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。     

Energy-efficient cooperative data aggregation for wireless sensor networks

Recently, cooperative communication mechanism is shown to be a promising technology to improve the transmit diversity only by a single transceiver antenna. Using this communication paradigm, multiple source nodes are able to coordinate their transmissions so as to obtain energy savings. As data aggregation is one of the most important operations in wireless sensor networks, this paper studies the energy-efficient data aggregation problem through cooperative communication. We first define the cooperative data aggregation (CDA) problem, and formally prove that this problem is NP-Hard. Due to the difficult nature of this problem, we propose a heuristic algorithm MCT for cooperative data aggregation. The theoretical analysis shows that this algorithm can reach the approximate performance ratio of 2. Moreover, the distributed implementation DMCT of the algorithm is also described. We prove that both centralized and distributed algorithms can construct the same topology for cooperative data aggregation. The experimental simulations show that the proposed algorithms will decrease the power consumption by about 12.5% and 66.3% compared with PEDAP and PEGASIS algorithms respectively.     

Energy-efficient forwarding in wireless sensor networks

For maximizing the energy efficiency in a wireless network, we propose two forwarding schemes termed single-link and multi-link energy-efficient forwarding that tradeoff delivery ratios against energy costs. Multi-link forwarding improves the network performance substantially by addressing multiple receivers at once during the packet forwarding process. If the first forwarding node does not receive a packet correctly, other nodes may act as backup nodes and perform the forwarding instead. By means of mathematical analyses, we derive how the energy efficiency of a forwarding path can be computed and how a forwarding tree is established. Routing cycles are explicitly taken into account and prevented by means of sequence numbers. Simulations and real-world experiments provide a comparison to other reference strategies, showing a superior performance of our forwarding scheme in terms of energy efficiency.     

Energy-efficient and high-accuracy secure data aggregation in wireless sensor networks

Due to the inherent characteristics of resource-constrained sensors, communication overhead is always a major concern in wireless sensor networks (WSNs). Data aggregation is an essential technique to reduce the communication overhead and prolong network lifetime. Since data aggregation results are usually used to make critical decisions, the accuracy of final aggregation results is very important. Furthermore, as wireless sensor networks are increasing being deployed in security-critical applications, we should take security into consideration as well. Therefore, for such applications, data aggregation protocols must be highly energy efficient and highly accurate while being able to prevent an adversary from stealing private data held by each sensor node. In this paper, we propose an energy-efficient and high-accuracy (EEHA) scheme for secure data aggregation. The main idea of our scheme is that accurate data aggregation is achieved without releasing private sensor readings and without introducing significant overhead on the battery-limited sensors. We conduct extensive simulations to evaluate the performance of EEHA. Our analysis and simulations show that EEHA is more efficient and accurate than the existing scheme.     

Energy-efficient bootstrapping for wireless sensor networks

Wireless sensor networks are poised for increasingly wider uses in many military and civil applications. Such applications has stimulated research in a number of research areas related to energy conservation in such networks. Most such research focuses on energy saving in tasks after the network has been organized. Very little attention has been paid to network bootstrapping as a possible phase where energy can be saved. Bootstrapping is the phase in which the entities in a network are made aware of the presence of all or some of the other entities in the network. This paper describes a bootstrapping protocol for a class of sensor networks consisting of a mix of low-energy sensor nodes and a small number of high-energy entities called gateways. We propose a new approach, namely the slotted sensor bootstrapping (SSB) protocol, which focuses on avoiding collisions in the bootstrapping phase and emphasizes turning off node radio circuits whenever possible to save energy. Our mechanism synchronizes the sensor nodes to the gateway’s clock so that time-based communication can be used. The proposed SSB protocol tackles the issue of node coverage in scenarios, when physical device limitations and security precautions prevent some sensor nodes from communicating with the gateways. Additionally, we present an extension of the bootstrapping protocol, which leverages possible gateway mobility.     

一种能量高效的无线传感器网络分簇路由算法

无线传感器网络中节点的能量有限,提高能量的有效性便成为无线传感器网络路由协议设计的首要目标。设计了一种能量高效的分簇路由算法,它提出让候选节点在一定的覆盖范围内以剩余能量为标准来竞选簇头,以使簇头分布均匀;处于簇类交界的节点则根据能量和距离来选择归属的簇头,以平衡网络负载;新算法还采用多跳的簇间通信方式来降低大部分簇头节点的通信负载。仿真结果表明:新算法能够有效降低网络能耗,延长网络生存时间。     

