高效节能的无线传感器网络数据收集协议*

现有的数据收集协议的性能不是很好,为此提出了一种基于数据收集树的数据收集协议。它通过减少数据收集树中的节点深度和中间节点数来减少制约系统生命期的节点传输数据给基站的能量消耗和节点空闲侦听的能量消耗。仿真实验表明,该协议能将系统生命期延长36%左右。     

一种移动终端辅助的传感器网络数据收集协议

提出了一种利用具有传感器通信接口的移动终端设备（如手机、手提电脑、个人数字助理等）进行辅助数据获取的传感器网络数据收集协议。网络中固定汇聚节点与移动终端共存,全部传感器节点都维护到固定汇聚节点的路由,移动终端进入网络后定期向其附近小范围内的传感器节点扩散自己的存在信息,传感器节点向距自己跳数最小的汇聚节点或移动终端发送或转发数据包,移动终端和传感器节点之间通过应答和重传的机制来保证数据的可靠传输。仿真研究证明,该协议在延长网络生存时间的同时可以获得较高的数据传输成功率和较短的数据传输延迟,而且可靠性、灵活性、可扩展性较强。     

Application-aware integration of data collection and power management in wireless sensor networks

Sensors are typically deployed to gather data about the physical world and its artifacts for a variety of purposes that range from environment monitoring, control, to data analysis. Since sensors are resource constrained, often sensor data is collected into sensor databases that reside at (more powerful) servers. A natural tradeoff exists between resources (bandwidth, energy) consumed and the quality of data collected at the server. Blindly transmitting sensor updates at a fixed periodicity to the server results in a suboptimal solution due to the differences in stability of sensor values and due to the varying application needs that impose different quality requirements across sensors. In order to adapt to these variations while at the same time optimizing the energy consumption of sensors, this paper proposes three different models and corresponding data collection protocols. We analyze all three models with a Markov state machine formulation, and either derive closed forms for the operation point of the data collection application or suggest algorithms for estimating this operating point to achieve a minimal energy consumption. We observe that the operating point depends on environmental characteristics and application quality requirements, which the proposed algorithms aim to accommodate. Our experimental results show significant energy savings compared to the naive approach to data collection.     

传感器网络中基于移动sink最优穿越路径的高效数据收集算法

移动sink数据收集研究主要集中在轨迹固定的移动策略。为此,建立了移动sink穿越路径可控条件下的数据收集模型,并提出一种最优路径穿越的移动sink数据收集算法(OTP-TS)。算法利用局部Voronoi网格将连续路径问题离散化,以收集数据量、系统能耗为衡量指标,结合禁忌搜索算法,实现系统数据量最大化和网络能耗最小化穿越。理论分析和实验结果表明,该算法很好地解决了移动sink在可控移动轨迹情况中数据收集的最优路径穿越问题。     

工业生产实时数据采集及管理数据库模型设计

提出了中小型生产企业在企业信息化过程中的生产数据实时采集、安全存储、有效管理的重要性,并给出生产数据的自动统计、分析、处理及为企业的生产经营提供决策的手段。     

传感器网络中基于树的分布式数据收集算法

数据收集是传感器网络的根本任务,由于传感器网络节点能量有限、易失效等因素,如何设计一个低能耗的、可扩展性强的数据收集机制是传感器网络的一个关键问题。为此,提出一种基于树的分布式数据收集算法,其基本思想是：基站发送广播信息,根据节点到基站的最小跳数构造出网络的层次结构,由层次结构生成以基站为树根的树型传输网络,并基于该网络模型收集数据。理论分析和仿真实验表明该算法具有较低的复杂度,能有效地延长网络的生命周期,并具有良好的扩展性和容错性。     

无线传感网中生命最大化的泛在数据收集协议

提出一个网络生命周期最大化的泛在数据收集协议MULAC。MULAC以用户所在当前位置为圆心, 半径为r的区域内选择一个节点v。以v为根构造一棵最大化生命周期树T。网络中的节点可以通过T传送数据给v, 数据采集者可以通过v接收到网络中的全部数据。当数据采集者移动到其他位置, T将根据用户新的位置改变根节点, 并且以最小的能量耗费调整树结构, 从而延长全网的寿命。在收集数据过程中保证无线传感器网络生命周期最大化是一个NP完全问题, MULAC能够近似最优地解决此问题。仿真实验和理论分析表明, MULAC能有效延长网络生命周期。     

Topology control for delay-constraint data collection in wireless sensor networks

