A scheduling scheme for wireless sensor networks based on social insect colonies

Sensor networks employ a large amount of wireless sensor nodes to provide sensing power with high redundancy. Such redundancy makes sensor networks robust under changing environments. However, without proper scheduling, the surplus sensing power will cost tremendous energy consumption to the wireless sensor nodes. A scheduling scheme based on social insect colonies is proposed here. The proposed scheme is a kind of adaptive 'periodic on-off' scheduling scheme that uses only local information for making scheduling decisions. The scheme is evaluated in terms of averaged detection delay, target 3-coverage hit-rate and energy consumption per successful target detection. Simulation results show that, when comparing with other generic scheduling schemes, the proposed scheme can reduce energy consumption from a minimum of 7.49% to a maximum of 90.81% and improve the target hit-rate from a minimum of 15.7% to a maximum of 58.9%. Optimisation of the network lifetime and other performances is possible by adjusting some parameters.     

Controlled deployments for wireless sensor networks

In wireless sensor networks (WSNs), the operation of sensor nodes has to rely on a limited supply of energy (such as batteries). To support long lifetime operation of WSNs, an energy-efficient way of sensor deployment and operation of the WSNs is necessary. A new controlled layer deployment (CLD) protocol to guarantee coverage and energy efficiency for a sensor network is proposed. CLD outperforms previous similar protocols in that it can achieve the same performances and guarantee full area coverage and connection using a smaller number of sensors. It can also ameliorate the 'cascading problem' that reduces the whole network lifetime. Finally, analysis and simulation results show that CLD can use fewer sensor nodes for coverage and also increases the lifetime of the sensor network when compared with the probing environment and adapting sleeping (PEAS) protocol.     

Hybrid Micropower Source for Wireless Sensor Network

Wireless sensor networks have become a very significant enabling technology in many applications and the use of environmental energy is a feasible source for low-power wireless sensor networks. The challenges of developing a power supply including generation or conversion, storage, and power management are manifold to extend the lifetime of a wireless sensor network. The objective of this research is to develop an intelligent hybrid power system to realize a self-sustaining wireless sensor node. The photovoltaic and thermoelectric generators are adopted as energy converters. The lithium ion battery and ultracapacitor are used as reservoirs. An intelligent power management system has been developed to control the power distribution. The design data and experimental results show that the hybrid micropower source can extend the lifetime of a sensor network.     

Energy-efficient directional routing between partitioned actors in wireless sensor and actor networks

Actor?actor communication is an important part of the functioning of wireless sensor?actor networks and enables the actor nodes to take coordinated action on a given event. Owing to various reasons such as actor mobility and low actor density, the actor network tends to get partitioned. The authors propose to use the underlying sensor nodes, which are more densely deployed, to heal these partitions. In order to maximise the utilisation of the limited energy available with the sensor nodes, a new routing protocol for actor?actor communication using directional antennas on the actor nodes is proposed. The authors contribution is threefold. First, using simulations they show that the problem of partitioning in the actor networks is significant and propose an architecture with directional antennas on actor nodes and sensor bridges to heal these partitions. Second, they identify the routing problem for this architecture based on a theoretical framework and propose centralised as well as distributed solutions to it. Third, they develop a routing protocol based on the distributed solution and show, using network simulations, that the proposed protocol not only heals the network partitions successfully, but also achieves high throughput and fairness across different flows, in addition to maximising the network lifetime.     