Energy-efficient communication in wireless cable sensor networks

In this paper, we introduce a new type of sensor: cable sensor. Unlike traditional point sensors, this type of sensor has a rectangular sensing region with a processor installed on it to do processing and communication. The wireless network formed by this kind of sensor is called wireless cable sensor network (WCSN). We study energy-efficient communication algorithms in WCSNs. We address it in two ways: one is through reducing the total transmission power of processors while maintaining the connectivity of the network and the other is through scheduling cable sensors to let them take turns to go to sleep without affecting the coverage and connectivity of the network. In the first approach, we initially develop a distributed algorithm called DTRNG based on the relative neighbourhood graph. Later we enhance it to Algorithm determine the transmission power by removing the largest edge in CYCles (DTCYC). Mathematical proofs show that Algorithm DTCYC provides an optimal solution that can not only minimise the total processor transmission power but maintain the connectivity of the network as well. In the second approach, we propose a cable mode transition algorithm which determines the minimum number of active sensors to maintain K-coverage as well as K-connectivity required by the application. We discuss the relationship between coverage and connectivity and prove the theorems that lay the foundation for our algorithm. Simulation results demonstrate that our algorithm is efficient in saving energy.     

Energy-efficient clustering in lossy wireless sensor networks

Recent experimental studies have revealed that a large percentage of wireless links are lossy and unreliable for data delivery in wireless sensor networks (WSNs). Such findings raise new challenges for the design of clustering algorithms in WSNs in terms of data reliability and energy efficiency. In this paper, we propose distributed clustering algorithms for lossy WSNs with a mobile collector, where the mobile collector moves close to each cluster head to receive data directly and then uploads collected data to the base station. We first consider constructing one-hop clusters in lossy WSNs where all cluster members are within the direct communication range of their cluster heads. We formulate the problem into an integer program, aiming at maximizing the network lifetime, which is defined as the number of rounds of data collection until the first node dies. We then prove that the problem is NP-hard. After that, we propose a metric-based distributed clustering algorithm to solve the problem. We adopt a metric called selection weight for each sensor node that indicates both link qualities around the node and its capability of being a cluster head. We further extend the algorithm to multi-hop clustering to achieve better scalability. We have found out that the performance of the one-hop clustering algorithm in small WSNs is very close to the optimal results obtained by mathematical tools. We have conducted extensive simulations for large WSNs and the results demonstrate that the proposed clustering algorithms can significantly improve the data reception ratio, reduce the total energy consumption in the network and prolong network lifetime compared to a typical distributed clustering algorithm, HEED, that does not consider lossy links.     

Energy-efficient distributed clustering in wireless sensor networks

The deployment of wireless sensor networks in many application areas requires self-organization of the network nodes into clusters. Clustering is a network management technique, since it creates a hierarchical structure over a flat network. Quite a lot of node clustering techniques have appeared in the literature, and roughly fall into two families: those based on the construction of a dominating set and those which are based solely on energy considerations. The former family suffers from the fact that only a small subset of the network nodes are responsible for relaying the messages, and thus cause rapid consumption of the energy of these nodes. The latter family uses the residual energy of each node in order to decide about whether it will elect itself as a leader of a cluster or not. This family’s methods ignore topological features of the nodes and are used in combination with the methods of the former family. We propose an energy-efficient distributed clustering protocol for wireless sensor networks, based on a metric for characterizing the significance of a node, w.r.t. its contribution in relaying messages. The protocol achieves small communication complexity and linear computation complexity. Experimental results attest that the protocol improves network longevity.     

Adaptive image compression technique for wireless sensor networks

When using wireless sensor networks for real-time image transmission, some critical points should be considered. These points are limited computational power, storage capability, narrow bandwidth and required energy. Therefore, efficient compression and transmission of images in wireless sensor network is considered. To address the above mentioned concerns, an efficient adaptive compression scheme that ensures a significant computational and energy reduction as well as communication with minimal degradation of the image quality is proposed. This scheme is based on wavelet image transform and distributed image compression by sharing the processing of tasks to extend the overall lifetime of the network. Simulation results are presented and they show that the proposed scheme optimizes the network lifetime, reduces significantly the amount of the required memory and minimizes the computation energy by reducing the number of arithmetic operations and memory accesses.     

无线传感器网络中的能效优化路由算法*

根据无线传感器网络节点能量消耗和网络生存周期的特点,通过建立动态规划能量优化模型,在路由总能耗满足能量阈值约束条件下,均衡消耗网络中各节点能量,在此基础上提出一种适合无线传感器网络的动态规划路由算法。仿真结果表明,提出的路由算法能充分地利用有限的能量资源,较大地延长网络生存周期并降低节点的平均能耗。     

Energy-efficient routing for mobile data collectors in wireless sensor networks with obstacles

This paper proposes an energy-efficient routing mechanism by introducing intentional mobility to wireless sensor networks (WSNs) with obstacles. In the sensing field, Mobile Data Collectors (MDCs) can freely move for collecting data from sensors. An MDC begins its periodical movement from the base station and finally returns and transports the data to the base station. In physical environments, the sensing field may contain various obstacles. A research challenge is how to find an obstacle-avoiding shortest tour for the MDC. Firstly, we obtain the same size grid cells by dividing the network region. Secondly, according to the line sweep technique, the spanning graph is easily constructed. The spanning graph composed of some grid cells usually includes the shortest search path for the MDC. Then, based on the spanning graph, we can construct a complete graph by Warshall-Floyd algorithm. Finally, we present a heuristic tour-planning algorithm on the basis of the complete graph. Through simulation, the validity of our method is verified. This paper contributes in providing an energy-efficient routing mechanism for the WSNs with obstacles.     

