Connectivity In Wireless Sensor Networks Research Articles

A biologically inspired intelligent environment architecture for mobile robot navigation

Localisation in conventional autonomous robot navigation using centralised on-board intelligence faces many challenging issues. Steering away from the centralised on-board solution, this paper proposes a distributed approach by deploying distributed wireless nodes that comprise of vision sensors and embedded computers to process images, localise the robot and dynamic obstacles, navigate and control the robot. This schema releases massive on-board information processing required by conventional autonomous robot to its operation environment. The objective is to enable robots with limited intelligence to carry out complex navigation functions. The architectural design and realisation for connecting wireless vision sensors in the environment for global robot navigation path planning and local motion control is described. The paper gives a review of the proposed algorithms. The details of the wireless sensor network connectivity, system functions and modules, organisation and connection of the system components are described. The hardware and software realisation and experiment results are also discussed.

Performance of the Eschenauer–Gligor Key Distribution Scheme Under an ON/OFF Channel

We investigate the secure connectivity of wireless sensor networks under the random key distribution scheme of Eschenauer and Gligor. Unlike recent work which was carried out under the assumption of full visibility, here we assume a (simplified) communication model where unreliable wireless links are represented as on/off channels. We present conditions on how to scale the model parameters so that the network i) has no secure node which is isolated and ii) is securely connected, both with high probability when the number of sensor nodes becomes large. The results are given in the form of full zero-one laws, and constitute the first complete analysis of the EG scheme under non-full visibility. Through simulations these zero-one laws are shown to be valid also under a more realistic communication model, i.e., the disk model. The relations to the Gupta and Kumar's conjecture on the connectivity of geometric random graphs with randomly deleted edges are also discussed.

Condition for the Coverage and Connectivity of Wireless Sensor Network

The topology attributes of both connectivity and coverage in a wireless sensor network depend on the spatial distribution and transmission range of the nodes. This paper proposes an analytical expression of the required critical transmission range of a node, for a given node density, to create an almost surely connected network. Equivalently, if the maximum range of the nodes is given, it can estimate effectively the number of nodes needed to cover a certain connected network. With experimental tests, the method is proved to achieve guaranteed degrees of coverage and connectivity, valuable for researchers in this area.

Efficient Algorithm for Constructing Minimum Size Wireless Sensor Networks to Fully Cover Critical Square Grids

Wireless sensor networks are formed by connected sensors that each have the ability to collect, process, and store environmental information as well as communicate with others via inter-sensor wireless communication. These characteristics allow wireless sensor networks to be used in a wide range of applications. In many applications, such as environmental monitoring, battlefield surveillance, nuclear, biological, and chemical (NBC) attack detection, and so on, critical areas and common areas must be distinguished adequately, and it is more practical and efficient to monitor critical areas rather than common areas if the sensor field is large, or the available budget cannot provide enough sensors to fully cover the entire sensor field. This provides the motivation for the problem of deploying the minimum sensors on grid points to construct a connected wireless sensor network able to fully cover critical square grids, termed CRITICAL-SQUARE-GRID COVERAGE. In this paper, we propose an approximation algorithm for CRITICAL-SQUARE-GRID COVERAGE. Simulations show that the proposed algorithm provides a good solution for CRITICAL-SQUARE-GRID COVERAGE.

Identifying Neighbor and Connectivity of Wireless Sensor Networks with Poisson Point Process

Identifying neighbor and connectivity are the fundamental requirements in wireless sensor networks. The sensor nodes are scattered randomly over the area of interest and their first step is to identify their immediate neighbors, i.e., the nodes with which they have direct wireless communication. On the other hand, connectivity ensures that sensor nodes can communicate with each other in order to aggregate sensing data hop by hop to the base stations (sink nodes). In this paper, we study identifying neighbor and connectivity in the context of wireless sensor networks, using Poisson point process theory.

