Practical Wireless Sensor Networks Research Articles

Modelling and planning reliable wireless sensor networks based on multi-objective optimization genetic algorithm with changeable length

Wireless sensor networks (WSN) have shown their potentials in various applications, which bring a lot of benefits to users from different working areas. However, due to the diversity of the deployed environments and resource constraints, it is difficult to predict the performance of a topology. Besides the connectivity, coverage, cost, network longevity and service quality should all be considered during the planning procedure. Therefore, efficiently planning a reliable WSN is a challenging task, which requires designers coping with comprehensive and interdisciplinary knowledge. A WSN planning method is proposed in this work to tackle the above mentioned challenges and efficiently deploying reliable WSNs. First of all, the above mentioned metrics are modeled more comprehensively and practically compared with other works. Especially 3D ray tracing method is used to model the radio link and sensing signal, which are sensitive to the obstruction of obstacles; network routing is constructed by using AODV protocol; the network longevity, packet delay and packet drop rate are obtained via simulating practical events in WSNet simulator, which to the best of our knowledge, is the first time that network simulator is involved in a planning algorithm. Moreover, a multi-objective optimization algorithm is developed to cater for the characteristics of WSNs. Network size is changeable during evolution, meanwhile the crossovers and mutations are limited by certain constraints to eliminate invalid modifications and improve the computation efficiency. The capability of providing multiple optimized solutions simultaneously allows users making their own decisions, and the results are more comprehensive optimized compared with other state-of-the-art algorithms. Practical WSN deployments are also realized for both indoor and outdoor environments and the measurements coincident well with the generated optimized topologies, which prove the efficiency and reliability of the proposed algorithm.

A modified differential evolution-based combined routing and sleep scheduling scheme for lifetime maximization of wireless sensor networks

In recent years, wireless sensor networks (WSNs) have transitioned from being objects of academic research interest to a technology that is frequently employed in real-life applications and rapidly being commercialized. Nowadays the topic of lifetime maximization of WSNs has attracted a lot of research interest owing to the rapid growth and usage of such networks. Research in this field has two main directions into it. The first school of researchers works on energy efficient routing that balances traffic load across the network according to energy-related metrics, while the second school of researchers takes up the idea of sleep scheduling that reduces energy cost due to idle listening by providing periodic sleep cycles for sensor nodes. As energy efficiency is a very critical consideration in the design of low-cost sensor networks that typically have fairly low node battery lifetime, this raises the need for providing periodic sleep cycles for the radios in the sensor nodes. Until now, these two fields have remained more or less disjoint leading to designs where to optimize one component, the other one must be pre-assumed. This in turn leads to many practical difficulties. To circumvent such difficulties in the performance of sensor networks, instead of separately solving the problem of energy efficient routing and sleep scheduling for lifetime maximization, we propose a single optimization framework, where both the components get optimized simultaneously to provide a better network lifetime for practical WSN. The framework amounts to solving a constrained non-convex optimization problem by using the evolutionary computing approach, based on one of the most powerful real-parameter optimizers of current interest, called Differential Evolution (DE). We propose a DE variant called modified semi-adaptive DE (MSeDE) to solve this optimization problem. The results have been compared with two state-of-the-art and widely used variants of DE, namely JADE and SaDE, along with one improved variant of the Particle Swarm Optimization (PSO) algorithm, called comprehensive learning PSO (CLPSO). Moreover, we have compared the performance of MSeDE with a well-known constrained optimizer, called $$\varepsilon $$ ? -constrained DE with an archive and gradient-based mutation that ranked first in the competition on real-parameter constrained optimization, held under the 2010 IEEE Congress on Evolutionary Computation (CEC). Again to demonstrate the effectiveness of the optimization framework under consideration, we have included results obtained with a separate routing and sleep scheduling method in our comparative study. Our simulation results indicate that in all test cases, MSeDE can outperform the competitor algorithms by a good margin.

Optimal Prediction Likelihood Tree Based Source- Channel ML Decoder for Wireless Sensor Networks

In this work, we develop a framework for optimal joint Source-Channel Maximum Likelihood (SCML) decoding in Wireless Sensor Networks (WSNs). The proposed scheme employs a novel Generalized Likelihood Ratio Test based Prediction Likelihood Tree (PLT) approach to exploit the spatio-temporal narrowband properties of the sensor data for sequence detection in wireless sensor networks. Further, analytical bounds are derived to characterize the performance of the low complexity decision feedback and optimal Viterbi based Maximum Likelihood Sequence Detection (MLSD) for joint decoding over fading wireless channels, where only ad hoc schemes exist in current literature. The PLT based SCML scheme, which has a low complexity, is ideally suited for implementation in practical wireless sensor networks with limited computational power and achieves a performance close to the optimal MLSD bound. Simulation results are presented to validate the performance of the SCML algorithm and the proposed analytical bounds for sensor data reception in WSNs.

