Comparison of energy harvesting systems for wireless sensor networks

Wireless sensor networks (WSNs) offer an attractive solution to many environmental, security, and process monitoring problems. However, one barrier to their fuller adoption is the need to supply electrical power over extended periods of time without the need for dedicated wiring. Energy harvesting provides a potential solution to this problem in many applications. This paper reviews the characteristics and energy requirements of typical sensor network nodes, assesses a range of potential ambient energy sources, and outlines the characteristics of a wide range of energy conversion devices. It then proposes a method to compare these diverse sources and conversion mechanisms in terms of their normalised power density.     

基于无线传感器网络的压电能量收集技术

随着物联网的发展,多节点的传感器供电成为关键问题,由于环境中普遍存在低频振动,采用了压电悬臂梁结构,建立压电悬臂梁结构的电学模型,并进行了ANSYS的仿真,仿真得到电压76 V,约等于模型的理论值,验证了模型的正确性。进而继续研究了压电悬臂梁几何尺寸对固有频率的影响,振子越长,质量块越长,频率越低。从而收集低频振动环境中的能量,为传感器供电装置提供了设计的理论依据。     

环境能量驱动的无线传感器节点数据传输优化机制

将环境能量收集模块引入无线传感器网络,可以有效改善网络的使用寿命,但是能量的随时补充也给原有的能量管理策略带来了巨大挑战.针对单个环境能量驱动节点在数据序列已经到达的情况下,研究了优化的数据传输策略,采用内罚函数法优化传输过程,使得固定时间内节点传输的数据量最大.理论分析及仿真结果表明,当各个时刻节点的传输功率比较接近时会获得最大的数据传输量;当实际节点获得最大数据传输时节点的传输功率随时间呈增大趋势.     

无线传感器网络的压电能量收集技术研究

针对压电能量收集装置在进行能量收集时具有固有频率高、能量收集效率低等问题,设计了一种变截面压电能量收集装置,并对压电振子进行了理论建模和有限元特性分析。根据分析结果,在相同的条件下,变截面悬臂梁的固有频率比等截面悬臂梁低。同时,变截面悬臂梁在截面厚度等于0. 4 mm时,电压输出最大,可达23. 77 V;变截面悬臂梁比等截面悬臂梁具有频带宽、输出电压高,并具有比等截面悬臂梁质量轻的优点。从而对环境中低频振动的能量进行收集时,为传感器的供电装置提供了理论的设计依据。     

Consensus networks over finite fields

This work studies consensus strategies for networks of agents with limited memory, computation, and communication capabilities. We assume that agents can process only values from a finite alphabet, and we adopt the framework of finite fields, where the alphabet consists of the integers {0,…,p−1}$\{0,\dots ,p-1\}$, for some prime number p$p$, and operations are performed modulo p$p$. Thus, we define a new class of consensus dynamics, which can be exploited in certain applications such as pose estimation in capacity and memory constrained sensor networks. For consensus networks over finite fields, we provide necessary and sufficient conditions on the network topology and weights to ensure convergence. We show that consensus networks over finite fields converge in finite time, a feature that can be hardly achieved over the field of real numbers. For the design of finite-field consensus networks, we propose a general design method, with high computational complexity, and a network composition rule to generate large consensus networks from smaller components. Finally, we discuss the application of finite-field consensus networks to distributed averaging and pose estimation in sensor networks.     

Interactive view-dependent rendering over networks

For a client-server based view-dependent rendering system, the overhead of view-dependent rendering and the network latency are major obstacles in achieving interactivity. In this paper, we first present a multiresolution hierarchy traversal management strategy to control the overhead of view-dependent rendering for low-capacity clients. Then we propose a predictive parallel strategy to overcome the network latency for client-server based view-dependent multiresolution rendering systems. Our solution is to make the client process and the server process run in parallel, using the rendering time to cover the network latency. For networks with long round-trip times, we manage to overlap the network latency for one frame with the rendering time for multiple frames. View-parameters prediction is incorporated to make the parallelism of the client and the server feasible. In order to maintain an acceptable view-dependent rendering quality in the network environment, we develop a synchronization mechanism and a dynamic adjustment mechanism to handle the transient network slowdowns and the changes of the network condition. Our experimental results, in comparison with the sequential method, show that our predictive parallel approach can achieve an interactive frame rate while keeping an acceptable rendering quality for large triangle models over networks with relatively long round-trip times.     

