无线传感器网络数据融合路由算法的改进

无线传感器网络能量有限,数据融合能通过合并冗余数据减少传输数据量,但其本身的代价不可忽略。针对该问题,研究数据融合代价和数据传输代价对数据融合路由的影响,在基于决策数据融合技术AFST中,对直传数据采用动态最短路径(DSPT)算法,动态识别网络环境和数据特征变化,以最小的代价调整路由。实验与分析结果表明,当网络结构发生变化时,DSPT算法比SPT算法效率更高、更节能。     

单机调度问题对偶集结迭代算法

具有到达时间约束、目标为最小化加权完工时间之和的单机调度问题是一个典型的NP-hard问题,采用时间下标建模的线性规划松弛方法可提供一个很强的下界,但优化求解存在维数困难.为此,本文提出了一种对偶集结优化策略,通过选择一个衰减集结矩阵集结对偶乘子变量,利用对偶理论获得模型的约束集结,从而降低计算复杂度.同时分析了集结模型的结构特性,并提出一种迭代算法来改善下界.仿真结果表明对偶集结迭代算法能够减少计算时间,同时改善下界性能,适用于大规模调度问题.     

Semantic Interoperability Aggregation in Service Requirements Refinement

Semantic refinement of stakeholders’ requirements is a fundamental issue in requirements engineering. Facing with the on-demand collaboration problem among the heterogeneous, autonomous, and dynamic service resources in the Web, service requirements refinement becomes extremely important, and the key issue in service requirements refinement is semantic interoperability aggregation. A method for creating connecting ontologies driven by requirement sign ontology is proposed. Based on connecting ontologies, a ...     

基于分簇的无线传感器网络数据汇聚传送协议

提出了一种基于分簇的无线传感器网络数据汇聚传送协议CDAT(a cluster-based data aggregation and transmission protocol for wireless sensor networks).CDAT通过均衡能耗的分簇方法及数据预测传送机制,可以有效延长网络的生命期.在簇头选取阶段,利用应用期望的无缝覆盖率与所需簇头数的数学关系,限制节点竞选簇头的初始概率,并联合节点的度和剩余能量来选取簇头;在数据聚合阶段,簇头广播消息,接收所有加入该簇的成员节点,然后对簇内数据进行聚合;在数据传送阶段,利用数据在时间上的相关性,簇头在满足传送精度的要求下,采用预测传送机制将数据传送给基站,通过该机制,网络有效地减少了数据传送的次数.理论分析和模拟实验结果表明,CDAT协议在满足应用期望的服务质量要求下,通过均衡能耗、减少数据传送次数,使得网络生命期优于LEACH(low-energy adaptive clustering hierarchy),PEGASIS(power-efficient gathering in sensor information systems)等协议.     

需求驱动的主动网构实体聚合

从主动服务、需求驱动、自主聚合的角度,提出了需求驱动的主动网构实体聚合模型.在该模型中,主动网构实体形成服务Agent,这些服务Agent主动发现需求并向需求聚集.针对同一需求聚集形成的服务Agent群,通过机制设计、协商、协作最终形成能够满足需求的多Agent系统.为了实现服务Agent对需求的发现和识别,构造了一个功能本体,包括特定领域的功能描述以及功能分解模式.为了实现服务Agent的协作,提出了需求驱动的自动机制设计,并给出了一种基于公平原则的协作模型——重心模型.最后得出由聚合产生的多Agent系统规格表示.     

无线传感器网络中非均匀的最少分簇能耗均衡算法

无线传感器网络中,邻近基站的节点由于承载过多的数据量而过早死亡,从而引发热点问题。采用簇结构可以减轻热点问题,同时降低整个网络的能量消耗,但是簇头昂贵。为此提出了一种非均匀的最少分簇能耗均衡算法（EBUC）,在该算法中,首先建立了一个最少覆盖模型,以优化簇头个数,并在此基础上研究如何通过调整簇内节点个数和融合相关度来均衡能耗,从而有效减轻热点问题。实验结果表明,通过调整簇内节点个数和限制融合相关度的大小,该算法可有效延长网络生存时间。     

应用分子聚集理论计算电解质溶液的渗透系数和活度系数

本文应用分子聚集理论对电解质溶液的渗透平衡机制进行分析,并导出了渗透系数和活度系数方程,本方程计算结果令人满意。     

超临界流体干燥技术在纳米粉体制备中的应用

由于纳米粒子的表面效应，用传统的干燥方法干燥纳米粉体时极可能产生团聚结构。超临界流体干燥技术是制备具有高比表面积、孔体积、较低密度和低热导率的块状气凝胶和纳米粉体的重要途径之一。介绍了超临界流体的性质、超临界流体干燥技术的研究进展、超临界流体干燥的工艺与设备及过程的影响因素，阐述了超临界流体干燥技术在纳米材料制备中的应用，并指出了超临界流体干燥过程的控制技术及注意点，为进一步加强超临界流体干燥技术的理论研究和拓展超临界流体干燥技术的应用领域奠定了基础。     

Privacy preserving secure expansive aggregation with malicious node identification in linear wireless sensor networks

The Wireless Sensor Networks (WSNs) used for the monitoring applications like pipelines carrying oil, water, and gas; perimeter surveillance; border monitoring; and subway tunnel monitoring form linearWSNs. Here, the infrastructure being monitored inherently forms linearity (straight line through the placement of sensor nodes). Therefore, suchWSNs are called linear WSNs. These applications are security critical because the data being communicated can be used for malicious purposes. The contemporary research of WSNs data security cannot fit in directly to linear WSN as only by capturing few nodes, the adversary can disrupt the entire service of linear WSN. Therefore, we propose a data aggregation scheme that takes care of privacy, confidentiality, and integrity of data. In addition, the scheme is resilient against node capture attack and collusion attacks. There are several schemes detecting the malicious nodes. However, the proposed scheme also provides an identification of malicious nodes with lesser key storage requirements. Moreover, we provide an analysis of communication cost regarding the number of messages being communicated. To the best of our knowledge, the proposed data aggregation scheme is the first lightweight scheme that achieves privacy and verification of data, resistance against node capture and collusion attacks, and malicious node identification in linear WSNs.     

DyDAP: A dynamic data aggregation scheme for privacy aware wireless sensor networks

End-to-end data aggregation, without degrading sensing accuracy, is a very relevant issue in wireless sensor networks (WSN) that can prevent network congestion to occur. Moreover, privacy management requires that anonymity and data integrity are preserved in such networks. Unfortunately, no integrated solutions have been proposed so far, able to tackle both issues in a unified and general environment. To bridge this gap, in this paper we present an approach for dynamic secure end-to-end data aggregation with privacy function, named DyDAP. It has been designed starting from a UML model that encompasses the most important building blocks of a privacy-aware WSN, including aggregation policies. Furthermore, it introduces an original aggregation algorithm that, using a discrete-time control loop, is able to dynamically handle in-network data fusion to reduce the communication load. The performance of the proposed scheme has been verified using computer simulations, showing that DyDAP avoids network congestion and therefore improves WSN estimation accuracy while, at the same time, guaranteeing anonymity and data integrity.