基于DSP的智能家居无线网络节点的设计

 将无线传感器网络技术融入智能家居系统中,设计合理的网络节点成为智能家居系统的核心问题．在分析无线传感器网络节点结构基础上,提出以DSP 芯片TMS320F206为处理器、AT86RF230为无线通信芯片的无线传感器网络节点．充分考虑节能和扩展性的需求,采用节点定时打开与关闭的协议且打开与关闭的时间比为1∶99．试验表明该无线网络节点能满足低功耗、长传输距离、准确定位、抗干扰的要求．     

Voronoi-based relay placement scheme for wireless sensor networks

Energy consumption is a crucially important issue in battery-driven wireless sensor networks (WSNs). In most sensor networks, the sensors near the data collector (i.e. the sink) become drained more quickly than those elsewhere in the network since they are required to relay all of the data collected in the network to the sink. Therefore more balanced data paths to the sink should be established in order to extend the lifetime of the sensor network. Accordingly, a novel relay deployment scheme for WSNs based on the Voronoi diagram is proposed. The proposed scheme is applicable to both two-dimensional and three-dimensional network topologies and establishes effective routing paths that balance the traffic load within the sensor network and alleviate the burden on the sensors around the sink. Simulation results indicate that the number of relays deployed in the proposed scheme is similar to that deployed in the predetermined location scheme and is significantly less than that deployed in the minimum set cover scheme. Furthermore, the lifetime of the sensor network containing relay nodes deployed using the current scheme is longer than that achieved using either the predetermined location scheme or the minimum set cover scheme.     

Intelligent Real-Time Adaptation for Power Efficiency in Sensor Networks

This paper presents an intelligent, dynamic power conservation scheme for sensor networks in which the sensor network operation is adaptive to both changes in the objects under measurement and the network itself. The conservation scheme switches sensor nodes between a sleep and an active mode in a manner such that the nodes can maximize the time they spend in a power-efficient sleep state, which corresponds to a nonmeasuring and/or nontransmitting mode, while not missing important events. A switching decision is made based on changes (or their absence) in the signals sensed from the environment by an intelligent agent that has been trained to determine whether or not a special event has occurred. This intelligent agent is based on a novel neural network topology that allows for a significant reduction in the resource consumption required for its training and operation without compromising its change detection performance. The scheme was implemented to control a sensor network built from a number of Telos rev. B motes currently available on the market. A few new utilities including an original neural network-based intelligent agent, a “visualizer,” a communication manager, and a scheduler have been designed, implemented, and tested. Power consumption measurements taken in a laboratory environment confirm that use of the designed system results in a significant extension of sensor network lifetime (versus “always on” systems) from a few days to a few years.      

Lifetime improvement in wireless sensor networks via collaborative beamforming and cooperative transmission

Collaborative beamforming (CB) and cooperative transmission (CT) have recently emerged as communication techniques that can make effective use of collaborative/cooperative nodes to create a virtual multiple-input/multiple-output system. Extending the lifetime of networks composed of battery-operated nodes is a key issue in the design and operation of wireless sensor networks. The effects on network lifetime of allowing closely located nodes to use CB/CT to reduce the load or even to avoid packet-forwarding requests to nodes that have critical battery life are considered. First, the effectiveness of CB/CT in improving the signal strength at a faraway destination using energy in nearby nodes is studied. Then, the performance improvement obtained by this technique is analysed for a special 2D disc case. Further, for general networks in which information-generation rates are fixed, a new routing problem is formulated as a linear- programming problem, whereas for other general networks, the cost for routing is dynamically adjusted according to the amount of energy remaining and the effectiveness of CB/CT. From the analysis and the simulation results, it is seen that the proposed method can reduce the payloads of energy-depleting nodes by about 90% in the special case network considered and improve the lifetimes of general networks by about 10%, compared with existing techniques.     

Monitoring in Industrial Systems Using Wireless Sensor Network With Dynamic Power Management

The advances in wireless communication, microelectronics, digital electronics, and highly integrated electronics and the increasing need for more efficient controlled electric systems make the development of monitoring and supervisory control tools the object of study of many researchers. This paper proposes a digital system for energy usage evaluation, condition monitoring, diagnosis, and supervisory control for electric systems applying wireless sensor networks (WSNs) with dynamic power management (DPM). The system is based on two hardware topologies responsible for signal acquisition, processing, and transmission: intelligent sensor modules (ISMs) and remote data acquisition units (RDAUs). The gateway function of the wired network is carried out by remote servers (RSs) based on the Soekris architecture, which is responsible for receiving the data collected and transmitting it to the supervisory controller (SC). To extend the WSN lifetime, sensor nodes implement a DPM protocol. The basic characteristics of the presented system are the following: 1) easy implementation; 2) low-cost implementation; 3) easy implementation of redundant routines (security); 4) portability/versatility; and 5) extended network lifetime.      

