分布式信息融合的物联网事件检测方法

事件检测是物联网感知技术的一项重要应用。由于感知节点资源受限,事件检测准确率与节点能量有效性较难平衡。提出了一种新的物联网事件检测方法,基于分布式无线传感器网络,采用特征选择与人工智能学习算法,对感知数据进行局部与全局的二级信息融合,在降低节点功耗的同时提升了检测的准确率。进行要地周界入侵事件检测实验,结果表明,该方法相比传统的事件检测方法更加有效。

一种基于RFID和WSN的分布式节点定位方法

射频识别(RFID)技术和无线传感网(WSN)技术在当今移动定位、目标识别与跟踪方面具有广泛的应用。针对这两种技术在定位领域的应用局限,如感应距离、识别效率、组网能力等方面限制,提出一种网络节点定位方法,将具有标识能力的射频识别(RFID)技术与具有通信、传感能力的无线传感网(WSN)技术相结合。首先,利用射频标签的感应范围获取准确的参考区域;然后,采用基于指纹的非测距定位方法在选定参考区域估算移动节点实时位置。仿真结果表示,在分布式网络定位应用中,所提出的算法有效提升了移动节点的定位精度,同时节约了网络资源,提升了定位效率。

低压配电网用电异常行为快速检测技术分析

本文提出一种低压配电网用电异常行为的快速检测技术,采用分布式光纤传感网和Φ-OTDR实时监测电流、电压及温度等参数。通过小波包变换与类神经网络融合进行特征提取,并利用GBDT模型构建高效异常检测系统,能准确识别电力盗用、过负荷等问题。同时设计了基于边缘计算的响应系统实现对异常行为的智能化监控与及时处理。实验验证该技术具有高可靠性和精度,为低压配电网安全运行提供有效解决方案,具备良好的产品化应用潜力。

分布式光纤拉曼光子温度传感器的研究进展

研究和讨论了分布式光纤传感器系统的测温方法和原理,介绍了国内外的研究概况、存在的问题和当前的研究趋势,探索了新一代光纤非线性效应的光纤传感机理。提出了光纤非线性散射效应的融合原理,研究和设计了一系列基于光纤拉曼与布里渊散射的分布式光纤传感器,采用光纤色散与损耗光谱的自校正方法提高了系统的可靠性、空间分辨率和测温精度;采用脉冲编码调制光源,提高了系统的信噪比和测温精度。

快速协方差交叉融合算法及应用

针对分布式传感网络系统中存在互协方差未知的情形,融合系数的科学设计对于融合性能至关重要.本文以各节点估计方差矩阵逆的迹的倒数作为计算融合系数的中间变量,设计了一种序贯快速协方差交叉融合算法,可以显著减少各个融合节点的计算量,能够保证各融合节点融合结果相同.在给定系统的误差方差上界约束与优化指标前提下,该融合算法结合粒子群优化算法,能够给出对分布式系统中各个节点的传感器精度要求.工程实践中,可为传感器的选型提供理论依据.最后,给出了一个分布式网络传感器精度选型的算例及快速协方差交叉融合算法在雷达网中的应用实例.

Reliability Analysis of Sensor Networks

To Integrate the capacity of sensing, communication, computing, and actuating, one of the compelling technological advances of these years has been the appearance of distributed wireless sensor network (DSN) for information gathering tasks. In order to save the energy, multi-hop routing between the sensor nodes and the sink node is necessary because of limited resource. In addition, the unpredictable conditional factors make the sensor nodes unreliable. In this paper, the reliability of routing designed for sensor network and some dependability issues of DSN, such as MTTF (mean time to failure) and the probability of connectivity between the sensor nodes and the sink node are analyzed. Unfortunately, we could not obtain the accurate result for the arbitrary network topology, which is #P-hard problem. And the reliability analysis of restricted topologies clustering-based is given. The method proposed in this paper will show us a constructive idea about how to place energy-constrained sensor nodes in the network efficiently from the prospective of reliability.

Optimal distributed resource allocation in a wireless sensor network for control systems

Wireless technology is applied increasingly in networked control systems. A new form of wireless network called wireless sensor network can bring control systems some advantages, such as flexibility and feasibility of network deployment at low costs, while it also raises some new challenges. First, the communication resources shared by all the control loops are limited. Second, the wireless and multi-hop character of sensor network makes the resources scheduling more difficult. Thus, how to effectively allocate the limited communication resources for those control loops is an important problem. In this paper, this problem is formulated as an optimal sampling frequency assignment problem, where the objective function is to maximize the utility of control systems, subject to channel capacity constraints. Then an iterative distributed algorithm based on local buffer information is proposed. Finally, the simulation results show that the proposed algorithm can effectively allocate the limited communication resource in a distributed way. It can achieve the optimal quality of the control system and adapt to the network load changes.

OPTIMAL DISTRIBUTED FUSION ALGORITHM WITH ONE-STEP OUT-OF-SEQUENCE ESTIMATES

The transmission modes of multi-hop and broadcasting for Wireless Sensor Networks(WSN)often make random and unknown transmission delays appear,so multisensor data fusion based ondelayed systems attracts intense attention from lots of researchers.The existing achievements for thedelayed fusion all focus on Out-Of-Sequence Measurements(OOSM)problem which has many dis-advantages such as high communication cost,low computational efficiency,huge computational com-plexity and storage requirement,bad real-time performance and so on.In order to overcome theseproblems occurred in the OOSM fusion,the Out-Of-Sequence Estimates(OOSE)are considered tosolve the delayed fusion for the first time.Different from OOSM which belongs to the centralized fusion,the OOSE scheme transmits local estimates from local sensors to the central processor and is thus thedistributed fusion;thereby,the OOSE fusion can not only avoid the problems suffered in the OOSMfusion but also make the design of fusion algorithm highly simple and easy.Accordingly,a novel optimallinear recursive prediction weighted fusion method is proposed for one-step OOSE problem in this letter.As a tradeoff,its fusion accuracy is slightly lower than that of the OOSM method because the currentOOSM fusion is a smooth estimate and OOSE gets a prediction estimate.But,the smooth result of theOOSE problem also has good fusion accuracy.Performance analysis and computer simulation show thatthe total performance of the proposed one-step OOSE fusion algorithm is better than the current one-step OOSM fusion in the practical tracking systems.

