Wireless Sensor Network Research Research Articles

Solar-Powered Wireless Sensor Network’s Energy Gathering Technology

We analyze the solar-powered wireless sensor network's energy gathering techniques, aiming to prolong the lifetime of wireless sensor network. We summarize wireless sensor network node's energy autonomy system, its characteristics in detail and new technology adopts, provides some suggestions and new ideas in the design and research of solar-powered wireless sensor networks.

Dempster–Shafer theory-based human activity recognition in smart home environments

Context awareness and activity recognition are becoming a hot research topic in ambient intelligence (AmI) and ubiquitous robotics, due to the latest advances in wireless sensor network research which provides a richer set of context data and allows a wide coverage of AmI environments. However, using raw sensor data for activity recognition is subject to different constraints and makes activity recognition inaccurate and uncertain. The Dempster–Shafer evidence theory, known as belief functions, gives a convenient mathematical framework to handle uncertainty issues in sensor information fusion and facilitates decision making for the activity recognition process. Dempster–Shafer theory is more and more applied to represent and manipulate contextual information under uncertainty in a wide range of activity-aware systems. However, using this theory needs to solve the mapping issue of sensor data into high-level activity knowledge. The present paper contributes new ways to apply the Dempster–Shafer theory using binary discrete sensor information for activity recognition under uncertainty. We propose an efficient mapping technique that allows converting and aggregating the raw data captured, using a wireless senor network, into high-level activity knowledge. In addition, we propose a conflict resolution technique to optimize decision making in the presence of conflicting activities. For the validation of our approach, we have used a real dataset captured using sensors deployed in a smart home. Our results demonstrate that the improvement of activity recognition provided by our approaches is up to of 79 %. These results demonstrate also that the accuracy of activity recognition using the Dempster–Shafer theory with the proposed mappings outperforms both naive Bayes classifier and J48 decision tree.

Positioning Research for Wireless Sensor Networks Based on PSO Algorithm

Based on the traditional DV-Hop algorithm and in order to overcome its existing drawbacks, an improved DV-Hop algorithm is brought forward in this paper by using the PSO algorithm. Through simulation experiments, it is found that both the average localization error and the localization coverage rate of PSO are better than that of DV-Hop. Moreover, with the increase of the number of nodes, the average localization error of PSO shows a downward trend and is less than that of DV-Hop. DOI: http://dx.doi.org/10.5755/j01.eee.19.9.5522

An Efficient Grid-Based Pairwise Key Predistribution Scheme for Wireless Sensor Networks

Research on wireless sensor networks (WSNs) has been receiving a lot of attention recently. Because of the constraints on the cost of hardware, there are a lot of restrictions regarding memory, computational ability, and energy consumption, hampering WSN research. So far, many key establishment schemes have been proposed for WSNs. For the proposed schemes, random key predistribution is a practical solution. With this, each sensor shares a common key with its neighbors via predistributed keys. However, it may happen that two sensor nodes do not share a common key. In this paper, an efficient grid-based pairwise key predistribution scheme for WSNs is proposed. In the proposed scheme, multiple polynomials for each row, each column, and each diagonal in the grid are constructed. Then, each sensor node in each row, column, and diagonal in the grid establishes a pairwise key with the other node using the predistributed symmetric polynomial. Simulation results demonstrate the effectiveness of the proposed scheme in increasing the probability of establishing pairwise keys and reducing communication overhead.

Wireless sensor networks: a survey on recent developments and potential synergies

Wireless sensor network (WSN) has emerged as one of the most promising technologies for the future. This has been enabled by advances in technology and availability of small, inexpensive, and smart sensors resulting in cost effective and easily deployable WSNs. However, researchers must address a variety of challenges to facilitate the widespread deployment of WSN technology in real-world domains. In this survey, we give an overview of wireless sensor networks and their application domains including the challenges that should be addressed in order to push the technology further. Then we review the recent technologies and testbeds for WSNs. Finally, we identify several open research issues that need to be investigated in future. Our survey is different from existing surveys in that we focus on recent developments in wireless sensor network technologies. We review the leading research projects, standards and technologies, and platforms. Moreover, we highlight a recent phenomenon in WSN research that is to explore synergy between sensor networks and other technologies and explain how this can help sensor networks achieve their full potential. This paper intends to help new researchers entering the domain of WSNs by providing a comprehensive survey on recent developments.

