Efficient time synchronization by K-D tree in WSN

Vehicle detectors provide essential information about parking occupancy and traffic flow. To cover large areas that lack a suitable electrical infrastructure, wired sensors networks are impractical because of their high deployment and maintenance costs. Wireless sensor networks (WSNs) with autonomous sensor nodes can be more economical. Vehicle detectors intended for a WSN should be small, sturdy, low power, cost-effective, and easy to install and maintain. Currently available vehicle detectors based on inductive loops, ultrasound, infrared, or magnetic sensors do not fulfill the requirements above, which has led to the search for alternative solutions. This paper presents a vehicle detector which includes a magnetic and an optical sensor and is intended as sensor node for use with a WSN. Magnetic sensors based on magnetoresistors are very sensitive and can detect the magnetic anomaly in the Earth's magnetic field that results from the presence of a car, but their continuous operation would drain more than 1.5 mA at 3 V, hence limiting the autonomy of a battery-supplied sensor node. Passive, low-power optical sensors can detect the shadow cast by car that covers them, but are prone to false detections. The use of optical triggering to wake-up a magnetic sensor, combined with power-efficient event-based software, yields a simple, compact, reliable, low-power sensor node for vehicle detection whose quiescent current drain is 5.5 μA. This approach of using a low-power sensor to trigger a second more specific sensor can be applied to other autonomous sensor nodes.

A scheme for WSNs (wireless sensor networks) security is given by dividing sensing tetrahedron into clusters and using the symmetric polynomials in this paper.The sensing tetrahedron is divided into a number of small grids.All those sensor nodes, both ordinary sensor nodes and heterogeneous sensor nodes are distributed in the sensing tetrahedron.In a grid, all ordinary sensor nodes and heterogeneous sensor nodes establish their shared keys through using the symmetric polynomials.All the heterogeneous sensor nodes establish their shared keys through using the symmetric polynomials.At last, all sensor nodes establish their keys directly or indirectly in the whole sensing tetrahedron.Analysis and comparison demonstrate this scheme enhances the WSN security, has good network connectivity, saves node storage, reduces network computing load, and extends the network lifetime.

Power efficient ultra-wideband based wireless communication for wireless body area network applications

The wireless sensor network is set of hundreds or thousands nodes, where each node is connected to one or sometimes several sensors. A WSN integrated circuits, sensor, embedded computing, modern network, Wireless communication and distributed information processing. Wireless sensor networks, a technology acquisition and processing of information. Recent developments in the course of it, in order to miniaturization and low power design. They act as a gateway between sensor nodes and the end user as they typically forward data from the WSN on to a server. Other special components in routing based networks are routers, designed to compute, calculate and distribute the routing tables. The project dealt with the problem of routing wireless sensor networks for energy balance. To optimize the solution, genetic algorithm is proposed. Key points when choosing the cluster center is proposed for placement algorithm. In this paper, the proposed standard algorithms, simulated results based on the parameters of the number of dead nodes, the number of bits transmitted to a base station, the number of bits sent to the heads of energy consumption compared repetitions and show superiority over the network the proposed algorithm is relative.

The domain of wireless sensor networks (WSNs) is one of the most rapidly growing scientific fields. This is because not only the technological advances have enabled the development of advanced sensor nodes with extremely low cost but the potential applications of such structures are ever growing too. WSNs differ from traditional wireless communication networks in several of their characteristics. One of them is power awareness, due to the fact that the batteries of sensor nodes have a restricted lifetime and are difficult to be replaced. Therefore, all protocols must be designed in such a way as to minimize energy consumption and preserve the longevity of the network. That is why, routing protocols in WSNs aim mainly to accomplish power conservation while in traditional networks they focus primarily on the quality of service (QoS). Recent advances in WSNs have led to many new protocols specifically designed for sensor networks where energy awareness is an essential issue. This work suggests the development of such hierarchical routing protocol, named SHPER (scaling hierarchical power efficient routing), which proves to be particularly effective.

Node placement for connected target coverage in wireless sensor networks with dynamic sinks

Wireless Sensor Network is greatly evolved in recent years. Technological advancements in wireless networks are intended to develop various fields especially in medical domain. Nowadays, remote health monitoring is possible by the enormous growth of wireless body area sensor networks. The Wireless Body Area Sensor Network monitors the human health by using wearable body sensors, and sends the status of the human health to the medical experts. Body nodes will be placed on, in and around the human body. The major key issue in Wireless Body Area Sensor Network is power management. Since batteries used in sensors are very tiny, it tends to have a minimal lifetime. In order to increase the lifetime of the sensor node, the energy needs to be utilized in an efficient manner. In this paper we have proposed conditional re-transmission technique to minimize the energy consumption. So the sensor nodes lifetime will get increased and in turn Wireless Body Area Sensor Networks lifetime will also be increased. By increasing the lifetime of the sensor nodes, the batteries or sensor nodes need not to be replaced frequently.