Joint routing, channel allocation and power control for real‐life wireless sensor networks

AbstractThe energy consumption of wireless sensor networks (WSNs) is a critical issue, because replacement of their batteries can be difficult or even impossible. It is well known that the radio is the most energy demanding part of the node. Therefore, efficient communications are imperative to increase the network lifetime. However, many issues arise in practical WSNs implementations because of the uncertainty and dynamics of the environment and the complexity constraints of the nodes. Routing protocol for low‐power and lossy networks (RPL) is one of the most widely implemented routing strategies because it deals with many of these practical issues. Unfortunately, this protocol does not adapt the nodes' transmission power nor the nodes' transmission channel. Nowadays, commercial motes have multi‐power and multi‐channel capabilities, and these can be used to reduce the network consumption and avoid the high collision probability that may arise in convergecast networks. In this paper, we enhance RPL to obtain a joint routing, transmission power control and channel allocation solution for real‐life WSNs. Two different strategies (minimum aggregated power and maximum probability delivery ratio) are designed and implemented in a WSN testbed with commercial motes. They are compared with the original RPL and also with other standard routing protocols, such as the routing strategy adopted in ZigBee. The experimental results show that the network performance is improved both in terms of reliability and energy consumption. Copyright © 2014 John Wiley & Sons, Ltd.

Events localisation and estimation in wireless sensor networks using compressed sensing

Events localisation and estimation are two major applications of wireless sensor networks (WSNs). However, owing to the noise of wireless sensing and transmission, it is difficult to guarantee the detection accuracy, especially in multiple events scenarios. This paper proposed a multiple events detection method based on compressive sensing (CS) to efficiently achieve the positions and the values of events simultaneously. Moreover, the high redundancy between the sparse signals of adjacent time slots is taken into account by distributed compressive sensing (DCS) to improve the detection accuracy. We also proposed an adaptive CS reconstruction algorithm to deal with the variable sparsity level in practical WSN scenarios. The simulation results show that the proposed method not only outperforms the traditional decentralised detection methods using Bayesian, but also perfectly handles the unknown sparsity level situations.

A Practical Monitoring System for the Structural Safety of Mega-Trusses Using Wireless Vibrating Wire Strain Gauges

Sensor technologies have been actively employed in structural health monitoring (SHM) to evaluate structural safety. To provide stable and real-time monitoring, a practical wireless sensor network system (WSNS) based on vibrating wire strain gauges (VWSGs) is proposed and applied to a building under construction. In this WSNS, the data measured from each VWSG are transmitted to the sensor node via a signal line and then transmitted to the master node through a short-range wireless communication module (operating on the Industrial, Scientific, and Medical (ISM) band). The master node also employs a long-range wireless communication module (Code Division Multiple Access—CDMA) to transmit the received data from the sensor node to a server located in a remote area, which enables a manager to examine the measured data in real time without any time or location restrictions. In this study, a total of 48 VWSGs, 14 sensor nodes, and seven master nodes were implemented to measure long-term strain variations of mega-trusses in an irregular large-scale building under construction. Based on strain data collected over a 16-month period, a quantitative evaluation of the construction process was performed to determine the aspects that exhibit the greatest influence on member behavior and to conduct a comparison with numerical simulation results. The effect of temperature stress on the structural elements was also analyzed. From these observations, the feasibility of a long-term WSNS based on VWSGs to evaluate the structural safety of an irregular building under construction was confirmed.

Distributed Broadcast with Minimum Latency in Asynchronous Wireless Sensor Networks under SINR-Based Interference

Data broadcast is a fundamental operation in wireless sensor networks (WSNs). The existence of wireless interference makes it nontrivial to design a minimum-latency broadcast scheme, which is known to be NP-hard. Existing works all assume strict time synchronization and provide centralized TDMA scheduling algorithms. However, WSNs in practice are more likely to be distributed asynchronous systems. In this paper, we investigate the problem of data broadcast with minimum latency for distributed asynchronous WSNs. To this end, we propose a Distributed Asynchronous Broadcast (DAB) algorithm which crucially leverages an elaborately optimized carrier-sensing range together with collision-backoff schemes to coordinate the transmissions among the nodes on a predetermined broadcast backbone. Theoretical analysis shows that DAB is order-optimal and achieves constant factor approximation to the optimal delay. We then conduct extensive simulations to evaluate the practical capability of DAB in asynchronous WSNs and the results corroborate our theoretical analysis.