On network connectivity of wireless sensor networks for sandstorm monitoring

As serious natural disasters, sandstorms have caused massive damages to the natural environment, national economy, and human health in the Middle East, Northern Africa, and Northern China. To avoid such damages, wireless sensor networks (WSNs) can be deployed in the regions where sandstorms generally originate so that sensor nodes can collaboratively monitor the origin and development of sandstorms. Despite the potential advantages, the deployment of WSNs in the vicinity of sandstorms faces many unique challenges, such as the temporally buried sensors and increased path loss during sandstorms. Consequently, the WSNs may experience frequent disconnections during the sandstorms. In this paper, the connectivity issue of WSNs for sandstorm monitoring is studied. First, four types of channels a sensor can utilize during sandstorms are analyzed, which include air-to-air channel, air-to-sand channel, sand-to-air channel, and sand-to-sand channel. Based on these analytical results, the percolation-based connectivity analysis is performed. It is shown that if the sensors are buried in shallow depth, allowing sensor to use multiple types of channels improves network connectivity. Accordingly, much smaller sensor density is required compared to the case, where only terrestrial air channels are used. Through this connectivity analysis, a WSN architecture can be established for efficient and effective sandstorm monitoring.

A Scheduling Strategy Suitable for Industrial Ethernet and Mine WSN Scheduling System

Aiming at the actual requirement of the System of industrial Ethernet Connectivity of wireless sensor networks in underground coal mine, a dynamic priority scheduling algorithm which is applied in the interconnected gateway is presented. The algorithm can avoid the occurrence of the congestion in the interconnected system. Simulation results show that packet loss rate is controlled within 7 to 15%, service response time is controlled within 2.8~7s and average queue length is stable when the interconnected system is three times than the maximum load. However, when the load of the interconnected system has returned to normal, the gateway enters the steady state that packet loss rate is zero only after 6s.

Towards robustness and energy efficiency of cut detection in wireless sensor networks

Reliable, full network connectivity in wireless sensor networks (WSN) is difficult to maintain. Awareness of the state of network connectivity is similarly challenging. Harsh, unattended, low-security environments and resource-constrained nodes exacerbate these problems. An ability to detect connectivity disruptions, also known as cut detection, allows WSN to conserve power and memory while reducing network congestion. We propose ER-CD and LR-CD, protocols that detect cuts while providing energy-efficiency and robustness to attack. Using distributed, cluster-based algorithms, ER-CD recognizes and determines the scope of disrupted connectivity while examining available data for evidence of an attack. For more resource-constrained networks, LR-CD enhances security through the use of a robust outlier detection algorithm. Extensive simulations and a hardware implementation provide experimental validation across a range of network sizes and densities. Results indicate that energy-efficiency can be improved by an order of magnitude in denser networks while malicious nodes are detected at deviations of 1% from expected behavior.

A Study of k-Coverage and Measures of Connectivity in 3D Wireless Sensor Networks

In a wireless sensor network (WSN), connectivity enables the sensors to communicate with each other, while sensing coverage reflects the quality of surveillance. Although the majority of studies on coverage and connectivity in WSNs consider 2D space, 3D settings represent more accurately the network design for real-world applications. As an example, underwater sensor networks require design in 3D rather than 2D space. In this paper, we focus on the connectivity and k-coverage issues in 3D WSNs, where each point is covered by at least k sensors (the maximum value of k is called the coverage degree). Precisely, we propose the Reuleaux tetrahedron model to characterize k-coverage of a 3D field and investigate the corresponding minimum sensor spatial density. We prove that a 3D field is guaranteed to be k-covered if any Reuleaux tetrahedron region of the field contains at least k sensors. We also compute the connectivity of 3D k-covered WSNs. Based on the concepts of conditional connectivity and forbidden faulty sensor set, which cannot include all the neighbors of a sensor, we prove that 3D k-covered WSNs can sustain a large number of sensor failures. Precisely, we prove that 3D k-covered WSNs have connectivity higher than their coverage degree k. Then, we relax some widely used assumptions in coverage and connectivity in WSNs, such as sensor homogeneity and unit sensing and communication model, so as to promote the practicality of our results in real-world scenarios. Also, we propose a placement strategy of sensors to achieve full k-coverage of a 3D field. This strategy can be used in the design of energy-efficient scheduling protocols for 3D k-covered WSNs to extend the network lifetime.

