基于SIMD PE阵列的图像同态滤波并行算法

为了满足G级像素帧实时处理的要求,提出图像同态滤波的数据并行实现方法.讨论了图像帧和滤波器在SIMD PE阵列中的预置及数据并行的滤波处理实现方法,其处理方式规则性强、并行度高,提高了处理速度.由于SIMD PE阵列具有可裁减性,可以适合不同规模图像帧的处理需求,满足不同的嵌入式应用环境.     

基于随机移动模型的移动sinks无线移动传感器网络性能分析与改进*

引入移动sinks节点是解决网络连通性、能耗平衡、提高网络生命周期和网络容量的有效方法。针对移动sinks节点的移动机制直接与网络性能相关,结合mWSNs体系结构,分析了基于随机移动模型的网络性能,提出了零数据包分片率的随机移动模型。理论分析与仿真结果表明,该模型能够保证数据零分片,提高了网络的时延性能和数据包传输成功率。     

基于GPS实时数据的在线过滤与补遗研究*

为提高GPS数据的有效性与可靠性,使之为实现实时交通流量预测与交通诱导服务,首先基于GPS历史数据,以变异系数极小化为优化目标进行GPS数据过滤模型的优选,并对实时数据缺损提出两种补遗算法;然后给出基于动态GPS实时数据的在线数据过滤与补遗一体化算法;最后结合2008年杭州市GPS历史数据对模型进行应用。结果表明,基于简单算术平均的滤波模型即为GPS数据过滤的最佳模型;基于时间序列缺失数据的快速补遗算法能够很好地满足实时预报要求,实现快速补遗。     

基于请求的多信道多数据项广播调度算法*

通过改进多信道单数据项请求的数据广播调度算法中的两层调度策略,提出了信道分配+QEM的算法;实现了用多信道广播来广播多数据项的请求;通过减少数据访问冲突和信道跳转减少了访问时间。分析证明此方法是可行和有效的。     

基于反向平衡聚合树的无线传感器网络分布式TDMA调度算法*

讨论了已有的TDMA算法在端到端延时上的弊端,在优化时隙数的基础上引入链路的使用顺序与数据流向的相关性,提出了分布式TDMA调度算法,利用反向平衡聚合树的生成过程分配时隙,通过控制链路染色顺序分布式优化延时与避免冲突。仿真结果验证了算法在端到端延迟和通信开销上的性能提升。     

构建本质图的改进算法*

利用图论相关知识,提出了一种构建本质图的改进算法。数值实验表明,对于V-结构较多的非循环有向图,改进算法能相对较快地确定出其本质图,从而能更好地学习贝叶斯网络的等价类。     

Approximate K-Median of Location Streams with Redundancy and Inconsistency

Data streams produced by positioning systems such as Global Positioning System (GPS) or RFID readers can be considered as location streams[12]. Location streams are usually generated in a distributed fashion by a large scale distributed system covering a wide range of areas. Computing on distributed location streams is both practically useful and theoretically challenging. The results of computation could be used to schedule the traffic in a metropolis to avoid traffic jam, dispatch taxis to serve the passengers more quickly and display the current position of goods in supply chain management, etc. Since location streams are usually generated with very high rate in uncertain ways over hostile environments, the collected updates of location are probably redundant and inconsistent in a wide positioning system. To process distributed location streams with redundancy and inconsistency, this paper proposes a novel method based on min-wise hash. With this method, redundant updates of distributed location streams can be effiectively filtered out, while the true location could be derived from inconsistent ones. Consequently, globally uniform samples can be obtained. Based on the uniform samples, an algorithm for computing the approximate k-median of huge number of moving objects is presented in this paper. Furthermore, it is demonstrated that sketch-based methods are not necessarily effiective in processing location streams with redundancy and inconsistency. In addition to theoretical analysis, some extensive experiments are conducted to validate the efficiency and effiectiveness of the proposed approach.     

基于重复热点数据的CF广播结构改进算法*

针对现有广播结构构建中对数据访问概率倾斜度考虑不足的问题,在CF索引树的基础上提出了一种基于数据倾斜度的广播构建算法。该算法充分考虑热点数据的请求,根据数据在CF索引树中所处位置的不同,在一个广播周期内重复广播热点数据及其对应的索引节点,尽量减少移动用户的访问时间。最后通过实验验证了改进后广播结构的有效性。     

Generating Rare Association Rules Using the Minimal Rare Itemsets Family

Rare association rules correspond to rare, or infrequent, itemsets, as opposed to frequent ones that are targeted by conventional pattern miners. Rare rules reflect regularities of local, rather than global, scope that can nevertheless provide valuable insights to an expert, especially in areas such as genetics and medical diagnosis where some specific deviations/illnesses occur only in a small number of cases. The work presented here is motivated by the long-standing open question of efficiently mining strong rare rules, i.e., rules with high confidence and low support. We also propose an efficient solution for finding the set of minimal rare itemsets. This set serves as a basis for generating rare association rules.     

高效节能的能量异构传感器网络数据聚合协议

介绍了一种有效地用于能量异构传感网络的数据采集协议EDGA。EDGA在能量最小化的网内通信和均衡能量负荷等性能上有很好的表现。它通过基于权重选择概率选取的簇头获得了更好的处理能量异构环境的能力,并且利用一种简单但有效的方法解决了簇内的面积覆盖问题。仿真结果表明,该EDGA方法在能量异构无线传感网络的数据采集应用中比LEACH和HEED等方法有明显的优势。