Three-dimensional Wireless Sensor Networks Research Articles

Directional source localization based on RSS-AOA combined measurements

Source localization plays an indispensable role in many applications. This paper addresses the directional source localization problem in a three-dimensional (3D) wireless sensor network using hybrid received-signal-strength (RSS) and angle-of-arrival (AOA) measurements. Both the position and transmission orientation of the source are to be estimated. In the considered positioning scenario, the angle and range measurements are respectively corresponding to the AOA model and RSS model that integrates the Gaussian-shaped radiation pattern. Given that the localization problem is non-convex and the unknown parameters therein are coupled together, this paper adopts the second-order cone relaxation and alternating optimization techniques in the proposed estimation algorithm. Moreover, to provide a performance benchmark for any localization method, the corresponding Cramer-Rao lower bounds (CRLB) of estimating the unknown position and transmission orientation of the source are derived. Numerical and simulation results demonstrate that the presented algorithm effectively resolves the problem, and its estimation performance is close to the CRLB for the localization with the hybrid measurements.

An Energy-Aware Data Transmission Scheme under the Guarantee of Reliability for 3D WSNs

Three-dimensional wireless sensor networks (3D WSNs) play an important role to provide data collection services for Internet of things (IoT) in the real applications. However, many of the existing WSN data collection researches are based on a relatively simple linear or plane network model. The three-dimensional space problems are simplified to two-dimensional plane, which limits the applicability. In this paper, the data collection in 3D WSN is studied. In the three-dimensional space, we firstly analyze the data loads, energy consumption, and end-to-end (E2E) delay of each node when the network is following the shortest path routing. The mathematical analysis of data loads and E2E delay of each node are presented. Based on the analysis of data loads and energy consumption, an energy-ware data transmission scheme is proposed to achieve the trade-off optimization between the E2E delay and network lifetime under the guarantee of the transmission reliability. The key point of the proposed scheme is to make fully use of the unbalanced energy consumption of the 3D WSN. The performance of the proposed scheme is discussed, analyzed, and evaluated. The theoretical analysis and simulation results show that the E2E network delay and energy efficiency can be improved under the constraint of transmission reliability.

Routing Clustering Protocol for 3D Wireless Sensor Networks Based on Fragile Collection Ant Colony Algorithm

Compared with two-dimensional wireless sensor networks (2DWSNs), three-dimensional wireless sensor networks (3DWSNs) have higher node energy consumption and weaker load balancing. To alleviate these problems, we propose a new multi-hop routing clustering protocol for a wide range of 3DWSNs. In terms of clustering, nodes will run for cluster head (CH) by timing broadcast based on their remaining energy and their average distance from surrounding nodes. Two new identity nodes are added between the CH and the member nodes, the load transfer node responsible for transferring the energy consumption of the CH, and the secondary cluster head node (SCH) acting as the CH for the next round. In order to reduce energy consumption in key node areas, we also enable key nodes to communicate directly with the sink node. In the aspect of routing construction, SN generates the routing table corresponding to each CH through our proposed fragile ant colony algorithm. Because CH and SCH exist at the same time and have a certain replacement order, the SN only needs to obtain the location of each CH when the network is first clustered, and can continuously generate a new routing table corresponding to the CH, which reduces the energy consumption of the network in the routing path construction. We simulate this protocol, LEACH protocol, AZ-SEP protocol, and UCNPD protocol in a three-dimensional environment. The results show that this protocol is better than the other three protocols in terms of network lifetime and network load balance, respectively.

Performing Data Assessment in Terms of Sensor Node Positioning over Three Dimensional Wireless Sensor Network

The formation of groups over the three-dimensional wireless sensor networks experiences increased overlying of signals because of circular range resulting in data duplications within the network. For addressing the disputes the intention is to model a sensing mechanism for the three-dimensional wireless sensor networks based on standards termed as three-dimensional scattered grouping (3D – SG) scheme. Based on the 3D – SG scheme precise data mining resembles a crucial dispute because of the surrounding noise where the group head node collects and calculates the data over each and every group. Therefore for mining accurate data in each and every group, the intention is to design three-dimensional data assessment (3D – DA) scheme. Additionally, the node positioning policies portray a crucial feature in increasing the data precision in three-dimensional wireless sensor networks. For several cases, the sensor nodes are positioned erratically but for both, the conditions they are not conscious about their positioning for mining increased data in terms of precision. Hence the positioning of nodes in their precise location over the three-dimensional wireless sensor networks is quite an intricate process. The intention is to design a three-dimensional node positioning scheme for locating probable nodes and their positioning policies for increasing the data precision within the network.

