-level behavior of TCP is robust against changes in the loss model.     

Clustering of high throughput gene expression data

High throughput biological data need to be processed, analyzed, and interpreted to address problems in life sciences. Bioinformatics, computational biology, and systems biology deal with biological problems using computational methods. Clustering is one of the methods used to gain insight into biological processes, particularly at the genomics level. Clearly, clustering can be used in many areas of biological data analysis. However, this paper presents a review of the current clustering algorithms designed especially for analyzing gene expression data. It is also intended to introduce one of the main problems in bioinformatics – clustering gene expression data – to the operations research community.