UAV-assisted data gathering in wireless sensor networks

An unmanned aerial vehicle (UAV) is a promising carriage for data gathering in wireless sensor networks since it has sufficient as well as efficient resources both in terms of time and energy due to its direct communication between the UAV and sensor nodes. On the other hand, to realize the data gathering system with UAV in wireless sensor networks, there are still some challenging issues remain such that the highly affected problem by the speed of UAVs and network density, also the heavy conflicts if a lot of sensor nodes concurrently send its own data to the UAV. To solve those problems, we propose a new data gathering algorithm, leveraging both the UAV and mobile agents (MAs) to autonomously collect and process data in wireless sensor networks. Specifically, the UAV dispatches MAs to the network and every MA is responsible for collecting and processing the data from sensor nodes in an area of the network by traveling around that area. The UAV gets desired information via MAs with aggregated sensory data. In this paper, we design a itinerary of MA migration with considering the network density. Simulation results demonstrate that our proposed method is time- and energy-efficient for any density of the network.     

Policy Management for Secure Data Access Control in Vehicular Networks

The state-of-the-art research in vehicular network security does not address the need for low latency message access control in vehicular applications with tight connection time and message delay requirements. In existing security solutions, the major limitation is that no trust establishment mechanisms that adapt to rapidly changing scenarios and highly mobile environments (mainly because of key management delay, processing overhead, and changing communication peers). To address this issue, we present a policy management framework for secure data access control in vehicular networks. Our solution address two interrelated research areas to achieve efficiency and scalability for data access control and policy management in highly dynamic vehicular networks. The main contributions are in two-fold: (a) efficient key management and group-based policy enforcement using attribute-based cryptography; and (b) dynamic security policy management framework and methodology to manage credentials based on role, time, location and other situation dependent attributes. Our solution utilizes efficient attribute-based cryptography algorithm to achieve unprecedented speedups in message processing time to meet the real-time requirement. To demonstrate the effectiveness of our proposed solution, a systematic and comprehensive evaluation is produced to valid our proposed solution.     

一种基于中继节点的线性无线传感器网络数据收集MAC协议

MAC协议对于无线传感器网络的能效是至关重要的。针对线性无线传感器网络设计了一个基于中继节点的数据收集MAC协议SLDMAC。源节点向汇聚节点发送数据时,引入节点能耗因子和剩余能量均衡因子两个参数,通过优化这两个参数,选择合适的中间节点进行中继,从而提升网络的性能。实验结果表明:与DMAC协议相比,SLDMAC协议提升了网络的能效和生存周期。     

基于混合计算模型的分布式传感器网络数据收集*

首先分析了传感器网络中两种计算模型的特点;然后针对装甲集群状态监控的实际需求,提出了基于无线传感器网络的装备状态监控系统的基本结构.分析了用于前端数据收集和传输的两层传感器网络的不同特点,结合client/server和移动agent模型的优点,提出基于混合计算模型的分布式传感器网络数据收集机制,在相对独立的车载监测网络中基于client/server模型建立数据收集机制,在车载监测网络之间基于移动agent模型建立数据收集机制.     

Data gathering algorithms in sensor networks using energy metrics

Gathering sensed information in an energy efficient manner is critical to operating the sensor network for a long period of time. The LEACH protocol presented by Heinzelman et al. (2000) is an elegant solution where clusters are formed to fuse data before transmitting to the base station. In this paper, we present an improved scheme, called PEGASIS (power-efficient gathering in sensor information systems), which is a near-optimal chain-based protocol that minimizes energy. In PEGASIS, each node communicates only with a close neighbor and takes turns transmitting to the base station, thus reducing the amount of energy spent per round. Simulation results show that PEGASIS performs better than LEACH. For many applications, in addition to minimizing energy, it is also important to consider the delay incurred in gathering sensed data. We capture this with the energy /spl times/ delay metric and present schemes that attempt to balance the energy and delay cost for data gathering from sensor networks. We present two new schemes to minimize energy /spl times/ delay using CDMA and non-CDMA sensor nodes. We compared the performance of direct, LEACH, and our schemes with respect to energy /spl times/ delay using extensive simulations for different network sizes. Results show that our schemes perform 80 or more times better than the direct scheme and also outperform the LEACH protocol.     