Node optimization coverage method under link model in passive monitoring system of three-dimensional wireless sensor network

3D coverage is not only closer to the actual application environment, but also a research hotspot of sensor networks in recent years. For this reason, a node optimization coverage method under link model in passive monitoring system of three-dimensional wireless sensor network is proposed in this article. According to wireless link-aware area, the link coverage model in three-dimensional wireless sensor network is constructed, and the cube-based network coverage is used to represent the quality of service of the network. This model takes advantage of the principle that the presence of human beings can change the transmission channel of the link. On this basis, the intruder is detected by the data packets transmitted between the wireless links, and then the coverage area is monitored by monitoring the received signal strength of the wireless signal. Based on this new link awareness model, the problem of optimal coverage deployment of the receiving node is solved, that is, how to deploy the receiving node to achieve the optimal coverage of the monitoring area when the location of the sending node is given. In the process of optimal coverage, the traditional genetic algorithm and particle swarm optimization algorithm are introduced and improved. Based on the genetic algorithm, the particle swarm optimization algorithm which integrates the idea of simulated annealing is regarded as an important operator of the genetic algorithm, which can converge to the optimal solution quickly. The simulation results show that the proposed method can improve the network coverage, converge quickly, and reduce the network energy consumption. In addition, we set up a real experimental environment for coverage verification, and the experimental results verify the feasibility of the proposed method.

An Efficient Hybrid RSS-AoA Localization for 3D Wireless Sensor Networks.

Wireless sensor networks (WSNs) enable many applications such as intelligent control, prediction, tracking, and other communication network services, which are integrated into many technologies of the Internet-of-Things. The conventional localization frameworks may not function well in practical environments since they were designed either for two-dimensional space only, or have high computational costs, or are sensitive to measurement errors. In order to build an accurate and efficient localization scheme, we consider in this paper a hybrid received signal strength and angle-of-arrival localization in three-dimensional WSNs, where sensors are randomly deployed with the transmit power and the path loss exponent unknown. Moreover, in order to avoid the difficulty of solving the conventional maximum-likelihood estimator due to its non-convex and highly complex natures, we derive a weighted least squares estimate to estimate jointly the location of the unknown node and the two aforementioned channel components through some suitable approximations. Simulation results confirm the effectiveness of the proposed method.

Target Detection Coverage Algorithm Based on 3D-Voronoi Partition for Three-Dimensional Wireless Sensor Networks

The detection of target events is an important research area in the field of wireless sensor networks (WSNs). In recent years, many researchers have discussed the problem of WSN target coverage in a two-dimensional (2D) coordinate system. However, the target detection problem in a 3D coordinate system has not been investigated extensively, and it is difficult to improve the network coverage ratio while ensuring reliable performance of WSN. In addition, sensor nodes that are initially deployed randomly cannot achieve accurate target coverage in practice. Moreover, it is necessary to consider the energy consumption factor owing to the limited energy of the sensor node itself. Hence, with the objective of addressing the target event coverage problem of WSNs in 3D space applications, this paper proposes a target detection coverage algorithm based on 3D-Voronoi partitioning for WSNs (3D-VPCA) in order to ensure reliable performance of the entire network. First, we extend Voronoi division based on the 2D plane, which allows 3D-Voronoi partitioning of sensor nodes in 3D regions. Then, it is optimized according to the 3D-Voronoi neighbouring node partitioning characteristics and combined with the improved algorithm. Next, we set the priority coverage mechanism and introduce the correlation force between the target point and the sensor node in the algorithm, so that the sensor node can move to the target position for accurate coverage. Finally, we carry out related simulation experiments to evaluate the performance and accuracy of the proposed algorithm. The results show that the proposed algorithm can effectively improve the coverage performance of the network while ensuring a high overall coverage ratio.

