Super-proximity routing in structured peer-to-peer overlay networks

Peer-to-Peer systems are emerging as one of the most popular Intemet applications. Structured Peer-to-Peer overlay networks use identifier based routing algorithms to allow robustness, load balancing, and distributed lookup needed in this environment. However, identifier based routing that is independent of Internet topology tends to be of low efficiency. Aimed at improving the routing efficiency, the super-proximity routing algorithms presented in this paper combine Internet topology and over|ay routing table in choosing the next hop. Experimental results showed that the algorithms greatly improve the efficiency of Peer-to-Peer routing.     

结构化P2P网络中关键字搜索算法

为了解决分布式哈希表(DHT)不支持模糊匹配和查找延迟长等问题,提出使用改进的超立方体互连圈结构建立逻辑的关键字搜索层.对于给定的文档和描述该文档的关键字集合,使用反向文档索引(IDF)技术选择文档的重要关键字,并映射到环标号,将描述文档的关键字集映射到立方体标号,有效地提取了关键字对于文档的重要性信息,并通过构造生成树来实施搜索操作.实验结果表明,与使用超立方体结构作为关键字搜索层的算法相比,该算法在查询关键字较少时,具有更好的性能.     

一种结构化对等网络中的偏向路由算法

由于路由效率高,贪婪式路由算法成为目前基于DHT的结构化P2P协议的首选路由算法,但贪婪式路由算法仅考虑路由效率而忽视了系统中节点负载平衡问题．文章提出一种适用于无状态结构化P2P协议中的偏向路由算法,与传统的路由算法不同的是,偏向路由算法将根据节点间负载变化和路由效率两个方面来动态选择下一跳节点．实验结果表明：与贪婪...     

结构化P2P中基于蜜罐的蠕虫发现策略研究

为解决结构化P2P网络中蠕虫发现时间长、准确率低的问题,提出了基于蜜罐技术的蠕虫发现策略.通过在P2P节点的文件索引哈希表中设置代表蜜罐节点地址信息的(K,V)对,将P2P蠕虫引入蜜罐中,并通过设置过滤名单提高P2P蠕虫的发现准确率.通过在模拟环境中的实验和对比,证明了该发现策略能够在P2P蠕虫爆发后的第一轮感染过程中将蠕虫引入蜜罐并准确的识别出P2P蠕虫.为结构化对等网络的蠕虫发现提供了新的方法.     

基于DHT的结构化P2P覆盖网络算法分析

目前P2P覆盖网络应用十分广连,关于覆盖网的研究已成为当前网络技术研究领域的热点。关于覆盖网络相应的路由算法在不断发展和完善,先后提出了集中目录式的算法和分布式查找算法。针对基于DHT的覆盖网络算法进行介绍和分析,并指出该领城的最近研究趋势。     

基于DHT的结构化P2P覆盖网络算法分析

目前P2P覆盖网络应用十分广泛,关于覆盖网的研究已成为当前网络技术研究领域的热点.关于覆盖网络相应的路由算法在不断发展和完善,先后提出了集中目录式的算法和分布式查找算法.针对基于DHT的覆盖网络算法进行介绍和分析,并指出该领域的最近研究趋势.     

Non-random segregation of sister chromosomes in Escherichia coli

It has long been known that the 5' to 3' polarity of DNA synthesis results in both a leading and lagging strand at all replication forks. Until now, however, there has been no evidence that leading or lagging strands are spatially organized in any way within a cell. Here we show that chromosome segregation in Escherichia coli is not random but is driven in a manner that results in the leading and lagging strands being addressed to particular cellular destinations. These destinations are consistent with the known patterns of chromosome segregation. Our work demonstrates a new level of organization relating to the replication and segregation of the E. coli chromosome.     

Co-mimics have a mutualistic relationship despite unequal defences

In the first clear mathematical treatment of natural selection, Müller proposed that a shared warning signal (mimicry) would benefit defended prey species by sharing out the per capita mortality incurred during predator education. Although mimicry is a mainstay of adaptationist thinking, there has been repeated debate on whether there is a mutualistic or a parasitic relationship between unequally defended co-mimic species. Here we show that the relationship between unequally defended species is mutualistic. We examined this in a 'novel world' of artificial prey with wild predators (great tit, Parus major). We kept the abundance of a highly defended prey ('model') constant and increased the density of a moderately defended prey ('defended mimic') of either perfect or imperfect mimetic resemblance to the model. Both model and defended mimic showed a net benefit from a density-dependent decrease in their per capita mortality. Even when the effect of dilution through density was controlled for, defended mimics did not induce additional attacks on the model, but we found selection for accurate signal mimicry. In comparison, the addition of fully edible (batesian) mimics did increase additional attacks on the model, but as a result of dilution this resulted in no overall increase in per capita mortality. By ignoring the effects of density, current theories may have overestimated the parasitic costs imposed by less defended mimics on highly defended models.     