An Energy-Efficient Wireless Power Transmission-Based Forest Fire Detection System

Compared with the traditional techniques of forest fires detection, wireless sensor network (WSN) is a very promising green technology in detecting efficiently the wildfires. However, the power constraint of sensor nodes is one of the main design limitations of WSNs, which leads to limited operation time of nodes and late fire detection. In the past years, wireless power transfer (WPT) technology has been known as a proper solution to prolong the operation time of sensor nodes. In WPT-based mechanisms, wireless mobile chargers (WMC) are utilized to recharge the batteries of sensor nodes wirelessly. Likewise, the energy of WMC is provided using energy-harvesting or energy-scavenging techniques with employing huge, and expensive devices. However, the high price of energy-harvesting devices hinders the use of this technology in large and dense networks, as such networks require multiple WMCs to improve the quality of service to the sensor nodes. To solve this problem, multiple power banks can be employed instead of utilizing WMCs. Furthermore, the long waiting time of critical sensor nodes located outside the charging range of the energy transmitters is another limitation of the previous works. However, the sensor nodes are equipped with radio frequency (RF) technology, which allows them to exchange energy wirelessly. Consequently, critical sensor nodes located outside the charging range of the WMC can easily receive energy from neighboring nodes. Therefore, in this paper, an energy-efficient and cost-effective wireless power transmission (ECWPT) scheme is presented to improve the network lifetime and performance in forest fire detection-based systems. Simulation results exhibit that ECWPT scheme achieves improved network performance in terms of computational time (12.6%); network throughput (60.7%); data delivery ratio (20.9%); and network overhead (35%) as compared to previous related schemes. In conclusion, the proposed scheme significantly improves network energy efficiency for WSN.     

基于遗传算法的传感器网络拓扑控制研究

无线传感器网络的首要设计目标是延长网络生命期,网络的拓扑控制是实现这一目标的支撑 基础。针对传统拓扑控制方案所获拓扑的连通冗余度高或结构健壮性低等弊端,将问题转化 为多判据最小生成树模型,提出了一种基于遗传算法的拓扑控制方案。仿真实验结果 表明,该方案可获得具有网络整体功耗低、结构健壮性高和节点间通信干扰小等特点的拓扑 结构,因而能够有效地延长传感器网络生命期。     

Efficient power-consumption-based load-sharing topology control protocol for harsh environments in wireless sensor networks

Energy conservation and network performance are critical issues in wireless sensor networks.The authors present a novel efficient communication topology control protocol, called quorum-based load-sharing control protocol (QLSCP). QLSCP is a quorum-based communication protocol, which chooses appropriate communication nodes, adjusts the service loads of critical nodes and performs adaptive sleep management. QLSCP is suitable for harsh environments without a central control server calculating the locations of sensors, using the factor of the remaining power to build the system topology. The proposed protocol divides the topology operation into topology formation, adjustment and execution phases. The topology formation phase builds the backbone of an enhanced tree. In the topology adjustment phase, the enhanced tree is adjusted by an optimal balance of critical nodes in the backbone. In the topology execution phase, the efficient surplus-energy consuming (ESC) mechanism is proposed to efficiently exhaust the energy of each node. The ESC mechanism is designed to efficiently exhaust the latest remaining electronic power of sensor nodes. Simulation results of QLSCP demonstrate that it efficiently achieves to prolong system lifetime in harsh environments.     