Information markets over trust networks

Information markets are inefficient. Information products have large upfront development costs, yet their duplication costs are negligibly small; and they are experience goods with high costs of marketing and promotion. As a result, either winner-take-all markets are created through large and expensive promotional campaigns, or artificial monopoly power is conferred by the government through copyright protection, or both, to prevent the collapse of these markets from intense price competition and piracy. Such inefficiency creates opportunities to design more efficient markets by utilizing new technologies. Trust networks provide such an opportunity where the network infrastructure acts not only as a distribution system for information products, but also as an advertising and promotion medium, a payment and pricing mechanism, a guarantee and insurance service, and a copyright enforcement and dispute resolution tool. Such a network-centric market place is proposed to remedy many of the shortcomings of mass markets by relying on peer-to-peer distribution, peer-to-peer payments, and peer-to-peer enforcement of trust and integrity. Analytical models are presented to show that such a market place for information goods can scale up to satisfy large markets without expensive promotions and advertising campaigns, create customized products with dynamic pricing, reduce entry costs by eliminating the distinction between buyers and sellers, and eliminate the need for copyright protection.     

复杂网络上的群体决策

现状和最新进展.首先介绍了观点动力学研究中的几种基本模型,即Ising模型、投票者模型、多数决定模型和有界自信模型等.其次以这些模型为基础,讨论了小世界、无标度等复杂网络上观点动力学的研究结果,然后指出了观点动力学与语言游戏、一致性和耦合振子同步问题的联系,接着给出了笔者在观点动力学方面所做的一些相关工作,最后指出了复杂网络上群体决策的未来发展方向和一些可能的应用前景.     

Opportunistic routing in wireless sensor networks powered by ambient energy harvesting

Energy consumption is an important issue in the design of wireless sensor networks (WSNs) which typically rely on portable energy sources like batteries for power. Recent advances in ambient energy harvesting technologies have made it possible for sensor nodes to be powered by ambient energy entirely without the use of batteries. However, since the energy harvesting process is stochastic, exact sleep-and-wakeup schedules cannot be determined in WSNs Powered solely using Ambient Energy Harvesters (WSN–HEAP). Therefore, many existing WSN routing protocols cannot be used in WSN–HEAP. In this paper, we design an opportunistic routing protocol (EHOR) for multi-hop WSN–HEAP. Unlike traditional opportunistic routing protocols like ExOR or MORE, EHOR takes into account energy constraints because nodes have to shut down to recharge once their energy are depleted. Furthermore, since the rate of charging is dependent on environmental factors, the exact identities of nodes that are awake cannot be determined in advance. Therefore, choosing an optimal forwarder is another challenge in EHOR. We use a regioning approach to achieve this goal. Using extensive simulations incorporating experimental results from the characterization of different types of energy harvesters, we evaluate EHOR and the results show that EHOR increases goodput and efficiency compared to traditional opportunistic routing protocols and other non-opportunistic routing protocols suited for WSN–HEAP.     

k-Multi-preference query over road networks

Nowadays, the road network has gained more and more attention in the research area of databases. Existing works mainly focus on standalone queries, such as k-nearest neighbor queries over a single type of objects (e.g., facility like restaurant or hotel). In this paper, we propose a k-multi-preference (kMP) query over road networks, involving complex query predicates and multiple facilities. In particular, given a query graph, a kMP query retrieves of the top-k groups of vertices (of k facility types) satisfying the label constraints and their aggregate distances are the smallest. A naïve solution to this problem is to enumerate all combinations of vertices with k possible facility types and then select the one with the minimum sum distance. This method, however, incurs rather high computation cost due to exponential possible combinations. In addition, the existing solutions to other standalone queries are for a single type of facilities and cannot be directly used to answer kMP queries. Therefore, in this paper, we propose an efficient approach to process a kMP query, which utilizes an index with bounded space and reduces the computation cost of the shortest path queries. We also design effective pruning techniques to filter out false alarms. Through our extensive experiments, we demonstrate the efficiency and effectiveness of our proposed solutions.     

Distributed linear estimation over sensor networks

We consider a network of sensors in which each node may collect noisy linear measurements of some unknown parameter. In this context, we study a distributed consensus diffusion scheme that relies only on bidirectional communication among neighbour nodes (nodes that can communicate and exchange data), and allows every node to compute an estimate of the unknown parameter that asymptotically converges to the true parameter. At each time iteration, a measurement update and a spatial diffusion phase are performed across the network, and a local least-squares estimate is computed at each node. The proposed scheme allows one to consider networks with dynamically changing communication topology, and it is robust to unreliable communication links and failures in measuring nodes. We show that under suitable hypotheses all the local estimates converge to the true parameter value.     