Symbolic and Graphical Representation Scheme for Sensors Deployed in Large-Scale Structures

As wireless sensor network (WSN)-based structural health monitoring (SHM) systems are increasingly being employed in civil infrastructures and building structures, the management of large numbers of sensing devices and the large amount of data acquired from WSNs will become increasingly difficult unless systematic expressions of the sensor network are provided. This study introduces a practical WSN for SHM that consists of sensors, wireless sensor nodes, repeater nodes, master nodes, and monitoring servers. This study also proposes a symbolic and graphical representation scheme (SGRS) for this system, in which the communication relationships and respective location information of the distributed sensing components are expressed in a concise manner. The SGRS was applied to the proposed WSN, which is employed in an actual large-scale irregular structure in which three types of sensors (75 vibrating wire strain gauges, 10 inclinometers, and three laser displacement sensors) and customized wireless sensor nodes are installed. The application results demonstrate that prompt identification of sensing units and effective management of the distributed sensor network can be realized from the SGRS. The results also demonstrate the superiority of the SGRS over conventional expression methods in which a box diagram or tree diagram representing the ID of sensors and data loggers is used.

An advanced temporal credential-based security scheme with mutual authentication and key agreement for wireless sensor networks.

Wireless sensor networks (WSNs) can be quickly and randomly deployed in any harsh and unattended environment and only authorized users are allowed to access reliable sensor nodes in WSNs with the aid of gateways (GWNs). Secure authentication models among the users, the sensor nodes and GWN are important research issues for ensuring communication security and data privacy in WSNs. In 2013, Xue et al. proposed a temporal-credential-based mutual authentication and key agreement scheme for WSNs. However, in this paper, we point out that Xue et al.'s scheme cannot resist stolen-verifier, insider, off-line password guessing, smart card lost problem and many logged-in users' attacks and these security weaknesses make the scheme inapplicable to practical WSN applications. To tackle these problems, we suggest a simple countermeasure to prevent proposed attacks while the other merits of Xue et al.'s authentication scheme are left unchanged.

Passive cluster-based multipath routing protocol for wireless sensor networks

Energy efficiency and quality of service (QoS) are both essential issues in the applications of wireless sensor networks (WSNs) all along, which are mainly reflected in the development of routing and MAC protocols. However, there is little design for achieving the dual performances simultaneously. In this paper, we develop a practical passive cluster-based node-disjoint many to one multipath routing protocol to satisfy the requirements of energy efficiency and QoS in practical WSNs. Passive clustering approach is put to use in the first round, while active clustering technique is taken in the other rounds. Implementation of smart delay strategy makes the cluster distribute uniformly, as well as lessen the number of nodes that have taken part in routing. Among cluster heads, a node-disjoint many to one multipath routing discovery algorithm, which is composed of the optimal path searching process and multipath expansion process, is implemented to find multiple paths at the minimum cost. The simulation results show the proposed protocol achieved very good performance both in energy efficiency and QoS.

Energy‐efficient network design via modelling: optimal designing point for energy, reliability, coverage and end‐to‐end delay

Considering that practical wireless sensor networks are mostly built upon energy-constrained sensor nodes, network lifetime becomes a key deployment factor for sustainability of such networks initiating an attempt for prolonging the lifetime. Adopting a new multi-mode switching protocol for sensor nodes between active and sleep states, in this study, the authors propose a new mathematical method using an embedded simulation-based computing of an energy-efficient strategy performance metric to maintain resiliency of the network against side effects appearing in duty-cycling protocols. Here, the authors use a Monte Carlo simulation to estimate network reliability. Then the proposed mathematical model enables us to build a decision for optimised performance upon trade-offs between consumed energy, reliability, coverage intensity and end-to-end delays by locating a network's operational points. The authors show the trade-off operational significance of the model against the percentage of sleeping probability via some design factors including figure of merit.