Localization in three-dimensional wireless sensor networks: a survey

Localization is a process of finding the coordinates of the deployed sensor nodes in the sensing area. Localization in wireless sensor networks (WSNs) is important as it results in location-stamped communication. Applications of WSNs like forest fire detection, nuclear or biological attacks, locating survivors post-disasters, etc. require location-aware information for real time and accurate response. Generally, the sensor nodes are not equipped with global positioning system due to its inefficiency for indoor and underwater regions. Other drawbacks include cost and power consumption. Localization in 3D WSNs is a complex task. The complexity increases due to an additional dimension leading to larger neighboring nodes and increase in coverage area (i.e., area coverage of a sensor node changes from circular to spherical). A lot of approaches have been proposed to localize the sensor nodes in 2D and are now being seen in 3D aspect. Although good efforts have been made for research summarization and guidance in 2D localization, it lacked attention by the researchers in 3D scope. This paper provides a comprehensive survey of the algorithms designed for localizing the sensor nodes in terrestrial and underwater regions. These algorithms have been classified based on the nature of anchor nodes. The localization methods have been categorized as static anchor node-based or mobile anchor node-based and further range-free or range-based depending upon the number of anchor nodes availability and distance estimation technique, respectively. The limitations and challenges of the proposed approaches have also been discussed briefly. The paper also tabulates these methods on the basis of attributes like localization process, complexity, number of sensor nodes used, etc.

A Novel Localization Method Based on RSS-AOA Combined Measurements by Using Polarized Identity

This paper proposes a novel scheme to solve the target localization problem by using combined measurements of received signal strength and angle-of-arrival (AOA) hybrid measurements in three-dimensional (3D) wireless sensor networks (WSNs). The proposed scheme can work effectively in both cases of known and unknown target transmit power. In the known transmit power case, by using polarized identity, we transform the available AOA measurements into a norm form and establish new relationships between the AOA measurements and the unknown target location, a novel target localization method is then proposed by using the second-order cone programming relaxation technique. Furthermore, we demonstrate that by using mean inequality, the proposed method can be effectively extended to the unknown transmit power case. In this case, we propose a practical alternating estimation procedure which alternatively estimates the target location and transmit power. Computer simulations are carried out to demonstrate that comparing with other methods, the proposed method can achieve significant performance gains for different settings in 3D WSNs.

RSS-AOA-Based Localization via Mixed Semi-Definite and Second-Order Cone Relaxation in 3-D Wireless Sensor Networks

In this paper, the target node localization problems based on hybrid RSS-AOA measurements in both noncooperative and cooperative three-dimensional (3-D) wireless sensor networks (WSNs) are discussed. By using novel error approximate expressions for both received signal strength (RSS) and angle-of-arrival (AOA) measurement models, new estimators based on the least squares (LS) criterion are proposed. These estimators can be transformed into mixed semi-definite programming (SDP) and second-order cone programming (SOCP) problems by applying convex relaxation techniques. In addition, the closed-form Cramer-Rao lower bound (CRLB) of the estimator on hybrid measurements in cooperative WSNs is also derived. Theoretical analysis and simulation results show that the Root Mean Square Error (RMSE) of the proposed hybrid RSS-AOA estimators is lower than that of the discussed estimators in both noncooperative and cooperative cases.

An Energy-Optimization Clustering Routing Protocol Based on Dynamic Hierarchical Clustering in 3D WSNs

An important issue in the three-dimensional (3D) wireless sensor networks (WSNs) is sensor energy optimization. To alleviate this issue, we introduce a new 3D spherical network structure model, and by combining the original energy consumption model to construct a new method to determine the optimal number of clusters and balance the total energy consumption. Since the different sizes of the clusters are generated by traditional hierarchical clustering, it causes unbalanced energy consumption in the network. To alleviate this problem, we adopt an improved dynamic hierarchical clustering method and implement two strategies that include the following three contributions: the introduction of the distance similarity index to get a better clustering, a double cluster head (CH) strategy to reduce the load of a cluster head in a large cluster, and a node dormancy mechanism to balance the energy consumption of the network. In addition, we also propose the optimal cluster-head function to select the CH of each cluster in each round, and the optimal cluster-head function is constructed based on the residual energy and positions of the nodes. Finally, to optimize the CH election strategy, several parameters of the optimal cluster-head function are determined according to the network structure. The simulation results show that our routing protocol is more robust compared with four other protocols, which is of great significance for the application in 3D environment monitoring.