面向无线网络的可伸缩视频编码传输策略*

针对现有面向无线网络的可伸缩视频编码(Scalable Video Coding, SVC)传输策略未能充分考虑失真和能耗的问题,提出了一种基于失真和节点能耗最小化的SVC传输策略。该策略在分析SVC的编码失真、传输过程中的丢包失真的基础上,计算了接收端的视频失真总和;通过计算SVC传输系统的功率,对无线网络中的节点能耗进行了分析。然后综合考虑了能耗、传输时间及质量要求,将SVC的传输策略转化为一个优化问题,进而得到最优的SVC编码参数,在获得较优视频质量的前提下实现了SVC的可靠传输。仿真实验结果表明,与目前典型的SVC传输策略相比,该策略不但有效降低了SVC传输过程中的平均失真,而且在相同的能量消耗水平下,获得了更好的视频质量。     

filtering of nonlinear plants over networks

In this paper, we consider the filtering problem for Lipschitz systems in a networked environment. We assume that the measurements transmitted over the network are subject to quantization, uncertain delays and communication constraints. We first analytically demonstrate how each of the these issues affect the filtering problem. Second, we tackle the filter design as an optimization problem with LMI constraints. The optimization maximizes the Lipschitz constant and thus the region of attraction for which the filter is stable and an bound is satisfied by the error system. Copyright © 2013 John Wiley & Sons, Ltd.     

Dependable user-level socket over dual networks

Message duplication over multiple links can enhance the communication reliability and availability among distributed processes running on clusters or networked workstations. In addition, message striping over multiple links can enhance communication throughput and transfer times. This paper introduces optimized techniques to provide a dependable user-level socket that enhances the reliability and performance of message deliveries over dual network interfaces. The proposed techniques are designed to work on top of reliable transport protocols. In addition, a technique for efficient duplication of messages on dual networks to enhance both communication reliability and performance on top of reliable transport protocol is proposed. A prototype socket based on this model is developed and evaluated. The experimental evaluations of the proposed model indicate good communication reliability and performance gains over conventional methods.     

无线传感器网络选择性DV-Hop定位算法

针对传统的矢量跳距(DV-Hop)定位算法平均定位误差大的问题,提出了一种具有选择性的改进DV-Hop定位算法。该算法首先剔除长距离信标节点信息,更新最小跳数与平均每跳距离,再次根据信标节点的实际距离和估计距离的误差进一步修正平均每跳距离。仿真结果表明:选择性DV-Hop定位算法能有效地减小平均定位误差,适应各种网络。     

一种新的适用于异构网络的TCP算法

提出了一种新的适用于异构网络的传输控制协议（TCP）算法。该算法不仅能够动态寻求网络中的性能最优点,尽量使网络流量保持在该点,而且能够判断网络中数据包丢失的原因,合理地调整参数,避免了TCP-Reno中盲目将发送窗口减半的机制。仿真实验的结果表明,新算法的性能优于TCP-Reno和其他同类改进协议。     

ADP-based optimal sensor scheduling for target tracking in energy harvesting wireless sensor networks

This paper proposes a novel sensor scheduling scheme based on adaptive dynamic programming, which makes the sensor energy consumption and tracking error optimal over the system operational horizon for wireless sensor networks with solar energy harvesting. Neural network is used to model the solar energy harvesting. Kalman filter estimation technology is employed to predict the target location. A performance index function is established based on the energy consumption and tracking error. Critic network is developed to approximate the performance index function. The presented method is proven to be convergent. Numerical example shows the effectiveness of the proposed approach.     

On optimal preference diffusion over social networks

It was well observed that a user’s preference over a product changes based on his/her friends’ preferences, and this phenomenon is called “preference diffusion”, and several models have been proposed for modeling the preference diffusion process. These models share an idea that the diffusion process involves many iterations, and in each iteration, each user has his/her preference affected by some other preferences (e.g., those of his/her friends). When computing users’ preferences after a certain number of iterations, these models use users’ preferences at the end of that iteration only, which we believe is not desirable since users’ preferences at the end of other iterations should also have some effects on users’ final preferences. Therefore, in this paper, we propose a new model for preference diffusion, which takes into consideration users’ preferences at each iteration for computing users’ final preferences. Under the new model, we study two problems for optimizing the preference diffusion process with respect to two different objectives. One is easy to solve for which we design an exact algorithm and the other is NP-hard for which we design a $(1-1∕e)$-factor approximate algorithm. We conducted extensive experiments on real datasets which verified our proposed model and algorithms.