Design of a miniaturized patch antenna for easy deployment on metal surfaces

Wireless sensor network (WSN) has become a hot topic lately. By using WSN things that previously were difficult or impossible to measure has now become available. One of the main reasons using WSN for monitoring is to save money by cost optimization and/or increase safety by letting the user knowing the physical status of the monitored structure. This thesis considers four main topics, empirical testing of WSN in harsh environments, antenna designs, antenna measurements and radio environment emulation.The WSN has been tested in train environment for monitoring of ball bearings and inside jet engines to monitor strain of blades and temperatures. In total, two investigations have been performed aboard the train wagon and one in the jet engine. The trials have been successful and provide knowledge of the difficulties with practical WSN applications. The key issues for WSN are robust communication, energy management (including scavenging) and physical robustness.For the applications of WSN in harsh environments antennas has to be designed. In the thesis, two antennas has been designed, one for train environment and one for the receiver in the jet engine. In the train environment, a more isotropic radiation pattern is preferable; hence a small dual layered patch antenna is designed. The antenna is at the limit of being electrically small; hence slightly lower radiation efficiency is measured. For the WSN in the jet engine, a directive patch array is designed on an ultra-thin and flexible substrate. The thin substrate of the antenna causes rather lower radiation efficiency. But the antenna fulfils the requirements of being conformal and directive.In reverberation chambers are used to measure antennas, but there are difficulties to provide a realistic radio environment, for example outdoor or on-body. In this thesis, a large reverberation chamber is designed and verified. It enables measurement between 400 MHz and 3 GHz. Also, a sample selection method is designed to provide a post processing possibilities to emulate the radio environment inside the chamber. The method is to select samples from a data set that corresponds to a desired probability density function. The method presented in this thesis is extremely fast but the implementation of the method is left for future research.

Energy Efficiency of the IEEE 802. 15. 4 Standard in Wireless Sensor Networks: Modeling and Improvement Perspectives

IEEE focuses on the physical and MAC layer of Wireless Sensor Networks (WSN) and the Internet Engineering Task Force (IETF) works on Network layer and higher in the seven layer OSI reference model for networking. The IEEE 802.15.4 standard, defines the physical layer (PHY) and medium access control (MAC) sub layer specifications for low-data-rate wireless connectivity with fixed, portable, and moving devices with no battery or very limited battery consumption requirements. In this paper, the energy consumption of a practical Wireless Sensor Network scenario is modeled at the bottom three layers of the traditional networking stack—the physical layer, data link layer and the MAC layer. Using these models, the optimization of energy consumption of WSN nodes is achieved using different modulation schemes to maximize the network lifetime. The approach is to design and simulate a wireless sensor network scenario consisting of 12 nodes in 500x500 m area and optimize the energy consumption (radio energy + circuit energy) of each node using suitable modulation techniques and reduce the Energy Consumption up to 80% in a home automation scenario.

Novel PIT Localization Algorithm based on Coverage of Anchors in WSN

Lots of applications in Wireless Sensor Networks (WSN) are related to location information. The cost of the hardware on WSN nodes hinder the application of distance-based localization technologies that depend on absolute point-to-point distance measurement. Schemes in distance-independent localization are being put forward instead of more expensive distance-based algorithm. APIT is one of typical distance-independent algorithms. But APIT algorithm requires that all participating anchor nodes are within a single hop from the location-unknown node (test node) and demands that nodes’ density is large enough to ensure that in any direction on the test node there exists at least one node, which is difficult to meet in practical WSN. Starting with APIT location algorithm in WSN, a novel Point In triangle Test (PIT) algorithm based on coverage of anchors is proposed in this paper. The novel algorithm looks for the anchors’ set within the intersection of coverage area formed by selected anchors and calculates the center of gravity of the anchors’ set. If the center of gravity is in the triangle formed by the selected anchors, the test node is inside the triangle. Otherwise, the test node is outside the triangle. The simulation results show that the accuracy of the novel algorithm is increased by about 20% compared with APIT algorithm.

Integration of dispenser-printed ultra-low-voltage thermoelectric and energy storage devices

This paper reports on an integrated energy harvesting prototype that consists of dispenser-printed thermoelectric energy harvesting and electrochemical energy storage devices. Parallel-connected thermoelectric devices with low internal resistances were designed, fabricated and characterized. The use of a commercially available dc-to-dc converter was explored to step-up a 27.1 mV input voltage from a printed thermoelectric device to a regulated 2.34 V output at a maximum of 34% conversion efficiency. The regulated power succeeds in charging dispenser-printed, zinc-based micro-batteries with charging efficiencies of up to 67%. The prototype presented in this work demonstrates the feasibility of deploying a printable, cost-effective and perpetual power solution for practical wireless sensor network applications.