固定和增长区域上一类互惠模型的扩散动力学

在生态中,互惠是一类常见的种群关系,由于某种群的数量增加对另一种群的变化有积极的作用,进而使得物种不断地繁衍进化.种群数量的变化受多种因素影响,尤其是栖息地大小的变化.为了研究区域的增长对互惠种群的影响,围绕互惠扩散模型,在固定区域和增长区域上通过数学分析和数值模拟了解其空间动力学.结果表明互惠的两种群之间互利、共生,在合适的环境中不会灭绝,并且区域的增长有利于互惠种群的生存发展.     

Lack of heterogeneity in antihapten antibodies of a phylogenetically primitive shark

Individual mammals have the capacity to express at least one million distinct antigen binding specificities, implying a high degree of structural heterogeneity in the variable heavy and light chain (VH and VL) portions of the antibody molecules. Studies of higher vertebrate species suggest that this heterogeneity is created both through a sizeable repertoire of germ-line VH and VL genes and through random rearrangements of V and joining genes. Additional somatic mechanisms probably also contribute to the ultimate heterogeneity; one-third of murine plasmacytomas producing lambda 1 immunoglobulin carry a somatically mutated Ig1-V gene. The relative contributions of these various mechanisms to the overall imunoglobulin variability are difficult to evaluate. The production of different antibodies to a defined determinant in different individuals of an inbred mouse strain [for example, (3-iodo-4-hydroxy-5-nitrophenyl) acetyl (NIP) in CBA mice] suggests the involvement of somatic mutations or rearrangement but does not rule out the possibility that each individual CBA mouse expresses only a small random fraction from a large germ-line repertoire of V genes determining different anti-NIP binding sites. The opposite finding, that different individuals produce nearly identical antibodies to a defined determinant, would suggest the presence and expression of a limited number of germ-line genes without somatic alterations. Data presented here suggest that primitive sharks (Heterodontus fransisci) produce such antibodies to the hapten furyloxazolone.     

一类互惠模型共存解的稳定性

目的研究了一类互惠模型共存解的稳定性。方法以λ为分歧参数,运用极值原理、局部分歧理论、线性算子的扰动理论和分歧解的稳定性理论进行研究。结果得到了系统共存解稳定的条件。结论此互惠模型在适当条件下共存解是稳定的。     

一类互惠模型的分歧与稳定性

以生长率a,b作为分歧参数,运用分歧理论讨论了一类互惠模型发自半平凡解的分歧,同时判定了这些分歧解的稳定性.     

一类互惠模型解的爆破性质

运用上下解方法讨论了一类三种群互惠扩散模型整体解存在的条件、解的爆破性及爆破时间估计．     

基于非随机初始种群遗传算法的分类规则挖掘

数据挖掘中分类问题一直是数据挖掘领域中研究的热点问题,先后提出了各种分类算法;其中遗传算法被认为是一种高效的分类算法.但是,传统的GA存在着易于陷入局部最优,致使得到的分类规则概括性不强的问题.提出了一种基于非随机初始种群的遗传算法分类规则挖掘算法.算法利用均匀种群方法生成非随机的初始种群,并通过均匀算子确保连续迭代过程中种群的多样性,从而达到防止GA早熟的目的.采用两个标准的公共领域的数据集验证了算法的有效性.实验结果表明,该算法能消除遗传算法在分类挖掘任务中收敛于局部最优的局限性,且能快速挖掘出易于理解的分类规则,提高对知识的理解力.     

面向对象方法与结构化方法

在归纳面向对象方法与结构化方法的内在一致性和主要区别基础上,对运用面向对象方法提出了5点建议,期望既坚持结构化方法已有成功经验,又不断追求面向对象方法的新发展,达到在软件开发中更好地运用面向对象方法的目的。     

多种群互惠型Volterra生态系统全局渐近稳定的充要条件

讨论了多种群互惠型Ｖｏｌｔｅｒｒａ生态系统ｘ＝ｘ（ｂ＋Ａｘ）＾ｒ存在正平衡点全局渐近稳定的充要条件，得到结论：１）若矩阵Ａ稳定，则系统有唯一正平衡点；２）若矩阵Ａ稳定，则系统的正平衡点全局渐近稳定。