Marmote SDR: Experimental Platform for Low-Power Wireless Protocol Stack Research

Over the past decade, wireless sensor network research primarily relied on highly-integrated commercial off-the-shelf radio chips. The rigid silicon implementation of the radio stack restricted access to the lower layers; thus, research focused mainly on the medium access control (MAC) layer and above. SRAM field-programmable gate array (FPGA)-based software-defined radios (SDR), on the other hand, provide a flexible architecture to experiment with any and all layers of the radio stack, but usually require desktop computers and draw high currents that prohibit mobile or longer-term outdoor deployments. To address these issues, we have developed a modular flash FPGA-based wireless research platform, called Marmote SDR, that has computational resources comparable to those of SRAM FPGA-based radio platforms, but at a reduced power consumption, with duty cycling support. We discuss the design decisions underlying Marmote SDR and evaluate its power consumption. Furthermore, we present and evaluate an asynchronous and multiple access communication protocol specifically designed for data-gathering wireless sensor networks.

Applied to Medical Monitoring of the Wireless Sensor Network Design and Research

Along with the computer technology and the rapid development of communication network, wireless network sensor will be exploring new medical mode, a breakthrough in the medical field, the main monitoring and measuring the human body physiological parameters, for the human body can be all kinds of condition monitoring, data transfer to all kinds of communication terminal. Without having to leave home, monitoring their own physical condition anytime, anywhere and the test results, in the form of network transmission will be updated to medical personnel information database, doctors and patients are more closely connected on a timely base and effective communication and treatment can be easily carried out.

Research of Underground Wireless Sensor Networks Based on CC1110

In view of the harsh and variable underground environment, the current existing coal mine monitoring system is difficult to expand and has monitoring blind spot. Based on CC1110 chip and SimpliciTI network protocol, we present a design scheme of underground wireless sensor network which relies on automatic monitoring and alarm to the mine area environmental parameters. First, introduces the system composition structure, and the hardware design of independent communication subnet. Secondly, explains the system network protocol, network access mechanism used of periodic synchronous, and channel prediction. Finally, describes the software design of monitoring nodes. The test results show that the network nodes have many characteristics such as long-distance communication, movability, build up flexibly, high stability, and so on.

Energy Constraints of Localization Techniques in Wireless Sensor Networks (WSN): A Survey

Sensor Network (WSN) localization is an important and fundamental problem that has received a lot of attention from the WSN research community. Determining the absolute and relative coordinate of sensor nodes in the network adds much more meaning to sense data. The research community is very rich in proposals to address this challenge in WSN. This paper, explores the various techniques proposed to address the acquisition of location information in WSN. The paper also evaluate the performance of these techniques based on the energy consumption, the skill and man hours needed to implement the technique and localization accuracy (error rate) and discuss some open issues for future research. Keywordssensor network, sensor nodes, localization centralized and distributed algorithm, range-based and range- free algorithm.

Sleep–wake up scheduling with probabilistic coverage model in sensor networks1

Energy optimisation is one of the important issues in the research of wireless sensor networks (WSNs). In the application of monitoring, a large number of sensors are scattered uniformly to cover a collection of points of interest (PoIs) distributed randomly in the monitored area. Since the energy of battery-powered sensor is limited in WSNs, sensors are scheduled to wake up in a large-scale sensor network application. In this paper, we consider how to reduce the energy consumption and prolong the lifetime of WSNs through wake-up scheduling with probabilistic sensing model in the large-scale application of monitoring. To extend the lifetime of sensor network, we need to balance the energy consumption of sensors so that there will not be too much redundant energy in some sensors before the WSN terminates. The detection probability and false alarm probability are taken into consideration to achieve a better performance and reveal the real sensing process which is characterised in the probabilistic sensing model. Data fusion is also introduced to utilise information of sensors so that a PoI in the monitored area may be covered by multiple sensors collaboratively, which will decrease the number of sensors that cover the monitored region. Based on the probabilistic model and data fusion, minimum weight probabilistic coverage problem is formulated in this paper. We also propose a greedy method and modified genetic algorithm based on the greedy method to address the problem. Simulation experiments are conducted to demonstrate the advantages of our proposed algorithms over existing work.

Advancements of Data Anomaly Detection Research in Wireless Sensor Networks: A Survey and Open Issues

Wireless Sensor Networks (WSNs) are important and necessary platforms for the future as the concept “Internet of Things” has emerged lately. They are used for monitoring, tracking, or controlling of many applications in industry, health care, habitat, and military. However, the quality of data collected by sensor nodes is affected by anomalies that occur due to various reasons, such as node failures, reading errors, unusual events, and malicious attacks. Therefore, anomaly detection is a necessary process to ensure the quality of sensor data before it is utilized for making decisions. In this review, we present the challenges of anomaly detection in WSNs and state the requirements to design efficient and effective anomaly detection models. We then review the latest advancements of data anomaly detection research in WSNs and classify current detection approaches in five main classes based on the detection methods used to design these approaches. Varieties of the state-of-the-art models for each class are covered and their limitations are highlighted to provide ideas for potential future works. Furthermore, the reviewed approaches are compared and evaluated based on how well they meet the stated requirements. Finally, the general limitations of current approaches are mentioned and further research opportunities are suggested and discussed.

