无线传感器网络基于议价解的合作策略

针对无线传感器网络（WSN）的合作多样性问题,对结合节点能耗和吞吐量的对称合作模式进行了讨论。基于Raiffa-Kalai-Smorodinsky议价解（RBS）,将对称合作问题转换成议价问题,提出了一种提高网络传输效率的WSN对称合作策略。分析了由[n]传感器节点和一个sink 组成的对称合作模型,并在此基础上,讨论了RBS最优带宽分配策略的实现过程。仿真结果表明,该对称合作策略可以大大提高传感器节点的传输效率。     

基于RBS 的合作通信网络公平合作策略

针对合作通信网络中基于纳什议价解(NBS)的合作策略存在用户效用分配不公平的问题,同时考虑用户的最大与最小效用,提出了基于Raiffa-Kalai-Smorodinsk议价解(RBS)的合作策略,并建立了用户合作的条件.仿真结果表明,基于RBS的合作策略在保证网络总效用不变的前提下,具有更好的公平性.     

Multi-user symmetric cooperation based on nash bargaining solution in cooperative relay networks

This paper presents a symmetric cooperation strategy for cooperative relay networks with multiple users. The multi-user symmetric cooperation model and the relay selection algorithm are proposed. Then, the time slot allocation problem is cast into a bargaining problem, and the optimal time slot allocation solution is obtained by Nash bargaining solution (NBS). Moreover, we also consider the implementations of the cooperation strategy, i.e., the grouping and admission control algorithm. Simulation results show that users can obtain larger rates under the symmetric cooperation strategy than the non-cooperative case.     

Ubiquitous tutoring in laboratories based on wireless sensor networks

Industrial education places a high premium on experiences in practical hands-on training, though it is commonly recognized for the deprivation in its opportunities of student performance analysis due to lack of recorded data as such. In the present study, the technology of wireless sensor networks has been implemented in the tutoring in courses offered in laboratory skills, where the students’ experimental skills and learning inclinations have been examined. Two sets of questionnaires in the respective aspects have been developed to be administered in order to have pretest–posttest scores obtained. As illustrated in the results derived from the study, a learning environment where wireless sensor networks provide a significant degree of support during laboratory sessions, student performance had significantly improved, and this has been proven evidently for the students in the low-achievement group when being compared to the results delivered by the students in the high-achievement group.     

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.     

A framework based on barycentric coordinates for localization in wireless sensor networks

Localization is a fundamental and vital problem in wireless sensor networks. This paper presents an optimizing framework for localization based on barycentric coordinates. The framework consists of two components. The first component retains the structure revealed by the distances between pairs of nodes; the second component constrains the boundary nodes to maintain the distance with their neighbor nodes. A hybrid localization algorithm is derived on top of the optimizing framework. A part of the computation is performed collaboratively by nodes, whereas the rest is executed on the sink node. Experimental results show that the proposed localization algorithm obtains lower location errors without higher communication costs.     

无线传感网络任务分配的能效性控制策略

无线传感网络包含大量密集分布传感节点,各节点测量产生大量数据给传输、存储、管理和分析带来困难,无线传感网络能源不可更换性限制了网络寿命.本文提出基于熵理论和欧式距离的网络能耗评价指标,采用对等(peer-to-peer,简称P2P)计算方法,利用基于蚁群智能的能效性优化任务分配控制策略,针对中心节点工作状态、传输能耗和网络寿命实现动态实时任务控制分配,完成多中心节点并行计算,提高网络工作效率,节约能耗.实验表明基于蚁群智能的能效性任务分配控制策略能实时有效地缩短无线传感网络计算时间,减少网络能耗,提高网络寿命.     

基于粒子滤波的无线传感器网络目标跟踪算法

传感器节点的组织和路由对无线传感器网络(WSN)目标跟踪算法的性能有重大影响.为此,针对具有簇一树型网络拓扑结构的WSN,首先给出集中式粒子滤波跟踪算法(CPFTA)实现的具体步骤,然后提出一种分布式粒子滤波跟踪算法(DPFTA),构建性能评价体系,通过仿真实验给出两种跟踪算法的定量比较,结果表明DPFTA的跟踪精度稍低于CPFTA,但能大幅度减少通信开销,而且具有更小的跟踪反应时间;最后仿真分析了传感器覆盖密度和检测周值对跟踪算法性能的影响.     

Node coordination mechanism based on distributed estimation and control in wireless sensor and actuator networks

Wireless sensor and actuator networks （WSANs） have a wide range of applications. To perform effective sensing and acting tasks, multiple coordination mechanisms among the nodes are required. As attempt in this direction, this paper describes collaborative estimation and control algorithms design for WSANs. First, a sensor-actuator coordination model is proposed based on distributed Kalman filter in federated configuration. This method provides the capability of fault tolerance and multi-source information fusion. On this basis, an actuator-actuator coordination model based on even-driven task allocation is introduced. Actuators utilize fused sensory information to adjust their action that incur the minimum energy cost to the system subject to the constraints that user＇s preferences regarding the states of the system are approximately satisfied. Finally, according to system requirements, a distributed algorithm is proposed to solve the task allocation problem. Simulations demonstrate the effectiveness of our proposed methods.     