Recent advancement in technologies for wireless sensor networks has led to the emergence of wireless body sensor networks (WBSN). These networks are composed of various sensor nodes that are placed on the human body and have the ability to constantly detect, process and transmit any sensed vital signs of patients to physicians without confining the patients to their hospital beds or restraining their movement. In common with a good number of other sensor network applications, the sensors are constrained by not having sufficient energy for them to function, a situation which often leads to unexpected failures in the network. However, recent research has shown that the use of mobile nodes for data transfer can significantly reduce energy consumption of the network. Hence, in this paper, an energy efficient hybrid algorithm using particle swarm optimization (PSO) algorithm and teaching-learning-based optimization (TLBO) algorithm is presented. The proposed algorithm takes into consideration the residual energy and the distance of each node from the base station to select routes from the sensing nodes to the base station. The hybridization is performed by the incorporation of the teaching and learning factors of TLBO algorithm into the velocity equation of PSO algorithm in order to improve the convergence of the algorithm into global optimum. The performance of the new hybrid algorithm is compared to similar optimization algorithms. Extensive simulation results show the potential of the proposed algorithm to optimize the energy of wireless body sensor networks.

An energy efficient and QoS aware routing protocol for wireless sensor and actuator networks

Ultra-wideband (UWB) radio communication sys- tems operate using extremely short duration base-band pulses. This paper compares the performance of three competing multi- ple access modulation schemes that have been proposed for appli- cation to UWB based wireless sensor networks. These multiple access schemes are ultra-wideband Time-Hopping (TH-UWB), Direct Sequence Spread Spectrum (DSSS-UWB) and Orthogonal Frequency Division Multiplexing (OFDM-UWB). Each system was investigated under four operating conditions of different bandwidths and bit rates for three different transmission ranges. The attributes measured to compare the performance of the multiple access schemes under consideration were packet link error rate, throughput and energy efficiency. TH-UWB outper- forms DSSS-UWB and OFDM-UWB for high bandwidth condi- tions. Whereas, DSSS-UWB performs better in low bandwidth conditions compared to the other two systems. Decreasing the transmission range significantly degrades the overall performance of the systems. I. INTRODUCTION Wireless sensor networks are special networks composing of a large number of inexpensive, low-power communication sensing devices (sensor nodes), which are densely deployed throughout a physical space and have the capability of col- laborating with each other to monitor a wide variety of ambient conditions. Realisation of sensor network applications requires wireless ad hoc networking techniques (1), therefore the sensor nodes are deployed in an ad hoc fashion and are required to organize themselves to form a multi-hop wireless communication network. Efficient and reliable communication between multiple sen- sor network entities is a big challenge. The increased collision probability resulting from multiple sensor nodes transmitting data simultaneously over the same transmission medium is a common problem facing communication in wireless networks. This problem can be overcome by using reliable multiple access techniques. An ideal wireless sensor communication network would require a multiple access scheme that allows the accommodation of multiple users and provides effective communication. It must also offer some measure of security and should have low probability of intercept. It should also be resistant to jamming and must be energy efficient. Ultra-wideband (UWB) radio is an emerging technology that operates using extremely short duration base-band pulses and has a number of advantages that makes it an attractive choice for sensor networks. In particular, UWB systems have low power and low complexity. They have a noise like signal and are therefore resistant to severe multipath and jamming. They also provide greater bandwidth and are more cost ef- fective for providing increased throughput without increasing power. The three approaches to multiple access in UWB are:

Recent technological advances in microelectronics and nano-systems technologies have made it feasible to equip wireless sensor nodes with small low-cost cameras to capture and transmit video. Wireless video sensor networks are gaining popularity due to numerous potential applications such as video surveillance, environmental and habitat monitoring, and so on. However, due to the limited battery available in wireless video sensor nodes, provisioning of QoS in such a network is a challenging task. We provide a survey on the major issues related to QoS provisioning in wireless video sensor networks and possible solution approaches. A dynamic power management framework is proposed for a wireless video sensor node to improve energy saving performance so that the lifetime of the sensor node can be increased. This framework considers the video traffic arrival process in the sensor node, the sleep and wakeup processes in the camera and wireless transceiver electronics, the queue status, and the wireless channel condition. Performance analysis results show that the proposed mechanism can achieve considerable energy saving in a sensor node while providing a target level of QoS performance.