RRSEB: A Reliable Routing Scheme for Energy-balancing Using a Self-adaptive Method in Wireless Sensor Networks

Over recent years, enormous amounts of research in wireless sensor networks (WSNs) have been conducted, due to its multifarious applications such as in environmental monitoring, object tracking, disaster management, manufacturing, monitoring and control. In some of WSN applications dependent the energy-efficient and link reliability are demanded. Hence, this paper presents a routing protocol that considers these two criteria. We propose a new mechanism called Reliable Routing Scheme for Energy-Balanced (RRSEB) to reduce the packets dropped during the data communications. It is based on Swarm Intelligence (SI) using the Ant Colony Optimization (ACO) method. The RRSEB is a self-adaptive method to ensure the high routing reliability in WSNs, if the failures occur due to the movement of the sensor nodes or sensor node’s energy depletion. This is done by introducing a new method to create alternative paths together with the data routing obtained during the path discovery stage. The goal of this operation is to update and offer new routing information in order to construct the multiple paths resulting in an increased reliability of the sensor network. From the simulation, we have seen that the proposed method shows better results in terms of packet delivery ratio and energy efficiency.

A survey on energy awareness mechanisms in routing protocols for wireless sensor networks using optimization methods

ABSTRACTOver recent years, enormous amounts of research in wireless sensor networks (WSNs) have been conducted; this is because of its multifarious applications such as in environmental monitoring, object tracking, disaster management, manufacturing, monitoring and control. Nevertheless, optimising the energy consumption of sensor nodes (SNs) in WSNs and realising the anticipated quality of solutions supplied from them present considerable challenges. In WSNs, the sudden ‘death’ of critical nodes can cause an entire network to malfunction. This is usually caused by uneven depletion of battery power of the individual nodes. Therefore, this survey investigates the methods that aim to minimise usage of energy in SNs, especially during routing. This is because network activities start to be challenged when the first SN exhausts its battery. In addition, this paper introduces a comprehensive categorization of the energy‐aware protocols in WSNs. Thus, the motivation of this survey is to present some decentralised energy‐aware routing using optimization methods that is generic and applicable to most of WSN applications that require reduction of energy consumptions and extend a network's life time. Copyright © 2013 John Wiley & Sons, Ltd.

OPCPP: An Online Plug-Configure-Play Experiment Platform for WSN

Wireless sensor network (WSN) experiment platforms are used for teaching, research, and development of WSN. However, existing WSN experiment platforms generally have the following disadvantages: tedious manual operations, invasive measurement method, poor sensor self-awareness, and low resource utilization rate. To address the above problems, this paper proposes OPCPP, an online Plug-Configure-Play experiment platform for WSN. It has four prominent strongpoints: in-application programming in batch, noninvasive measurement method, sensor self-awareness, and remote operation. OPCPP has been used in eight colleges in China for teaching course of “internet of things” till now. We also develop a sensor-aware ZigBee-based smart home system prototype based on OPCPP.

Qos Management in Wireless Sensor Networks using LFQMS

Wireless sensor networks (WSNs) are emerging rapidly as a new generation of sensor networks. Despite intensive research in wireless sensor networks (WSNs), limited work has been found in the open literature in the field of WSNs. In particular, quality-of-service (QoS) management in WSNs remains an important issue yet to be investigated. As an attempt in this direction, this paper develops a logic for QoS management (LFQMS) scheme for WSNs with constrained resources and in dynamic and unpredictable environments. Taking advantage of the feedback control technology, this scheme deals with the impact of unpredictable changes in traffic load on the QoS of WSNs. It utilizes a logic controller inside each source sensor node to adapt sampling period to the deadline miss ratio associated with data transmission from the sensor to the sensor. The deadline miss ratio is maintained at a pre-determined desired level so that the required QoS can be achieved. The (LFQMS) has the advantages of generality, scalability, and simplicity. Simulation results show that the (LFQMS) can provide WSNs with QoS support.

Design and application of sink node for wireless sensor network

PurposeThe purpose of this paper is to present one type of the architecture for wireless sensor network and to discuss in detail the hardware design of the sink node which can be responsible for transmission data or instructions between sensor nodes and data. Finally, an experiment based on wireless sensor network has proved that the design of sink node is applicable and reliable in monitoring environmental elements such as temperature, humidity, etc.Design/methodology/approachA design for the sink node is presented which constants three parts: the power module, the storage/display module and the communication module. Zigbee, GPRS and Ethernet techniques are used on ARM7 microcontroller. The sink node is capable of bridging the user's terminal with sensor nodes for information transmission.FindingsIn this paper, a new method of the power management based on wireless sensor network is proposed to conserve energy. The antenna height is proven to be an important factor to the communicating among nodes. Finally, the paper proposes regular patterns of the deployment for sensor nodes based on the communication range and the sampling range.Originality/valueThe experiment for providing real‐time data on environment monitoring parameters indicates that the system is efficient. The authors believe that the idea and the design presented in the paper may help the research and application of wireless sensor network.

