基于复杂网络数据流密度的增量子空间数据挖掘算法

为了提升在复杂网络中对大规模网络数据流进行挖掘时的准确性,提出一种基于复杂网络数据流密度的增量子空间数据挖掘算法,在算法中先对复杂网络的数据流密度进行分析,并根据不同网络的数据流密度来划分社区,进行无向环路遍历来确定数据流的所属社区.再通过增量子空间数据挖掘算法来计算社区网络与数据流的相关度以及数据流所经过的节点与时间的相关系数,从而准确确定目标数据流所处的节点.通过仿真实验结果和数据分析表明,增量子空间数据挖掘算法的数据挖掘精度在节点、社区数较多的情况下仍达到了较高的挖掘精度.     

基于情节规则匹配的数据流预测

提出了一种数据流预测算法Predictor.该算法为每个待匹配的一般形式的情节规则分别使用了一个自动机,通过单遍扫描数据流来同时跟踪这些自动机的状态变迁,以搜索每个规则前件最近的最小且非重叠发生.这样不仅将无界的数据流映射到有限的状态空间,而且避免了对情节规则的过于匹配.另外,算法预测的结果是未来多个情节的发生区间和发生概率.理论分析和实验评估表明,Predictor具有较高的预测效率和预测精度.     

一种新的数据流分形聚类算法

提出了基于分形的数据流聚类算法,利用分形维数的变化程度来度量数据点与聚类的自相似程度,在噪音干扰下能发现反映数据流自然聚集状态的任意形状的聚类。实验证明,FClustream算法是一种高效的数据流聚类算法。     

基于情节规则匹配的数据流预测??

提出了一种数据流预测算法 Predictor.该算法为每个待匹配的一般形式的情节规则分别使用了一个自动机,通过单遍扫描数据流来同时跟踪这些自动机的状态变迁,以搜索每个规则前件最近的最小且非重叠发生.这样不仅将无界的数据流映射到有限的状态空间,而且避免了对情节规则的过于匹配.另外,算法预测的结果是未来多个情节的发生区间和发生概率.理论分析和实验评估表明,Predictor具有较高的预测效率和预测精度.     

数据流中基于事务链表组的频繁闭项集挖掘

挖掘频繁项集是挖掘数据流的基本任务.许多近似算法能够对数据流进行频繁项集的挖掘,但不能有效控制内存资源消耗和挖掘运行时间.为了提高数据流挖掘的效率,通过挖掘数据流中的频繁闭项集来减少挖掘结果项集的数量,并借鉴Relim算法和Manku算法,引入事务链表组作为概要数据结构,提出了一种新的数据流频繁闭项集的挖掘算法.最后通过实验,证明了该算法的有效性.     

低代价的数据流分类算法

现有数据流分类算法大多使用有监督学习,而标记高速数据流上的样本需要很大的代价,因此缺乏实用性.针对以上问题,提出了一种低代价的数据流分类算法2SDC.新算法利用少量已标记类别的样本和大量未标记样本来训练和更新分类模型,并且动态监测数据流上可能发生的概念漂移.真实数据流上的实验表明,2SDC算法不仅具有和当前有监督学习分类算法相当的分类精度,并且能够自适应数据流上的概念漂移.     

基于优先级分类的工业无线网络确定性调度算法

确定性调度技术对于工业无线网络数据的实时性和确定性传输有着重要意义.本文针对工业无线网络数据流本身存在优先级分类属性的情况,基于多信道时分多址接入(TDMA)技术,在分析高优先级数据流对低优先级数据流造成的链路冲突延时和信道竞争延时基础上,对网络进行调度预处理,进而排除参数不合理的网络,并向网络管理者反馈.对于通过预处理的网络,调度算法优先为高优先级数据流的链路分配时隙和信道资源,而对属于同一类优先级的数据流,提出一种基于比例冲突空余时间的调度方案,在满足可调度性条件的前提下,根据各链路的比例冲突空余时间值从小到大依次分配时隙和信道资源.实验结果表明,所提出的调度算法可以取得较高的网络调度成功率.     

基于密度的混合属性数据流聚类算法

数据流聚类分析是当前数据挖掘研究的热点问题,为了克服数据流聚类框架CluStream算法不能处理混合属性数据流的缺陷,提出了基于密度的混合属性数据流聚类算法MCStream.在微聚类中使用面向维度的距离来度量对象之间的相似度,在宏聚类中使用改进的密度聚类算法M-DBSCAN对微簇进行聚类.实验结果表明,MCStream算法能快速有效地处理混合属性数据流聚类问题.     