一种安全有效的无线传感器网络数据收集方案

数据收集技术是无线传感器网络（WSNs）中的重要技术之一。针对无线传感器网络中存在恶意节点攻击可能造成数据包丢失,给出一种安全有效的无线传感器网络数据收集方案。该方案首先利用多路径路由和跟踪反馈机制构造出安全路径,然后再根据安全路径进行数据收集。性能分析结果表明：与基于随机分散路由的数据收集方案相比,所给方案可以大幅降低数据包被拦截率,具有更高的安全性。     

Understanding optimal data gathering in the energy and latency domains of a wireless sensor network

The problem of optimal data gathering in wireless sensor networks (WSNs) is addressed by means of optimization techniques. The goal of this work is to lay the foundations to develop algorithms and techniques that minimize the data gathering latency and at the same time balance the energy consumption among the nodes, so as to maximize the network lifetime. Following an incremental-complexity approach, several mathematical programming problems are proposed with focus on different network performance metrics. First, the static routing problem is formulated for large and dense WSNs. Optimal data-gathering trees are analyzed and the effects of several sensor capabilities and constraints are discussed, e.g., radio power constraints, energy consumption model, and data aggregation functionalities. Then, dynamic re-routing and scheduling are considered. An accurate network model is proposed that captures the tradeoff between the data gathering latency and the energy consumption, by modeling the interactions among the routing, medium access control and physical layers.For each problem, extensive simulation results are provided. The proposed models provide a deeper insight into the problem of timely and energy efficient data gathering. Useful guidelines for the design of efficient WSNs are derived and discussed.     

EADEEG:能量感知的无线传感器网络数据收集协议

提出了一种基于簇结构的无线传感器网络数据收集协议EADEEG(an energy-aware data gathering protocol for wireless sensor networks).EADEEG通过最小化网络通信开销以及良好的能量负载平衡方法,可以有效地延长网络寿命.与以前的相关研究相比,EADEEG采用了一种全新的簇头竞争参数,能够更好地解决节点能量异构问题.此外,EADEEG也采用了一种简单而有效的簇内节点调度算法,通过控制活动节点的密度,可以在不增加额外控制开销的条件下关闭冗余节点并保证覆盖要求,因此可以进一步延长网络寿命.模拟实验证明,在节点初始能量同构和异构两种情况下,EADEEG协议都能够满足用户对覆盖率的要求,并在网络寿命上大幅度优于LEACH(low energy adaptive clustering hierarchy),PEGASIS(power-efficient gathering in sensor information systems)和DEEG(distributed energy-efficient data gathering and aggregation protocol)协议.     

A new paradigm for urban surveillance with vehicular sensor networks

We consider a new application paradigm of vehicular sensor networks (VSN). Currently, vehicles are equipped with forward facing cameras to assist forensic investigations of events by proactive image-capturing from streets and roads. Due to content redundancy and storage imbalance in this in-network distributed storage system, how to maximize its storage capacity becomes a nontrivial challenge. In other words, how to maximize the average lifetime of sensory data (i.e., images generated by cameras) in the network is a fundamental problem to be solved. This paper presents, VStore, a cooperative storage solution in vehicular sensor networks for mobile surveillance, which has been designed to support redundancy elimination and storage balancing throughout the network. Compared with existing works, we propose a novel storage architecture for urban surveillance and deal with challenges in a mobile scenario. Field testing was carried out with a trace-driven simulator, which utilized about 500 taxis in Shanghai. The testing results showed that VStore can largely prolong the average lifetime of sensory data by cooperative storage.     