ECO-BAT: A New Routing Protocol for Energy Consumption Optimization Based on BAT Algorithm in WSN

Wireless sensor network (WSN) has been widely used due to its vast range of applications. The energy problem is one of the important problems influencing the complete application. Sensor nodes use very small batteries as a power source and replacing them is not an easy task. With this restriction, the sensor nodes must conserve their energy and extend the network lifetime as long as possible. Also, these limits motivate much of the research to suggest solutions in all layers of the protocol stack to save energy. So, energy management efficiency becomes a key requirement in WSN design. The efficiency of these networks is highly dependent on routing protocols directly affecting the network lifetime. Clustering is one of the most popular techniques preferred in routing operations. In this work we propose a novel energy-efficient protocol for WSN based on a bat algorithm called ECO-BAT (Energy Consumption Optimization with BAT algorithm for WSN) to prolong the network lifetime. We use an objective function that generates an optimal number of sensor clusters with cluster heads (CH) to minimize energy consumption. The performance of the proposed approach is compared with Low-Energy Adaptive Clustering Hierarchy (LEACH) and Energy Efficient cluster formation in wireless sensor networks based on the Multi-Objective Bat algorithm (EEMOB) protocols. The results obtained are interesting in terms of energy-saving and prolongation of the network lifetime.     

An efficient local improvement operator for the multi-objective wireless sensor network deployment problem

Wireless sensor network layout, also known as sensor node deployment, is a complex NP-complete optimization task that determines most of the functioning features of a wireless sensor network. Coverage, connectivity and lifetime (handled through its opposing parameter, power consumption), are three of the most important characteristics of the service, and are taken into consideration in this article within a multi-objective approach of the problem. Leveraging on the specific properties of the wireless sensor nodes and networks, the Proximity Avoidance Coverage-preserving Operator (PACO) for local improvement is presented, described and tested. The testbed consists of a set of state-of-the-art multi-objective optimization algorithms with different configurations, and problem instances of varying size. In all the scenarios, and more specially in the algorithmic settings that already produce high performance solutions, PACO has proven to be a robust enhancement to the raw optimization technique, without requiring additional computation, that easily scales through problem complexity.     

无线传感器网络几类拓扑控制及其抗毁性应用简述

无线传感器网络的拓扑结构随着网络中节点的增加、减少和移动实时变化,为保证网络的连通性和覆盖性不被影响,拓扑控制技术所要解决的问题正是传感器节点如何更好地自组织构建全局网络拓扑．本文首先概述了四类拓扑控制算法的理论基础及算法步骤．然后,对提高网络抗毁性的两类拓扑演化算法进行了详细叙述,即无标度网络生长与构建$k$连通网络,分别构建了基于节点位置偏好的移动网络拓扑模型和基于$k$连通的节点调度优化模型．最后,分别从移动节点的引入、折中控制算法的探索、复杂网络理论的应用和传统算法与智能算法的结合这四方面对拓扑控制算法的前景进行了阐述．     

无线传感器网络的流量自适应分簇算法协议

在分析LEACH路由协议算法的缺点的基础上,提出了一种用于无线传感器网络的基于流量自适应的TDMA分簇算法协议.该协议根据当前节点数据流量的变化,自适应地调整该节点在其簇内通信的时隙长度,减少节点空闲时消耗的能量和节点从睡眠到活跃状态来回切换的能量.仿真实验结果表明,与LEACH协议簇内时隙分配算法相比,运用这种新的时隙分配算法,可以节省节点的能量,提高网络的生存时间,改善网络性能.     