基于最小竞争窗口的IEEE 802.11区分服务机制及其性能分析

针对无线adhoc网络不能提供数据流优先级区分的问题,本文提出了一种基于802.11DCF退避算法的改进机制,该机制通过设置不同的MAC层最小竞争窗口来实现数据流的区分服务,使发送高优先级数据流(如实时数据流)的节点更容易连接信道,从而使高优先级数据流占有更多带宽资源。数学分析表明,该策略能有效的提高高优先级数据流的传输性能。     

一种基于动态负载均衡的路由算法

传统IGP仅基于最短路径算法来为数据流选择传输通路,对数据流的需求以及网络资源的动态变化未加以考虑,因此不具备均衡网络负载的能力.文中通过分析IGP的局限性,提出基于动态负载均衡的DLB-OSPF路由算法.该算法依据数据流的带宽需求和网络资源的使用状况来进行路由选择,并通过有效手段将数据流更合理地分配到能满足传输需求的链路上.经过示例分析表明,该算法不仅能减少网络拥塞,并且提高了网络资源利用率.     

Evaluation of parallel copying garbage collection on ashared-memory multiprocessor

A parallel copying garbage collection algorithm for symbolic languages executing on shared-memory multiprocessors is proposed. The algorithm is an extension of Baker's sequential algorithm with a novel method of heap allocation to prevent fragmentation and facilitate load distribution during garbage collection. An implementation of the algorithm within a concurrent logic programming system, VPIM, has been evaluated and the results, for a wide selection of benchmarks, are analyzed here. The authors show 1) how much the algorithm reduces the contention for critical sections during garbage collection, 2) how well the load-balancing strategy works and its expected overheads, and 3) the expected speedup achieved by the algorithm     

基于磷虾群算法的无线传感器网络QoS任播路由算法

无线传感器网络多约束QoS任播路由问题是一个NP难题,提出一种基于磷虾群算法的优化策略来解决该路由问题.该算法采用适应度函数和全局最优个体位置更新方法来寻找无线传感器网络中满足多QoS约束的最优任播路由,并加入遗传繁殖机制中的交叉与变异操作以加快优化速度.实验验证了该算法的有效性,实验数据表明相比较粒子群优化算法,该算法在算法效率和可扩展性性能上具有较好的性能;具有较快的收敛速度,从而适用于对路由选择有时延敏感的网络.     

基于权值自适应优化的协作频谱认知算法

提出一种基于权值自适应优化的协作频谱认知算法。根据各协作认知节点的信噪比分配合适的权值向量,反映对检测统计量的贡献大小。基于最小均方误差原则,权值向量可根据实际的各节点信噪比向量进行自适应优化,从而提高认知网络中存在低信噪比节点时的检测性能。仿真结果表明,与传统协作算法相比,该算法无论在节点高信噪比或低信噪比条件下均有更优的检测性能,且收敛速度较快。     

最优常数竞争窗口对WLAN的性能优化研究*

在IEEE 802.11网络中可通过监控信道获得系统中竞争节点数目,而IEEE 802.11DCF协议的设计并没有利用这一参数。因此,首先分析了在IEEE 802.11DCF中使用常数竞争窗口的可行性,提出了DCF/CCW这一改进协议,并对其进行系统吞吐量和接入时延分析。在此基础上,提出根据网络中竞争节点数目来选择最优常数竞争窗口的optimal-DCF/CCW协议。在optimal-DCF/CCW中,各终端首先利用S-DCF算法估算网络中竞争节点的数目,据此选择所应采用的最优常数竞争窗口Wopt的值。仿     

Contention-aware scheduling with task duplication

Finding an efficient schedule for a task graph on several processors is a trade-off between maximising concurrency and minimising interprocessor communication. Task duplication is a technique that has been employed to reduce or avoid interprocessor communication. Certain tasks are duplicated on several processors to produce the data locally and avoid the communication among processors. Most of the algorithms using task duplication have been proposed for the classic scheduling model, which allows concurrent communication and ignores contention for communication resources. It is increasingly recognised that this classic model is unrealistic and does not permit creating accurate and efficient schedules. The recently proposed contention model introduces contention awareness into task scheduling by assigning the edges of the task graph to the links of the communication network. It is intuitive that scheduling under such a model benefits even more from task duplication, yet no such algorithm has been proposed as it is not trivial to duplicate tasks under the contention model. This paper proposes a contention-aware task duplication scheduling algorithm. We investigate the fundamentals for task duplication in the contention model and propose an algorithm that is based on state-of-the-art techniques found in task duplication and contention-aware algorithms. An extensive experimental evaluation demonstrates the significant improvements to the speedup of the produced schedules.     