Fault-tolerant and energy-efficient routing protocols for a virtual three-dimensional wireless sensor network

In this paper, we consider a low-density, three-dimensional Wireless Sensor Network (3D WSN for short) in which the distribution of the sensors is poor, and the 3D virtual architecture proposed in our previous work. This later architecture provides a powerful, fast and economic partitioning of the network into a set of easily manageable clusters. We derive a fault-tolerant and energy-efficient routing protocol that allows efficient broadcasts of the data collected by the sensor nodes to a base station – a sink node located at the center of the network. Unlike existing routing protocols that run only on dense Networks ours is reliable on any type of 3D WSN: dense, sparse or non-connected. It can lead to the development of efficient algorithms for many applications as multicast, geocast, data aggregation, data collection with authentication and security.

Improved the Network Lifetime Through Energy Balancing in Depth Based Routing Protocol for Underwater Sensor Network

Underwater Wireless Sensor Network (UWSN) is a three-dimensional wireless sensor network which works under water and used acoustic signals for transmission. In underwater communication, energy efficiency in routing is play a vital role due to the distinctive characteristics, such as water currents, limited battery power, and long acoustic propagation delay. Due to the water undercurrents sensor nodes moves uninterruptedly and makes dynamic and complex network topology. Depth-based routing protocol (DBR) is much usable protocol in underwater scenario, because it uses only depth information only which is easier to obtain. However, in DBR, packets may be forwarded through multiple paths and some sensor nodes are frequently used to transmit data which is nearer to the surface sink, might cause energy waste as well as moderate the life of network. In this article, we propose an energy balancing scheme for DBR to provide energy efficient routing and to increase the life of network.

Improved range-free localization for three-dimensional wireless sensor networks using genetic algorithm

This paper presents a distributed range-free node localization algorithm for three-dimensional (3D) wireless sensor networks (WSNs), named as 3D-GAIDV Hop (3D genetic algorithm based Improved Distance Vector Hop). In the proposed algorithm, the average hop size of anchor nodes is modified by updating a correction factor and the modified hop size is further optimized by line search algorithm. The concept of coplanarity is introduced to reduce location errors caused by the anchor nodes which are coplanar. The localization accuracy is further improved by applying genetic algorithm (GA). To improve the positioning coverage of the network, those target nodes which have been localized successfully in the first round of the localization process, are upgraded to assistant anchor node. All the processes and calculations are carried out at target node level, which makes the proposed algorithm energy efficient. Simulation results show that our proposed algorithm outperforms the similar kind of existing algorithms.

Virtual Architecture and Energy Efficient Routing Protocols for 3D Wireless Sensor Networks

This paper proposes a virtual architecture for three-dimensional (3D) wireless sensor networks (WSNs), a dynamic coordinate system, and a scalable energy-efficient training protocol for collections of nodes deployed in the space that are initially anonymous, asynchronous, and unaware of their initial location. The 3D WSNs considered comprise massively deployed tiny energy-constrained commodity sensors and one or more sink nodes that provide an interface to the outside world. The proposed architecture is a generalization of a two-dimensional virtual architecture previously proposed in the literature, in which a flexible and intuitive coordinate system is imposed onto the deployment area and the anonymous nodes are partitioned into clusters where data can be gathered from the environment and synthesized under local control. The architecture solves the hidden sensors problem that occurs because of irregularities in rugged deployment areas or environments containing buildings by training the network of nodes arbitrarily dispersed in the 3D space. In addition, we derive two simple and energy-efficient routing protocols, respectively for dense and sparse networks, based on the proposed dynamic coordinate system. They are used to minimize the power expended in collecting and routing data to the sink node, thus increasing the lifetime of the network.

An Integration Framework of Three-Dimensional Wireless Multimedia Sensor Network with Cloud Computing for Surveillance Applications

Objectives: Three-Dimensional Wireless Multimedia Sensor Networks (3-D WMSNs) are the type of WSN. These networks deal with multimedia content such as images in various formats, video, and audio etc. Moreover 3-D WMSNs are widely used for surveillance applications, underwater monitoring, aerial surveillance, urban warfare, monitoring infrastructure of national importance etc. Methods/Statistical Analysis: The system presents an integrated framework of three-dimensional wireless multimedia sensor network with cloud computing for surveillance applications. The integrated framework of 3D WMSNs with cloud computing is suitable for monitoring and surveillance in multi-floor buildings or marine environment. The client utilizes http protocol to interact with framework. At the server side, the sensor nodes collect the data and transfer the data to cloud where it is stored and processed in a distributed environment. On the client side, the user utilizes web services to retrieve data from the distributed SQL databases. Findings: User can fully access cloud service using devices that have internet capabilities. The work focuses distributed computing and resource allocation of processing three-dimensional wireless multimedia sensor data, and performance evaluation over various parameters settings in a cloud environment. Application/Improvements: We utilize CloudSim for simulating the cloud computing environment. The benefits of the system include basic computing hardware and reasonable storage capacities making it suitable for any 3D WMSN which provides real time monitoring and surveillance.

