Joint k-Coverage and Hybrid Forwarding in Duty-Cycled Three-Dimensional Wireless Sensor Networks

Although most of the studies on coverage and connectivity in wireless sensor networks (WSNs) considered two-dimensional (2D) settings, such networks can in reality be accurately modeled in a three-dimensional (3D) space. The concepts of continuum percolation theory best fit the problem of connectivity in WSNs to find out whether the network provides long-distance multihop communication. In this paper, we focus on percolation in coverage and connectivity in 3D WSNs. We say that the network exhibits a coverage percolation (respectively, connectivity percolation) when a giant covered region (respectively, giant connected component) almost surely spans the entire network for the first time. Because of the dependency between coverage and connectivity, the problem is not only a continuum percolation problem but also an integrated continuum percolation problem. Thus, we propose an integrated-concentric-sphere model to address coverage and connectivity in 3D WSNs in an integrated way. First, we compute the critical density lambdaC con above which coverage percolation in 3D WSNs will almost surely occur. Second, we compute the critical density lambdac con above which connectivity percolation in 3D WSNs will almost surely occur. Third, we compute the critical density lambdac cov-con above which both coverage and connectivity percolation in 3D WSNs will almost surely occur. For each of these three problems, we also compute their corresponding critical network degree. Our results can be helpful in the design of energy-efficient topology control protocols for 3D WSNs in terms of coverage and connectivity.

The topology control for three-dimensional (3D) wireless sensor network is a basic problem in the research of 3D wireless sensor network, and it is also one of the important supporting technologies. Aiming at the topology control problem of three-dimensional wireless sensor networks, this paper proposes an optimal topology rapid generation algorithm based on minimum spanning tree and edge addition operation, and analyzes the time complexity of the algorithm. Compared with the existing algorithms, this algorithm can generate a three-dimensional optimal rigid graph as the wireless sensor network topology in a shorter time to ensure the connectivity and robustness of the network. Finally, the effectiveness of the algorithm is further verified by comparing simulation experiments.

In Wireless Sensor Networks (WSNs), providing full area coverage while maintaining connectivity between the sensors is considered an important issue. Coverage-aware sleep scheduling is an efficient way to optimize the coverage of WSNs while maximizing the energy consumption. On the other hand, clustering can provide an efficient way to achieve high connectivity in WSNs. Despite the close relationship between the coverage problem and the clustering problem, they have been formulated, discussed and evaluated separately. Furthermore, most existing WSN strategies are designed to be applied on Two-Dimensional (2D) fields under an ideal energy consumption model that relies on calculating the Euclidean distance between any pair of sensors. In reality, sensors are mostly deployed in a Three-Dimensional (3D) field in many applications and they do exhibit a discrete energy consumption model that depends on the sensors' status rather than the distance between them. In this paper, we propose a Pareto-based network configuration strategy for 3D WSN s. In the proposed protocol, deciding the status of each sensor in a 3D WSN s is formulated as a single multi-objective minimization problem. The proposed formulation considers the following combined properties: energy efficiency, data delivery reliability, scalability, and full area coverage. The performance of the proposed protocol is tested in 3D WSNs and under a realistic energy consumption model which is based on the characteristics of the Chip con CC2420 radio transceiver data sheet.

Event detection techniques are crucial for environmental monitoring and object tracking applications in wireless sensor networks. Event detection requires sensor readings to be collected from multiple sensors, and as sensors have limited resources, their readings should be retrieved efficiently. Existing aggregation-based event detection methods, however, require all sensors in the network to transmit their readings, which results in high energy consumption for the network. We propose an energy-efficient event detection technique for estimating the state of the whole environment based on only some of the sensor readings and use a contour map to represent the outline of the environment. To detect events in 3D environments, we modify an existing 2D contour mapping algorithm, extending it for 3D environments. By simulation, we show how our event detection technique is more energy-efficient than existing solutions that take readings from all sensors. We evaluated our method from the point of energy efficiency and found that it improves the energy efficiency of event detection in 3D wireless sensor networks.

The localization of sensor nodes is one of the critical technologies in a three-dimensional (3D) wireless sensor network. Nowadays, many time-critical scenarios, like a forest fire, demand fast and efficient assessment of the affected area.A mobile anchor-assisted localization ensures efficient positioning while reducing energy and time consumption for the overall network. To achieve this a suitable trajectory for a mobile anchor is of great importance. In our work, we assume a micro aerial vehicle (MAV) as the mobile anchor. MAVs provide many practical benefits and easier access to dangerous areas is one of them.In this paper, we propose a novel path planning algorithm - 3D Adaptive Scan. It only covers the area where the unlocalized wireless nodes are present. In this way, the localization time is reduced by half when compared to the state-of-the-art algorithms. Moreover, we use a novel evaluation metric, namely trajectory efficiency that takes into account localization time, error and ratio. The obtained results indicate that our 3D Adaptive Scan guarantees the efficiency of around 70% outperforming its competitors by at least 30%.

Today, underwater target tracking using underwater wireless sensor networks (UWSNs) is an essential part in many military and non-military applications. Most of moving target tracking studies in UW...