基于模数的WiMAX网络高负载自适应冲突解决算法

根据现有的部分研究结果发现,IEEE 802.16标准中使用的截断二进制指数后退算法在解决网络冲突时效率很低;并且当网络的负载增多时,该算法的运行性能更差.在此基础上,提出了一种基于模数的自适应冲突解决算法来优化WiMAX网络的冲突解决过程.该算法将所有用户站按照当前时间帧内的传输机会数量分为多个小组,并且要求用户站只能通过特定的传输机会发送请求.与此同时,为了保证整个网络的高性能,本算法要求基站和用户站根据上一轮请求过程中的平均冲突概率和传输机会使用率来调整当前时间帧内的传输机会数量,以及挑选部分用户站参与带宽请求,保证了WiMAX网络在高负载情况下的运行性能.模拟结果表明,本算法在WiMAX网络运行过程中能够较好地解决请求过程中的冲突,对网络性能提高较大.     

竞争窗口线性变化的分级冲突解析算法

设计合理的冲突解析机制可有效提高无线信道利用率。针对二进制指数退避（Binary Exponential Backoff,BEB）算法及其各种改进算法中普遍存在的节点间交叉冲突问题,提出一种竞争窗口线性变化的分级冲突解析算法（Staged Collision Resolution algorithm with Linearly Varying contention window,LV-SCR）。它通过使处于不同退避阶段节点的退避时隙互相隔离,彻底消除了节点间的交叉冲突;为降低信道空闲概率,还采用了一种竞争窗口的线性调节机制。仿真结果表明,与BEB算法相比,在网络吞吐量和数据帧平均接入时延未明显恶化的情况下,LV-SCR算法可使节点间的碰撞次数减少10%至50%以上。     

Dynamic I/O-Aware Scheduling for Batch-Mode Applications on Chip Multiprocessor Systems of Cluster Platforms简

Efficiency of batch processing is becoming increasingly important for many modern commercial service centers, e.g., clusters and cloud computing datacenters. However, periodical resource contentions have become the major performance obstacles for concurrently running applications on mainstream CMP servers. I/O contention is such a kind of obstacle, which may impede both the co-running performance of batch jobs and the system throughput seriously. In this paper, a dynamic I/O-aware scheduling algorithm is proposed to lower the impacts of I/O contention and to enhance the co-running performance in batch processing. We set up our environment on an 8-socket, 64-core server in Dawning Linux Cluster. Fifteen workloads ranging from 8 jobs to 256 jobs are evaluated. Our experimental results show significant improvements on the throughputs of the workloads, which range from 7% to 431%. Meanwhile, noticeable improvements on the slowdown of workloads and the average runtime for each job can be achieved. These results show that a well-tuned dynamic I/O-aware scheduler is beneficial for batch-mode services. It can also enhance the resource utilization via throughput improvement on modern service platforms.     

Response compaction for system-on-a-chip based on advanced convolutional codes

Testing digital circuit accounts for an increasing part of the cost to design, manufacture and service, electric system―― a trend that is projected to continue and accelerate[1]. Test compression is known as a methodology to reduce the test cost. Test c…     

A new fast-path mechanism for mutual exclusion

Summary. Several years ago, Yang and Anderson presented an N-process algorithm for mutual exclusion under read/write atomicity that has time complexity, where “time” is measured by counting remote memory references. In this algorithm, instances of a two-process mutual exclusion algorithm are embedded within a binary arbitration tree. In the two-process algorithm that was used, all busy-waiting is done by “local spinning.” Performance studies presented by Yang and Anderson showed that their N-process algorithm exhibits scalable performance under heavy contention. One drawback of using an arbitration tree, however, is that each process is required to perform remote memory operations even when there is no contention. To remedy this problem, Yang and Anderson presented a variant of their algorithm that includes a “fast-path” mechanism that allows the arbitration tree to be bypassed in the absence of contention. This algorithm has the desirable property that contention-free time complexity is O(1). Unfortunately, the fast-path mechanism that was used caused time complexity under contention to rise to in the worst case. To this day, the problem of designing a read/write mutual exclusion algorithm with O(1) time complexity in the absence of contention and O(logN) time complexity under contention has remained open. In this paper, we close this problem by presenting a fast-path mechanism that achieves these time complexity bounds when used in conjunction with Yang and Anderson's arbitration-tree algorithm. Received: July 1999 / Accepted: July 2000