一种新的分布式无线传感器网络定位方法

针对无线传感器网络节点能源受限的特征,以系统最小硬件开销为设计原则,提出了一种适用于基于测距的分布式定位方法(3/2-NANDB),该方法可在不增加单个独立节点硬件开销的情况下,利用附加的外部控制系统发射一个旋转定向波束充分挖掘节点间的冗余信息,有效排除节点位置的模糊性,从而可完全确定只有两个邻居节点的节点位置和部分只有一个邻居节点的节点位置,达到减少GPS携带节点数量、最大化网络内部可定位节点数目、扩大网络观察范围和延长无线传感器网络存活时间等目的.而利用该方法的节点二义性排除算法,还可以辅助其他现有的基于三邻居(3-NA)的定位算法提高整体定位性能.     

Three-Dimensional Distance-Error-Correction-Based Hop Localization Algorithm for IoT Devices

The Internet of Things (IoT) is envisioned as a network of various wireless sensor nodes communicating with each other to offer state-of-the-art solutions to real-time problems. These networks of wireless sensors monitor the physical environment and report the collected data to the base station, allowing for smarter decisions. Localization in wireless sensor networks is to localize a sensor node in a two-dimensional plane. However, in some application areas, such as various surveillances, underwater monitoring systems, and various environmental monitoring applications, wireless sensors are deployed in a three-dimensional plane. Recently, localization-based applications have emerged as one of the most promising services related to IoT. In this paper, we propose a novel distributed range-free algorithm for node localization in wireless sensor networks. The proposed three-dimensional hop localization algorithm is based on the distance error correction factor. In this algorithm, the error decreases with the localization process. The distance correction factor is used at various stages of the localization process, which ultimately mitigates the error. We simulated the proposed algorithm using MATLAB and verified the accuracy of the algorithm. The simulation results are compared with some of the well-known existing algorithms in the literature. The results show that the proposed three-dimensional error-correction-based algorithm performs better than existing algorithms.     

A Mobile Host Approach for Wireless Powering and Interrogation of Structural Health Monitoring Sensor Networks

Wireless sensor networks (WSNs) for structural health monitoring (SHM) applications can provide the data collection necessary for rapid structural assessment after an event such as a natural disaster puts the reliability of civil infrastructure in question. Technical challenges affecting deployment of such a network include ensuring power is maintained at the sensor nodes, reducing installation and maintenance costs, and automating the collection and analysis of data provided by a wireless sensor network. In this work, a new "mobile host" WSN paradigm is presented. This architecture utilizes nodes that are deployed without resident power. The associated sensors operate on a mechanical memory principle. A mobile host, such as a robot or unmanned aerial vehicle, is used on an as-needed basis to charge the node by wireless power delivery and subsequently retrieve the data by wireless interrogation. The mobile host may be guided in turn to any deployed node that requires interrogation. The contribution of this work is the first field demonstration of a mobile host wireless sensor network. The sensor node, referred to as THINNER, capable of collecting data wirelessly in the absence of electrical power was developed. A peak displacement sensor capable of interfacing with the THINNER sensor node was also designed and tested. A wireless energy delivery package capable of being carried by an airborne mobile host was developed. Finally, the system engineering required to implement the overall sensor network was carried out. The field demonstration took place on an out-of-service, full-scale bridge near Truth-or-Consequences, NM.     

Nimble and adaptive time-division multiple access control phase algorithm for cluster-based wireless sensor networks

Control phase plays a critical role in the performance of time-division multiple access (TDMA)-based networks. Within cluster-based wireless sensor networks, a nimble and adaptive control phase algorithm called NACPA to control the control phase of TDMA-based medium access control (MAC) in cluster-based sensor networks is proposed. This algorithm takes advantage of the wireless sensor hardware feature and presents a more accurate although simpler means to calculate the number of contention nodes in one round. On the basis of the analysis of the features of contention probability against the number of contention nodes, this algorithm can significantly reduce its computation complexity, rendering it practically feasible for resource-constrained sensor networks. Detailed analytical evaluation against two typical MAC algorithms (polling and carrier sense multiple access) is presented both in terms of packet transmission delay and average channel utilisation, the results of which, while also matching the simulation observation, have shown its effectiveness and efficiency.