Location information is of paramount importance for wireless Sensor Networks (WSNs). The design of WSNs has always been focused on an specific point of networks in a two-dimensional (2D) space. Nowadays this design is not enough and the study of the three dimension is needed. In this article, we focus on 3D location accuracy in WSNs. We quantify the estimation accuracy for the RSS measurements by deriving the Cramer-Rao bound (CRB), and discuss the performance in two application scenarios, 2D WSN and 3D WSN. Matlab simulation indicates that the 3D location accuracy is superior to the 2D location accuracy for WSNs with reference devices and blindfolded devices being deployed randomly.

How to provide reliable coverage for a field of interest (FOI) and prolong network lifetime is a critical issue in three-dimensional (3D) Wireless Sensor Networks (WSNs). In practical applications, sensors may not have the same energy consumption model, which profoundly influences the network lifetime. In this paper, we address the problem of maximizing the network lifetime while satisfying $$k$$ -coverage of the 3D FOI by determining redundant sensors. We assume different sensors have different sensing and communication range, and energy consumption models. We propose a method to find the redundant sensors and their neighbors based on the border effect and probability sensing model and develop a distributed sleep scheduling algorithm. Through simulations, the results show that the proposed algorithm outperforms the other existing approach, providing a longer lifetime and higher average coverage ratio by using few communication messages.

Novel fuzzy clustering scheme for 3D wireless sensor networks

Wireless Sensor Networks (WSN) has proliferated in the past decade. These networks consist of massive number of battery-powered nodes distrusted over a given area. The nodes are responsible for sensing the environment and delivering the sensed data to a central point, named sink node. In order to reduce the power consumption of these nodes, sleeping/waking scheduling strategy has been proposed. In this work, a new hybrid sleeping/waking scheduling algorithm is proposed based on graph theory metrics and unsupervised K-mean machine learning algorithm. In the proposed algorithm, the sink node is responsible for calculating the metrics and clustering the nodes into three main clusters; dense, mid and light. Subsequently, the algorithm attempts to reduce the load on the nodes in light cluster in order to prolong the network lifetime. The algorithm has been simulated in 3D WSN with a clustering routing protocol. The simulation results show that the algorithm reduces the number of working sensor network nodes without affecting the network diameter. Moreover, the scheduling strategy has prolonged the network lifetime and has reduced the number of disconnected components.

In many applications, sensor nodes are deployed in a 3D environment with obstacles, in which case a great deal of holes exist in 3D wireless sensor networks constructed. Recently, several geographic routing protocols are proposed for 3D wireless sensor networks. Each of them, however, cannot guarantee packet delivery or demands a long routing path to turn around a hole. In this paper, we first introduce a method of constructing a guide to the navigation on the surface of a hole. Subsequently, a geographic routing protocol termed the Greedy‐Guide_Navigation‐Greedy protocol (GGNG) that can always route a packet to turn around a hole with the help of the guide is proposed. GGNG guarantees packet delivery and can be extended toward a mobile sensor network in a limited 3D space. Simulations show that the path stretch of each routing protocol to GGNG in approximately 90%of the cases is between 1.02 and 189.24. In addition, the number of messages transmitted by a node surrounding a hole in the guide construction is approximately three. Copyright © 2014 John Wiley & Sons, Ltd.

Using wireless sensor networks (WSNs) in delay and reliability critical environments is highly desired due to their unique advantages such as low cost, ease of deployment, and redundancy. However, successful deployment of resource-limited WSNs in such applications requires strict quality-of-service (QoS) provisioning techniques to meet the desired latency and reliability targets of those applications. Implementation of QoS techniques in WSNs is significantly challenging since WSNs have been initially devised for low-data-rate non-real-time applications. Therefore, WSN designers and developers resort to different cross-layer interaction and optimization techniques to provision QoS in WSNs. In this paper, we present a survey on the state of the art of cross-layer QoS approaches in wireless terrestrial sensor networks to achieve delay and reliability bounds in critical applications. Our paper provides a unique classification of cross-layer QoS approaches in WSNs that allows surveying a large amount of studies with utmost clarity. Furthermore, we highlight the main challenges of implementing QoS protocols in WSNs and present an overview of QoS-aware WSN applications.

Wireless sensor networks (WSNs) are quickly becoming an essential part of today's modern infrastructure, and it is becoming crucial to consider time synchronisation problems in WSNs. Furthermore, one of the main design issues in WSN time synchronisation is the efficient use of energy at each sensor node to prolong the lifespan of the network. This paper describes a new energy-efficient time protocol based on the spanning tree of the network model graph in a WSN. Three major cases are discussed: 1) time synchronisation using the energy-efficient spanning tree (EST) protocol in a WSN with approximately 300 sensors; 2) an improved EST protocol in large-scale WSNs; 3) an improved EST protocol under weighted graph. Additionally, a series of practical algorithms are proposed in this paper, where both energy and time efficient can be clearly shown through a number of simulated examples along with their comparative results.

QoSNET: An integrated QoS network for routing protocols in large scale wireless sensor networks

Wireless sensor networks(WSN) are a kind of communication networks with in-dependent sensor nodes which could construct multi-hop ad hoc network to trans-fer data. The transport protocols for Wireless Sensor Network play an important role to promote the performance of the whole systems. This paper proposes a modified transport layer protocol for heterogeneous Wireless Sensor Networks(HWSN). As TCP is not suitable to use in HWSN directly, we design a modified transport protocol(named mTCP) based on TCP by a six-state finite state machine. Experimental results illustrate that our design can improve the communication capability of the transmission layer in heterogeneous wireless sensor networks significantly.