无线传感网中延迟受限的生命周期最大的数据收集算法

无融合数据收集是无线传感网络中最重要的技术之一.在持续实时的监测应用中,网络生命周期和网络传输延迟是衡量数据收集性能的两个重要指标,已有的研究大多侧重于某单一性能指标,而较少关注多性能的折衷优化.因此,本文研究了如何构造一棵延迟受限的生命周期最大的数据收集树,并将该构造问题形式化为一个整数规划问题,提出了有效的数据收集算法-EDG.该算法首先利用MITT方法构造生命周期近似最优的数据收集树,然后对“瓶颈节点”进行路径调整以使其满足延迟约束.仿真结果表明,与无延迟约束的MITT算法相比,EDG算法能在保证网络传输延迟的前提下,使其网络生命周期在大多数情况下达到MITT的90％以上.     

能量有效和延迟敏感的无线传感器网络数据收集协议

利用移动Sink进行数据收集是无线传感器网络数据收集的一个趋势。本文提出一种能量有效、延迟敏感的移动数据收集协议（Energy—efficient and Delay—Sensitive Data Gathering Protocol for Wireless Sensor Networks,简称EEDS）。EEDS中,移动Sink在网络中穿行,从代理节点收集传感器节点监测到的数据。为了减少数据收集的延迟,采用类TSP（Traveling Salesman Problem）的解决方法,确保移动Sink在各个代理节点中收集数据时,始终选择一条最短路径在网络中行走。模拟仿真表明,提出的数据收集协议在延长网络生命周期以及减少数据收集延迟方面都有显著的优势。     

延迟容忍传感器网络基于相对距离的数据传输

延迟容忍移动无线传感器网络(delay tolerant mobile sensor network,简称DTMSN)用于广泛数据收集.与传统的传感器网络不同,DTMSN 具有节点移动性、间歇连通性并且能够容忍适当的延迟,因此传统传感器网络的数据收集算法不能适用.提出了一种基于相对距离感知的动态数据传输策略RDAD(relative distance-aware data delivery scheme).RDAD采用传感器节点到汇聚点(sink node)的相对距离来计算节点传输概率的大小,并以此作为消     

无线传感器网络数据收集算法研究

对于无线传感器网络而言,可靠的数据收集是推进其大规模应用的关键,本文引入了移动传感器网络解决静态传感网络中的通信中断问题.针对移动传感器网络的数据收集,提出了数据收集的分类,分析了移动节点不同移动模式对网络数据收集的影响,比较了移动节点受控移动路径对比固定移动模式的优势,最后介绍了典型的移动节点受控移动的路径规划算法.     

A honeycomb structure based data gathering scheme with a mobile sink for wireless sensor networks

With the widespread use of wireless sensor networks, more and more applications require energy efficient and low packet loss rate data collection methods. Recently, the concept of ‘mobile’ is introduced in various mechanisms to meet the needs of this kind. In this paper, a honeycomb structure based data gathering scheme, HSDG, is proposed for wireless sensor networks with a mobile sink. By partitioning the network into a honeycomb structure and giving each partition a direction value, every sensor node can obtain the latest location of the mobile sink dynamically with a small amount of broadcasting overhead. HSDG uncouples the moving strategy of mobile sink from the data forwarding mechanism, and three subscheme HSDG_RM, HSDG_DGM, and HSDG_EGM are proposed. Our schemes are investigated from average energy consumption, maintenance cost, packet loss rate and the number of packets collected. Compared with BTDG and ALURP, HSDG_DGM is the most energy efficient with a low packet loss rate.     