成簇无线传感网中能量高效的协作通信

在成簇无线传感器网络中,会出现极大簇和极小簇并存的现象,从而导致整个网络的能量消耗不均衡,进而降低网络性能。通过采用邻近极大极小簇协作发送的方案,极大地均衡了网络的能量消耗,提高了通信的可靠性。仿真结果表明,基于邻近极大极小簇的协作发送方案是一种高能效协作方案,能够很好地均衡网络能量消耗,在延长网络生存周期方面具有更优越的性能。     

能量有效的无线传感器网络协同覆盖

在节点随机分布的无线传感器网络目标覆盖中,考虑到单个节点有时难以完成对目标的感知,利用节点的概率感知模型和漏检率的概念,提出了节点协同覆盖的思想,并建立了协同覆盖模型;详细分析并推导了协同覆盖感知概率、节点数目和节点参与协同覆盖的最低感知概率之间的关系;在协同覆盖模型的基础上,考虑节点能量消耗的因素,设计了优化网络使用寿命的协同覆盖算法ECTC;仿真结果表明,该算法在改善网络感知概率的同时,延长了网络的使用寿命。     

无线传感器网络中能量有效的加权分簇算法

针对无线传感器网络中节点受到能量和带宽等资源严格制约的问题,通过分簇可以使网络中节点能量负载均衡,从而延长网络的生存周期.从能量和节点度的角度出发,分析了无线传感器网络中现有的一些分簇算法提出,了一种新的适合于无线传感器网络的能量有效的加权分簇算法,通过仿真和分析得出,该算法是一种有效的分簇算法.     

高效节能的链式分层无线传感器网络路由协议

提出了一种高效节能的链式分层无线传感器网络路由协议（ECR）,阐述了协议的组织思想。本协议采用混合控制方式,有效结合中心控制方式和分布式算法的优势,产生两层链式簇结构;利用简单而高效的最大剩余能量原则选取父簇头,有效延长了网络第一个节点失效的时间和提高了网络能量利用率。通过与LEACH和PEGASIS 两协议的仿真比较,论证了ECR协议的高效性。     

能量有效的三维无线传感器网络覆盖算法

无线传感器网络通常都工作在三维空间中,因此需要三维空间中的覆盖算法。结合三维空间的特点对二维空间内的覆盖算法SGA进行改进,在此基础上提出一种三维空间的覆盖算法——SSG算法,该覆盖算法的优点是不依赖于节点位置信息,并通过仿真实验给出了覆盖质量分析。     

无线传感网中能量有效的免碰撞MAC协议

无线传感网络普遍使用CSMA/CA机制和二进制指数退避算法避免碰撞。提出了一种能量有效的免碰撞MAC协议ERC。该协议将数据传输划分为协商和节点排队传输两个阶段,通过碰撞避免、节点休眠和批量传输机制提升吞吐量并节省整体能耗。理论分析和仿真表明,该协议在各种负载情况下都能明显提升网络的吞吐量与能量效率。     

Energy-efficient adaptive sensor scheduling for target tracking in wireless sensor networks

Sensor scheduling is essential to collaborative target tracking in wireless sensor networks (WSNs). In the existing works for target tracking in WSNs, such as the information-driven sensor query (IDSQ), the tasking sensors are scheduled to maximize the information gain while minimizing the resource cost based on the uniform sampling intervals, ignoring the changing of the target dynamics and the specific desirable tracking goals. This paper proposes a novel energyefficient adaptive sensor scheduling approach that jointly selects tasking sensors and determines their associated sampling intervals according to the predicted tracking accuracy and tracking energy cost. At each time step, the sensors are scheduled in alternative tracking mode, namely, the fast tracking mode with smallest sampling interval or the tracking maintenance mode with larger sampling interval, according to a specified tracking error threshold. The approach employs an extended Kalman filter (EKF)-based estimation technique to predict the tracking accuracy and adopts an energy consumption model to predict the energy cost. Simulation results demonstrate that, compared to a non-adaptive sensor scheduling approach, the proposed approach can save energy cost significantly without degrading the tracking accuracy.