Frequency converters are used to control electric motors in many kinds of industrial applications. Since they control the electric motors that run the machines or processes, they must be strongly integrated with the rest of the automation system. If the wireless sensor and actuator networks are used as a part of the same automation system, it would be beneficial to have a direct connection between wireless sensor network and frequency converter instead of routing the information through several interfaces. To enable this, we built a software and hardware integration between frequency converter and wireless sensor network. Developed system was tested by performing several experiments in real industrial environment that consisted of sophisticated mobile machines. In the experiments, several frequency converters and sensor nodes were used in the same network. System performance and reliability was evaluated based on the experiment results, and some directions pointed for the future work.

Wireless Sensor Network is useful in broad range of applications such as natural disaster relief, military, environmental and health monitoring. Coverage is one of the fundamental problem and an active research area in wireless sensor network. WSN is an emerging field due to its large contribution in dealing with coverage. It consist of low cost, low power, small size and multifunction sensor nodes. The critical aspect with wireless sensor network is energy conservation. In power constrained WSN, scheduling of sensors to be done effectively and efficiently so as to maximize network lifetime. In this paper we give an introduction to WSN and its fundamental problems that is target coverage problem together with energy constraint. The target coverage problem is proven to be NP-Complete problem by many researchers. We propose a new energy-efficient heuristic for target coverage problem in wireless sensor network to maximize total network lifetime.

The efficiency of transportation system depends on many factors, such as traffic congestion, vehicle accidents and road conditions. To improve the reliability, productivity and safety of the system, many researchers propose to use a wireless sensor network (WSN) as a solution. A WSN usually consists of many tiny sensor nodes for sensing, data processing and communication. In this study, we present the development of a small-sized, low-power and lightweight wireless sensor node. It is equipped with a 3-axes accelerometer, an altimeter sensor, humidity sensor, temperature sensor, 315 MHz RF transceiver module and a typical coin-sized lithium battery (3.0 V, 220 mAh). The entire sensor node fits within a 28 × 20 × 8 mm <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</sup> volume and is only 7 grams (not including the antenna). An 8-bit MCU is included in the RF transceiver module to control sensor node operation. It collects and transmits sensors data in real time to the RF repeater with bit rate 24 kbps. During continuous operation, the sensor node consumes less than 3 mA current. Thus for a 220 mAh battery, the wireless sensor node can continue operating for more than 75 hours.

Sensor nodes in Wireless Sensor Networks (WSNs) operate with limited power resources such as small batterieswhich are difficult to be either recharged or replaced in some environments when depleted. Power consumptionrepresents one of the most constraints impact the design of WSNs, leading to various protocols and algorithmsaimed at minimizing the power consumption and extending batteries' lifetime. Sensor nodes in WSNs transmittheir periodic packets continuously to central nodes (receivers) which are responsible for decoding packets andtransmitting them to other communication networks. In addition, sensors usually follow various MAC strategieswhich allow accessing to wireless communication channels. However, sensors may attempt to access thewireless channels at the same time, potentially, leading to collisions among multiple nodes. In fact, central nodesin WSNs most often consume a large amount of power due to the necessity to decode every received packetregardless of the fact that the transmission may suffer from packets collision which impede the networkperformance. Therefore, in the receiver side of WSNs current collision detection mechanisms have largely beenrevolving around direct demodulation and decoding of received packets and deciding on a collision based onsome form of parity bits in each packet for error control. From information theoretic prospective full decoding ofreceived packets with error control bits at central nodes can achieve an efficient usage of network capacity,however, such an approach represents a major burden on power-constrained sensors. This drawback comes fromthe need to expend a significant amount of energy and processing complexity at sink nodes in order tofully-decode a packet, only to discover the packet is illegible due to a collision. In this paper, we propose a morepractical power saving approaches which achieve a significant power saving with low-complexity at the expenseof low throughput losses. Based on studying the statistics of received packets, central nodes can make a fastdecision to detect a collision without the need for full-decoding of the whole received packets. Our novelapproaches not only reduces processing complexity and hence power consumption, but it also reduces the delayincurred to detect a collision since it operates on only a small number of IQ samples in the beginning of areceived packet. In such a paradigm, our approaches operate directly at the output of the receiver’sAnalog-to-Digital-Converter (ADC) and eliminate the need to pass the corrupted packets through the entiredemodulator/decoder line-up. The performance gain of our proposed approach is illustrated through thecomparison between the computational complexity of our Statistical Discrimination (SD) approaches and someexisting Full Decoding (FD) algorithms(note 1). Our results show that the SD approaches has significant powersavings and low computational complexities over existing FD algorithms with low False-Alarm and Missprobabilities, which qualify our SD approaches to be considered as reliable collision detection mechanisms inWSNs. We also show how to tune various design parameters in order to allow a system designer multipledegrees of freedom for design trade-offs and optimization.