A novel differential evolution based clustering algorithm for wireless sensor networks

Clustering is an efficient topology control method which balances the traffic load of the sensor nodes and improves the overall scalability and the life time of the wireless sensor networks (WSNs). However, in a cluster based WSN, the cluster heads (CHs) consume more energy due to extra work load of receiving the sensed data, data aggregation and transmission of aggregated data to the base station. Moreover, improper formation of clusters can make some CHs overloaded with high number of sensor nodes. This overload may lead to quick death of the CHs and thus partitions the network and thereby degrade the overall performance of the WSN. It is worthwhile to note that the computational complexity of finding optimum cluster for a large scale WSN is very high by a brute force approach. In this paper, we propose a novel differential evolution (DE) based clustering algorithm for WSNs to prolong lifetime of the network by preventing faster death of the highly loaded CHs. We incorporate a local improvement phase to the traditional DE for faster convergence and better performance of our proposed algorithm. We perform extensive simulation of the proposed algorithm. The experimental results demonstrate the efficiency of the proposed algorithm.     

无线传感器网络动态重传算法

无线传感器网络路由协议通过点到点的重传来提高数据传输的可靠性,其重传机制没有考虑不同业务数据的可靠性需求差异,统一设定一个静态的最大重传次数。本文提出了一种动态重传算法,为每种业务分别根据其可靠性需求动态设定最大重传次数。对于较低可靠性需求的业务,相比于传统重传机制减少了重传次数。仿真表明动态重传算法能有效降低网络能耗。     

基于节点协同覆盖的传感器网络寿命最大化模型

针对保证网络连通覆盖和最小能量消耗的优化目标,建模了基于节点协同覆盖的传感器网络寿命最大化模型.提出一种基于多目标优化遗传算法的求解方案,设计了基于链路状态的分簇机制以及基于NSGA-Ⅱ的簇内覆盖控制算法.仿真结果表明该方案能快速收敛于最优解,在高密度和低密度布撒环境下表现出优越的性能,且具有良好的适应性.     

一种分布式能量有效的无线传感器网络分簇路由协议

提出了一种分布式能量有效的无线传感器网络分簇路由协议DEEC(Distributed Energy-efficient Clustering Algorithm)。该协议采用基于时间的簇首选择算法,广播时间取决于自身剩余能量和其邻居节点的剩余能量。在数据传输阶段,采用簇内单跳与簇间多跳相结合的方式,引入权值函数优化簇首中继节点的选择。仿真实验结果表明,与LEACH,PEGASIS协议相比,DEEC能够有效地节约单个节点能量、均衡网络能耗、延长网络生存周期。     

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.

一种基于优先级的无线传感器网络实时MAC协议

MAC(Medium access control)协议直接影响着无线传感器网络能量的有效性和实时性,对此,提出一种基于公平优先级的MAC(FP-MAC)协议.该协议对不同类型的网络数据流设置不同的优先级,以保证较高优先级的数据能够实时传输;根据网络负载自适应地调节占空比,实现了低能耗与低时延.分析及实验表明,协议给出了时延上限,提供了实时性及可扩展性,同时保证了不同优先级之间的公平性,能够很好地适应具有实时性要求的无线传感器网络应用.     

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.     

Angle-of-arrival localization based on antenna arrays for wireless sensor networks

Among the large number of contributions concerning the localization techniques for wireless sensor networks (WSNs), there is still no simple, energy and cost efficient solution suitable in outdoor scenarios. In this paper, a technique based on antenna arrays and angle-of-arrival (AoA) measurements is carefully discussed. While the AoA algorithms are rarely considered for WSNs due to the large dimensions of directional antennas, some system configurations are investigated that can be easily incorporated in pocket-size wireless devices.A heuristic weighting function that enables decreasing the location errors is introduced. Also, the detailed performance analysis of the presented system is provided. The localization accuracy is validated through realistic Monte-Carlo simulations that take into account the specificity of propagation conditions in WSNs as well as the radio noise effects. Finally, trade-offs between the accuracy, localization time and the number of anchors in a network are addressed.     

无线传感器网络基于路径的非均匀分布策略

无线传感器网络中多对一的数据传输方式导致节点负载的不均衡性,靠近汇聚节点(Sink)的节点要比远离Sink的节点消耗更多的能量,如此容易引发能量空洞问题。针对该问题,从网络数据的传递路径出发,根据网络中节点承担的路径数量的不同,平衡各层节点的能耗,提出感知节点覆盖率一致、内层路由节点与其所有外层感知节点数目相同的的非均匀分布策略,并通过仿真实验证明了该方法的有效性。     

Practical data compression in wireless sensor networks: A survey

Power consumption is a critical problem affecting the lifetime of wireless sensor networks. A number of techniques have been proposed to solve this issue, such as energy-efficient medium access control or routing protocols. Among those proposed techniques, the data compression scheme is one that can be used to reduce transmitted data over wireless channels. This technique leads to a reduction in the required inter-node communication, which is the main power consumer in wireless sensor networks. In this article, a comprehensive review of existing data compression approaches in wireless sensor networks is provided. First, suitable sets of criteria are defined to classify existing techniques as well as to determine what practical data compression in wireless sensor networks should be. Next, the details of each classified compression category are described. Finally, their performance, open issues, limitations and suitable applications are analyzed and compared based on the criteria of practical data compression in wireless sensor networks.