Research on Algorithm of Three-Dimensional Wireless Sensor Networks Node Localization

This paper proposes a three-dimensional wireless sensor networks node localization algorithm based on multidimensional scaling anchor nodes, which is used to realize the absolute positioning of unknown nodes by using the distance between the anchor nodes and the nodes. The core of the proposed localization algorithm is a kind of repeated optimization method based on anchor nodes which is derived from STRESS formula. The algorithm employs the Tunneling Method to solve the local minimum problem in repeated optimization, which improves the accuracy of the optimization results. The simulation results validate the effectiveness of the algorithm. Random distribution of three-dimensional wireless sensor network nodes can be accurately positioned. The results satisfy the high precision and stability requirements in three-dimensional space node location.

The Indoor Localization and Tracking Estimation Method of Mobile Targets in Three-Dimensional Wireless Sensor Networks

Indoor localization is a significant research area in wireless sensor networks (WSNs). Generally, the nodes of WSNs are deployed in the same plane, i.e., the floor, as the target to be positioned, which causes the sensing signal to be influenced or even blocked by unpredictable obstacles, like furniture. However, a 3D system, like Cricket, can reduce the negative impact of obstacles to the maximum extent and guarantee the sensing signal transmission by using the line of sight (LOS). However, most of the traditional localization methods are not available for the new deployment mode. In this paper, we propose the self-localization of beacons method based on the Cayley–Menger determinant, which can determine the positions of beacons stuck in the ceiling; and differential sensitivity analysis (DSA) is also applied to eliminate measurement errors in measurement data fusion. Then, the calibration of beacons scheme is proposed to further refine the locations of beacons by the mobile robot. According to the robot’s motion model based on dead reckoning, which is the process of determining one’s current position, we employ the filter and the strong tracking filter (STF) to calibrate the rough locations, respectively. Lastly, the optimal node selection scheme based on geometric dilution precision (GDOP) is presented here, which is able to pick the group of beacons with the minimum GDOP from all of the beacons. Then, we propose the GDOP-based weighting estimation method (GWEM) to associate redundant information with the position of the target. To verify the proposed methods in the paper, we design and conduct a simulation and an experiment in an indoor setting. Compared to EKF and the filter, the adopted STF method can more effectively calibrate the locations of beacons; GWEM can provide centimeter-level precision in 3D environments by using the combination of beacons that minimizes GDOP.

Analysis of stochastic coverage and connectivity in three-dimensional heterogeneous directional wireless sensor networks

Coverage and connectivity are important factors that determine the quality of service of three-dimensional wireless sensor networks (3D WSNs) monitoring a field of interest (FoI). Most of the literature on the analysis of coverage and connectivity in 3D WSNs assumes the use of omni-directional sensors with spherical sensing regions. In this paper, we assume that the sensors are deployed uniformly at random in a FoI. We also consider a case when the sensors have only directional sensing capability and may have heterogeneity in terms of the sensing range, communication range, and/or probability of being alive. For such 3D heterogeneous directional WSNs, we derive probabilistic expressions for k-coverage and m-connectivity that are useful to optimize the cost of random deployment. We validate our analysis and demonstrate its benefits with numerical results. We also illustrate the application of this work for optimal design of a 3D heterogeneous directional WSN.

Planning the obstacle-avoidance trajectory of mobile anchor in 3D sensor networks

Localization plays an important role in many applications of wireless sensor networks. Recently, mobile anchor assisted localization methods become promising, and the moving trajectory planning of anchor is an interesting and basic issue in these methods. In this paper, an obstacle-avoidance trajectory planning method for three-dimensional wireless sensor networks is proposed. After dividing the network into grids, a depth-first-search algorithm with greedy strategy is proposed to get the approximately shortest path, and a trigonal function based localization method is presented to estimate the positions of the sensor nodes. Simulations show that this method can obtain almost the optimal path and localize almost all the sensor nodes.