无线传感器网络中移动协助的数据收集策略

利用移动数据收集器(mobile data collector,简称MDC)进行传感器网络中感知数据的收集,可以有效地减少传感器将数据发送到静止基站的传输跳数,节约网络的能量,延长网络寿命.此外,MDC通过循环收集传感器数据或承担数据转发的功能,避免节点间由于多跳传输引起的能量空洞(energy hole)以及节点失效造成的传输链路中断等问题.MDC的移动性也为无线传感器网络的研究带来新的挑战.研究基于移动协助数据收集的无线传感器网络结构,分类总结了近年来提出的一些典型的基于MDC的算法和协议,着重讨论了MDC在网络能量、延迟、路由和传输等方面带来的性能变化.最后,进行了各种算法的比较性总结,针对传感器网络中MDC的研究提出了亟待解决的问题,并展望了其未来的发展方向.     

Edge-centric trust management in vehicular networks

A major objective of vehicular networking is to improve road safety and reduce traffic congestion. The experience of individual vehicles on traffic conditions and travel situations can be shared with other vehicles for improving their route planning and driving decisions. Nevertheless, the frequent occurrence of adversary vehicles in the network may affect the overall network performance and safety. These vehicles may behave intelligently to avoid detection. To effectively control and monitor such security threats, an efficient Trust Management system should be employed to identify the trustworthiness of individual vehicles and detect malicious drivers which is the major focus of this work. We propose a hybrid solution, which integrates Edge Computing and Multi-agent modeling in a Trust Management system for vehicular networks. The proposed solution also aims to overcome the limitations of the two commonly utilized approaches in this context: cloud computing and Peer-to-Peer (P2P) networking. Our framework has a set of features that make it an efficient platform to address the major security challenges in vehicular networks including latency, scalability, uncertainty, data accessibility, and malicious behavior detection. Performance of the approach is evaluated by simulating a realistic environment. Experimental results show that the proposed approach outperforms similar approaches from literature for various performance indicators.     

数据融合在传感器网络协议中的节能性分析

传感器网络受到带宽、能量和吞吐量因素的限制,制约了点对点信息传送的数量。网内处理冗余数据或信息,组合更为高效,符合用户需求的数据融合技术很好地解决了这些问题。阐述数据融合在传感器网络中的作用,针对现有数据融合在网络协议中提出的各种算法思想,分析比较了数据融合的节能性能。由此可知,基于生成树的融合方法更能平衡节点负载,延长网络的生命周期,从而解决无线传感器网络存在的问题。     

一种基于非均匀分簇的混合无线传感网数据收集方法

提出了一种针对混合无线传感网的数据收集协议。将网络划分为非均匀高度的网格,并利用主次簇头分别构建针对矢量和标量信息的数据收集路径。实验结果表明,与MTP,CDFUD等分层和分簇的数据收集方法相比,本算法具备较好的能耗均衡性。     

Bio-inspired data transmission scheme to multiple sinks for the long-term operation of wireless sensor networks

Wireless sensor networks have a wide range of applications, such as natural environmental monitoring, object tracking, and environmental control in residential spaces or plants. In wireless sensor networks, many sensor nodes with limited resources are placed in an observation area and used to gather information about environments. Therefore, a data gathering scheme (or a routing algorithm) for saving and balancing the energy consumption of each sensor node is needed to prolong the lifetime of wireless sensor networks. This article proposes a new bio-inspired data transmission scheme for the long-term operation of wireless sensor networks. By using the proposed scheme, autonomous load-balancing data transmission to multiple sinks can be actualized. We evaluate the proposed scheme using computer simulations to verify its effectiveness, and also discuss its development potential.     

基于蚁群算法的传感器网络分布式广播算法

提出了一种基于优化蚁群算法的传感器网络中分布式广播算法。根据传感节点的密度进行簇的划分,用优化的蚁群算法在各簇中分别寻找从广播源点开始遍历所有传感节点,返回广播源点的最优链路,利用蚁群算法的正反馈效应来达到广播与数据聚集的目的。实验表明,该多链方案不需要网络节点维护全局信息,避免了全网构建的链中可能存在两个离得远的节点成为邻节点的情况,它在节点不均匀分布的情况下比最近邻居算法取得了更小的能耗和延迟代价,是一种高效的分布式广播算法。