Optimum Sensor Density in Distortion-Tolerant Wireless Sensor Networks

The optimum sensor node density for one- and two-dimensional (1-D and 2-D) wireless sensor networks (WSNs) with spatial source correlation is studied in this paper. The WSN attempts to reconstruct a spatially correlated signal field by collecting the location-dependent measurements from the distributed sensor nodes. The WSN is designed to minimize the mean square error (MSE) distortion between the original and the reconstructed signals under the constraint of a fixed power per unit area. The impacts of node density and spatial data correlation on the network performance are investigated for both small networks with finite number of nodes, and large networks with infinite area, infinite number of nodes, but finite node density through asymptotic analysis. The interactions among the various network parameters and their impacts on the system performance are quantitatively identified with exact analytical expressions, many of which are in closed-forms. The results provide guidelines on the design of practical WSNs.

A Lightweight Lap Time Measurement System for Alpine Ski Sport Using a TDMA-Based Linear Wireless Sensor Network

In Alpine ski sport, traditional lap time measurement systems record a skier's departure and arrival using time-of-day timers through wires, which is not cost effective in unofficial or training games. This paper develops a lightweight lap time measurement system using a wireless sensor network, which employs a practical TDMA-based linear wireless sensor network protocol for multihop communications in long strap-shaped environments where sensor nodes are linearly deployed. We evaluate the performance of this protocol through the implementation and deployment of the lap time measurement system. The experimental results show that the proposed protocol transmits data at a success rate of 99.66% and maintains the time synchronization errors between two adjacent nodes within 183 μs without using any other time synchronization protocols. In an experimental deployment for a 1.5 km ski slope covered by 31 nodes, the system provides lap time measurements with a measurement error of 1.255 ms, which satisfies the official measurement error of 5.0 ms.

Scale-free topology evolution for wireless sensor networks with reconstruction mechanism

How to improve survivability of wireless sensor networks (WSNs) is an important issue which has attracted much attention over recent years. In this paper, by resorting to complex network theories, we propose two models, namely, a linear growth evolution model (LGEM) and an accelerated growth evolution model (AGEM). In the model evolution processes, the following factors: node addition, node deletion, and link reconstruction that naturally arise from practical WSNs applications are considered. In addition, accelerated growth is introduced into the evolving processes of AGEM. Theoretical analysis shows that AGEM is an extension of the LGEM model, and AGEM is generally more flexible and accommodating in practice. Simulation results show that the degree distributions of two models have scale-free characteristics and the topologies generated by the two models show a good survivability under random and deliberate attacks.

Implementation and application of a multi-radio wireless sensor networks testbed

The authors propose EasiTest, a multi-radio testbed for heterogeneous wireless sensor networks (WSNs). Two types of sensor nodes, specifically, high-speed multi-radio node (EZ271) and low-speed single-radio node (EZ521) are developed. An administration platform is provided to monitor and control the testbed. EasiTest enjoys high flexibility, powerful processing capability and ease of expansion. EasiTest provides a powerful tool not only for the study and evaluation of large-scale, heterogeneous sensor networks, but also for quick prototyping of practical WSN applications. To demonstrate the capability of the testbed, the co-existence problem of IEEE 802.11 and IEEE 802.15.4 is studied. Guidelines are given on channel allocation and network parameter configuration to minimise the interference. In addition, to demonstrate the flexibility of the testbed, the authors evaluate robust opportunistic scheduling for ad hoc networks, a distributed opportunistic scheduling protocol, based on the testbed. The experimental results match with the simulation results very well.

A single hop architecture exploiting cooperative beamforming for wireless sensor networks

In this paper, we propose a single hop architecture for a cooperative wireless sensor network and analyze the attained distributed beamforming gain performance using the theory of random arrays. All nodes in the system transmit a single carrier such that the signals add up constructively towards the direction of the fusion center. The potential directive beamforming gains are investigated for different sensor network densities which are expressed as the number of nodes per carrier wavelength squared. The multiple access capability of the sensor network is achieved by employing an on-off keying orthogonal signaling technique, which is usually employed in atmospheric optical systems. Finally, we investigate the average loss in directivity gain when the received signal from each sensor node follows a Ricean distribution. The results show that high directive gains can be achieved in practical wireless sensor networks using simple sensor nodes.