A Stochastic Model for Environment Sensing Correction

Wireless Sensor Networks (WSN) are growing in popularity and penetrating newer fields of applications more than ever. Gradually, we are relying on WSNs to perform more complex tasks with increasing cognitive abilities. At the core of the WSN research transpires, the need is to achieve accurate sensing at real-time. Unfortunately, confidence in sensors’ readings decreases in harsh environments and as a result of normal reading errors, message loss, or even low battery operations. The complex problem of dealing with corrections and in some cases shredding the outcome of entire deployments leads to loss of effort, time, and money. Classic approaches for correcting laboratory experiments like curve fitting and least square are well known and have been established for decades. But little research attempts have been made to correct and recalibrate sensors observations in real-time. Furthermore, classic approaches for correcting sensor observations require higher interaction between sensors to a level we cannot afford in deployments where battery, network, and memory represent scarce resource. In addition, classical corrections lack the ability to contemplate the physical properties of the underlying sensor environment. In this article, we present a sensor correction model that relies on clustered WSN. Our approach employs autonomous selection mechanism to elect cluster heads by applying a stochastic competition between cluster members while maintaining the underlying physical properties as the bases to locate competition winner. Then, we perform the stochastic competitive correction at real-time by referencing the underlying physical properties of the environment represented by selected relation as suggested by the physics of the environment. Finally, sensors adapt the minor changes and maintain a relation to their surroundings by continuously monitoring and assimilating information received from surrounding sensors. We show that this approach has smaller footprint in terms of processing, communicating, and storage. We present our approach and apply it on an environment of known physical property.

The Dynamic Optimization Strategy Research of Wireless Sensor Network Based on Multi-populations Cultural Framework

The Dynamic Optimization Strategy Research of Wireless Sensor Network Based on Multi-populations Cultural Framework

Efficient and secure chaotic S‐Box for wireless sensor network

ABSTRACTInformation security using chaotic dynamics is a novel topic in the wireless sensor network (WSN) research field. After surveying analog and digital chaotic security systems, we give a state of the art of chaotic S‐Box design. The substitution tables are nonlinear maps that strengthen and enhance block crypto‐systems. This paper deals with the design of new dynamic chaotic S‐Boxes suitable for implementation on wireless sensor nodes. Our proposed schemes are classified into two categories: S‐Box based on discrete chaotic map with floating point arithmetic (cascading piecewise linear chaotic map and a three‐dimensional map) and S‐Box based on discrete chaotic map with fixed‐point arithmetic (using discretized Lorenz map and logistic–tent map). The security analysis and implementation process on WSN are discussed. The proposed methods satisfy Good S‐Box design criteria and exceed the performance of Advanced Encryption Standard static S‐Box in some cases. The energy consumption of different proposals and existing chaotic S‐Box designs are investigated via a platform simulator and a real WSN testbed equipped with TI MSP430f1611 micro‐controller. The simulations and the experimental results show that our proposed S‐Box design with fixed‐point arithmetic Lorenz map has the lowest energy‐consuming profile compared with the other studied and proposed S‐Box design. Copyright © 2013 John Wiley & Sons, Ltd.

Adaptive routing in wireless sensor networks: QoS optimisation for enhanced application performance

One of the key challenges for research in wireless sensor networks is the development of routing protocols that provide application-specific service guarantees. This paper presents a new cluster-based Route Optimisation and Load-balancing protocol, called ROL, that uses various Quality of Service (QoS) metrics to meet application requirements. ROL combines several application requirements, specifically it attempts to provide an inclusive solution to prolong network life, provide timely message delivery and improve network robustness. It uses a combination of routing metrics that can be configured according to the priorities of user-level applications to improve overall network performance. To this end, an optimisation tool for balancing the communication resources for the constraints and priorities of user applications has been developed and Nutrient-flow-based Distributed Clustering (NDC), an algorithm for load balancing is proposed. NDC works seamlessly with any clustering algorithm to equalise, as far as possible, the diameter and the membership of clusters. This paper presents simulation results to show that ROL/NDC gives a higher network lifetime than other similar schemes, such Mires++. In simulation, ROL/NDC maintains a maximum of 7% variation from the optimal cluster population, reduces the total number of set-up messages by up to 60%, reduces the end-to-end delay by up to 56%, and enhances the data delivery ratio by up to 0.98% compared to Mires++.