Distributed Plume Source Localization Using Hierarchical Sensor Networks

A hierarchical wireless sensor networks(WSN) was proposed to estimate the plume source location.Such WSN can be of tremendous help to emergency personnel trying to protect people from terrorist attacks or responding to an accident.The entire surveillant field is divided into several small sub-regions.In each sub-region,the localization algorithm based on the improved particle filter(IPF) was performed to estimate the location.Some improved methods such as weighted centroid,residual resampling were introduced to the IPF algorithm to increase the localization performance.This distributed estimation method eliminates many drawbacks inherent with the traditional centralized optimization method.Simulation results show that localization algorithm is efficient for estimating the plume source location.

Distributed Connectivity Restoration Strategy for Movable Sensor Networks

Failure of one or multiple critical nodes may partition wireless sensor networks into disjoint segments, and thus brings negative effect on the applications. We propose DCRS, a Distributed Connectivity Restoration Strategy to tolerate the failure of one critical node. Because of the energy restriction of sensor nodes, the energy overhead of the recovery process should be minimized to extend the lifetime of the network. To achieve it, we first design a novel algorithm to identify 2-critical nodes only relying on the positional information of 1-hop neighbors and some 2-hop neighbors, and then we present the criteria to select an appropriate backup for each critical node. Finally, we improve the cascaded node movement algorithm by determining whether a node can move to another non-adjacent node directly or not to reduce the number of nodes moved. The effectiveness of DCRS is validated through extensive simulation experiments.

Energy-Efficient Distributed Lifetime Optimizing Scheme for Wireless Sensor Networks

In this paper, a sensing model for the coverage analysis of wireless sensor networks is provided. Using this model and Monte Carlo method, the ratio of private range to sensing range required to obtain the desired coverage can be derived considering the scale of deployment area and the number of sensor nodes. Base on the coverage analysis, an energy-efficient distributed node scheduling scheme is proposed to prolong the network lifetime while maintaining the desired sensing coverage, which does not need the geographic or neighbor information of nodes. The proposed scheme can also handle uneven distribution, and it is robust against node failures. Theoretical and simulation results demonstrate its efficiency and usefulness.

Distributed Key Management Scheme against Sybil Attacks of Wireless Sensor Network

Wireless sensor network nodes （WSN nodes） have limited computing power, storage ca-pacity, conmmunication capabilities and energy and WSN nodes are easy to be paralyzed by Sybil at- tack. In order to prevent Sybil attacks, a new key distribution scheme for wireless sensor networks is presented. In this scheme, the key inforrmtion and node ID are associated, and then the attacker is dif-ficult to forge identity ID and the key inforrmtion corresponding to ID can not be forged. This scheme can use low-power to resist the Syhil attack and give full play to the resource advantages of the cluster head. The computing, storage and corrn^ni- cation is rminly undertaken by the cluster head o- verhead to achieve the lowest energy consumption and resist against nodes capture attack. Theoretical analysis and experimental results show that com- pared with the traditional scheme presented in Ref. [14], the capture rate of general nodes of cluster re-duces 40%, and the capture rate of cluster heads reduces 50%. So the scheme presented in this pa-per can improve resilience against nodes capture at- tack and reduce node power consumption.

Aggregation in Intersection Region for Distributed Heterogeneous Mobile Sensor Networks

This paper presents two aggregation strategies in convex intersection region for the distributed mobile sensor network(MSN) with heterogeneous dynamics. First, the authors analyze individual local perception model and dynamics model, set the intersection of all the local perceptions as the region of interest(ROI). The MSN consists of sensors with first-order dynamics and second-order dynamics. Then, the authors design a control strategy to ensure that individuals aggregate at a point in the ROI relying on their local perceptions and the locations of neighbors within their communication scope. The authors describe this situation of aggregation as rendezvous. In addition, the authors introduce artificial potential field to make sensors deploy dispersedly in a bounded range near the ROI,which the authors call dispersed deployment. Finally, the authors prove the stability of the proposed strategies and validate the theoretical results by simulations. This research is applied for the cooperative deployment and data collection of mobile platforms with different dynamics under the condition of inaccurate perception.

Design and Implementation of a Wearable Body Area Sensor Network for Distributed FES System

A wearable body area sensor network(WBASN) was designed and implemented to monitor movement information of stroke patients in real time. The sensor system was combined with a previously developed distributed functional electrical stimulation(d FES) system, which is a promising technology for motor rehabilitation of stroke patients. Movement information could be useful in outcome assessment of rehabilitation, or for closed-loop adaptive stimulation during rehabilitation. In addition,a short-latency, low-power communication protocol was developed to meet the clinical requirements of energy efficiency and high rate of data feed-through. The prototype of the WBASN was tested in preliminary human experiments. Experimental results demonstrate the feasibility of the proposed wearable body area sensor network in monitoring arm movements on healthy subjects.