Data collection is one of the most important operations in wireless sensor networks. Many practical applications require the real-time data transmission, such as monitoring, tracking, etc. In this paper, we import and define the topology control problem for delay-constraint data collection (TDDC), and then formalize this problem into an integer programming problem. As NP-Hardness of this problem, we present a load-aware power-increased topology control algorithm (namely LPTC) to heuristically solve the problem. The theoretical analysis shows that this algorithm can reach O(1)-approximation ratio for the linear networks. And we also analyze the impact of the delay-constraint on the worst-case for the planar networks. Moreover, this paper designs two localized algorithms, called as SDEL and DDEL, based on the area division for TDDC problem. The experimental results show that LPTC algorithm can save at least 17% power consumptions compared with HBH algorithm in many situations.     

A wireless sensor networks MAC protocol for real-time applications

Wireless sensor networks (WSN) are designed for data gathering and processing, with particular requirements: low hardware complexity, low energy consumption, special traffic pattern support, scalability, and in some cases, real-time operation. In this paper we present the virtual TDMA for sensors (VTS) MAC protocol, which intends to support the previous features, focusing particularly on real-time operation. VTS adaptively creates a TDMA arrangement with a number of timeslots equal to the actual number of nodes in range. Thus, VTS achieves an optimal throughput performance compared to TDMA protocols with fixed size of frame. The frame is set up and maintained by a distributed procedure, which allows sensors to asynchronously join and leave the frame. In addition, duty cycle is increased or decreased in order to keep latency constant below a given deadline. Therefore, a major advantage of VTS is that it guarantees a bounded latency, which allows soft real-time applications.

Optimizing data collection path in sensor networks with mobile elements

Exploiting mobile elements (MEs) to accomplish data collection in wireless sensor networks (WSNs) can improve the energy efficiency of sensor nodes, and prolong network lifetime. However, it will lead to large data collection latency for the network, which is unacceptable for data-critical applications. In this paper, we address this problem by minimizing the traveling length of MEs. Our methods mainly consist of two steps: we first construct a virtual grid network and select the minimal stop point set (SPS) from it; then, we make optimal scheduling for the MEs based on the SPS in order to minimize their traveling length. Different implementations of genetic algorithm (GA) are used to solve the problem. Our methods are evaluated by extensive simulations. The results show that these methods can greatly reduce the traveling length of MEs, and decrease the data collection latency.     

时延受限能耗均衡的无线传感网数据采集树

为延长网络寿命,缩短网络汇聚时延,提出了一个时延受限,能耗均衡的传感网数据采集树构建方法。该方法以节点的剩余能量和节点间距离为参数构建权值函数,使用Dijkstra算法计算一个最小加权能耗生成树。在此基础上,沿最小加权路径,对生成树进行局部调整,从而在满足时延要求的同时,均衡网络能耗。实验表明,该方法延长了网络平均生存期,达到了均衡网络能耗的目的。     

串行通信在实时数据采集中的应用

本文讨论了VB 6.0 MSComm控件在数据采集中的应用。利用VB6.0 ActiveX中的MSComm通信控件,实现了Windows下单台PC机与多台计量仪表的串行通信,达到了以较低的硬件成本对多路数据自动采集、计算和分析的目的。     

Energy efficient approximate self-adaptive data collection in wireless sensor networks

To extend the lifetime of wireless sensor networks, reducing and balancing energy consumptions are main concerns in data collection due to the power constrains of the sensor nodes. Unfortunately, the existing data collection schemesmainly focus on energy saving but overlook balancing the energy consumption of the sensor nodes. In addition, most of them assume that each sensor has a global knowledge about the network topology. However, in many real applications, such a global knowledge is not desired due to the dynamic features of the wireless sensor network. In this paper, we propose an approximate self-adaptive data collection technique (ASA), to approximately collect data in a distributed wireless sensor network. ASA investigates the spatial correlations between sensors to provide an energyefficient and balanced route to the sink, while each sensor does not know any global knowledge on the network.We also show that ASA is robust to failures. Our experimental results demonstrate that ASA can provide significant communication (and hence energy) savings and equal energy consumption of the sensor nodes.     

基于时间序列预测模型的簇型数据收集机制

由于温度、光照等物理属性的时空连续性,密集部署的传感器网络中节点感知的数据往往具有很高的时空相关性。这种数据相关性产生的数据冗余会带来通信负担,也会缩短网络的生命周期。提出一种基于预测模型的簇型数据收集机制 (CDCF),探索数据相关性,减少无线传感器网络的通信量。该机制包括一种基于曲线拟合最小二乘法的时间序列预测模型和简单有效的误差控制方法。在数据收集过程中,簇型结构考虑到了数据间的空间相关性,时间序列预测模型探讨数据的时间相关性。实验仿真表明,在较为稳定的网络环境中,相对于收集原始数据,该机制只需10%~20%的通信量就可完成整个网络的数据收集任务;数据误差控制方法可以确保基站恢复数据的误差控制在用户定义的误差范围之内。     

两层传感网隐私保护的不完全数据Skyline查询协议

感知节点感知数据易受外界环境影响,使得不完全数据广泛存在于无线传感器网络中,且感知数据面临严重的隐私威胁。针对两层传感器网络不完全数据查询过程中存在的隐私泄露问题,提出一种基于置换和桶技术的两层传感器网络隐私保护的不完全数据Skyline查询协议（PPIS）。为了实现对不完全数据的Skyline查询,PPIS将缺失属性值置换为数据域的上界值,并将不完全数据映射到桶中;为了保证数据隐私性,PPIS首先将桶区间转化为前缀编码,然后将前缀编码加载到Bloom过滤器中,保证存储节点在无需数据和桶区间明文的前提下执行查询处理;为了保证查询结果的完整性,PPIS采用Merkle哈希树构造完整性验证编码,实现对查询结果的完整性验证。理论分析和仿真实验验证了PPIS的安全性和有效性,与现有隐私保护Skyline查询协议SMQ和SSQ相比,PPIS通信能耗节省了70%以上。     

Support for real-time decision making in mobile financial applications

Mobile users making real-time decisions based on current information need confidence that their context has been taken into consideration in producing the system’s recommendations. This chapter reviews current use of mobile technologies for context-aware real-time decision support. Specifically, it describes a framework for assessing the impact of mobility in decision making. The framework uses dynamic context model of data quality to represent uncertainties in the mobile decision-making environment. This framework can be used for developing visual interactive displays for communicating to the user relevant changes in data quality when working in mobile environments. As an illustration, this chapter proposes a real-time decision support procedure for on-the-spot assistance to the mobile consumer when choosing the best payment option to efficiently manage their budget. The proposed procedure is based on multi-attribute decision analysis, scenario reasoning, and a quality of data framework. The feasibility of the approach is demonstrated with a mobile decision-support system prototype implementation. This article is part of the “Handbook on Decision Support Systems” edited by Frada Burstein and Clyde W. Holsapple (2008) Springer.     

Analysis of smartphone user mobility traces for opportunistic data collection in wireless sensor networks

The increasing ubiquity of smartphones coupled with the mobility of their users will allow the use of smartphones to enhance the operation of wireless sensor networks. In addition to accessing data from a wireless sensor network for personal use, and the generation of data through participatory sensing, we propose the use of smartphones to collect data from sensor nodes opportunistically. For this to be feasible, the mobility patterns of smartphone users must support opportunistic use. We analyze the dataset from the Mobile Data Challenge by Nokia, and we identify the significant patterns, including strong spatial and temporal localities. These patterns should be exploited when designing protocols and algorithms, and their existence supports the proposal for opportunistic data collection through smartphones.     

A distributed energy-efficient clustering protocol for wireless sensor networks

Minimizing energy dissipation and maximizing network lifetime are among the central concerns when designing applications and protocols for sensor networks. Clustering has been proven to be energy-efficient in sensor networks since data routing and relaying are only operated by cluster heads. Besides, cluster heads can process, filter and aggregate data sent by cluster members, thus reducing network load and alleviating the bandwidth. In this paper, we propose a novel distributed clustering algorithm where cluster heads are elected following a three-way message exchange between each sensor and its neighbors. Sensor’s eligibility to be elected cluster head is based on its residual energy and its degree. Our protocol has a message exchange complexity of O(1) and a worst-case convergence time complexity of O(N). Simulations show that our algorithm outperforms EESH, one of the most recently published distributed clustering algorithms, in terms of network lifetime and ratio of elected cluster heads.     

基于预测模型的传感器网络近似数据采集算法

基于模型的数据采集技术可以有效抑制不必要的数据传输,节省能量开销,已经在传感器网络中得到广泛应用。对传统基于模型的数据采集进行了改进,提出基于卡尔曼滤波器的近似数据采样算法ADCA。ADCA可以在一定误差范围内有效获取数据。空间相近的节点被组织成簇,簇头和成员分别建立卡尔曼滤波模型,并保存对方的镜像模型。簇头节点可以为成员节点产生近似的数据,所以用户查询可以通过簇头来回答。实验表明ADCA具有较好的性能。