Energy conservation algorithms for maintaining coverage and connectivity in wireless sensor networks

Energy conservation, coverage and connectivity are three critical application requirements in wireless sensor networks, especially in sensor networks for vehicular applications. Related researches have either concerned coverage, connectivity and energy conservation separately or required sensing/transmission range restrictions. In this study, the authors aim to maximise the network lifetime by redundant sensor nodes, while maintaining coverage and connectivity simultaneously, without any sensing or transmission range restriction. We propose maximum disjoint sets for maintaining coverage and connectivity (MDS-MCC) problem and the authors prove it is NP-complete. We also present two algorithms to solve MDS-MCC, Heuristic Algorithm and Network Flow Algorithm. We analyse and compare the performance of these two algorithms through simulations. According to several metrics, the authors give some suggestions of designing a sensor network. Furthermore, we study MDS-MCC problem under some special conditions, and an important theoretical result is obtained while designing a sensor network. As well as aiming to design an energy conservation sensor network, the present work can also be applied in applications requiring fault tolerance by redundancy.

Connectivity analysis of wireless sensor networks with regular topologies in the presence of channel fading

This paper investigates the probabilistic connectivity of wireless sensor networks in the presence of channel fading. Due to the stochastic nature of wireless channels in sensor networks, the geometric disk shaped model widely used for connectivity analysis of sensor networks can be misleading. In this paper, we develop a mathematical model to evaluate the probabilistic connectivity of sensor networks which incorporates the characteristics of wireless channels, multi-access interference, the network topology and the propagation environment. We present an analytical framework for the computation of node isolation probability and network connectivity under different channel fading models. We also analyze the connectivity of sensor networks in the presence of unreliable sensors. We present numerical and simulation results that compare different regular topologies in terms of several metrics such as node isolation probability, end-to-end connectivity, and network connectivity.

Special Issue on “Wireless Sensor Networks”

Toward the end of the 20th century, the Internet has been able to provide a large number of users with the ability to move diverse forms of information readily and thus has revolutionized business, industry, defense, science, education, research, and human interactions. In the last 10 years, sensor networking combines the technology of modern microelectronic sensors, embedded computational processing systems, and modern computer networking methodology. It is believed that sensor networking in the 21st century will be equally significant by providing measurement of the spatial-temporal physical phenomena around us, leading to a better understanding and utilization of this information in a wide range of applications. Sensor networking will be able to bring a finer-grained and fuller measurement and characterization of the world around us to be processed and communicated, so the decision makers can utilize the information to take actions in near-real-time. The potential applications enabled by SNs include security and surveillance, environmental monitoring and control, target detection and tracking, etc. Wireless sensor networks utilize the extensive networking concepts of ad hoc networks and apply them to specific sensor network scenarios. This mini-special issue comprises three papers covering three quiet diverse aspects of wireless sensor networks. The first paper, “Lifetime Maximization Based on Coverage and Connectivity in Wireless Sensor Networks,” is by T. Zhao et al. They studied the problem of network lifetime maximization for QoS specific information retrieval for the reconstruction of a spatially correlated signal field in a wireless sensor network for two wireless transmission cases. In one case, they assumed there exist single-hop transmissions between sensors and the access point, and in the other case, the measurements are sent to the access point through multi-hop transmissions. To address both of these problems, they formulated the problems using integer programming based on the theories of coverage and connectivity in sensor networks and then derived upper bounds for the network lifetime that provides benchmarks for the performance of suboptimal methods. Several lowcomplexity suboptimal algorithms for joint node scheduling and data routing were then proposed to approach the performance upper bounds. The second paper, “Using Heterogeneity to Enhance Random Walk-based Queries,” is by M. Zuniga et al. They presented a study of the impact of heterogeneous node connectivity on random walk-based queries. The main contribution of the work is showing that with a small percentage (e.g., 10%) of high-degree nodes in the network and using a simple distributed push-pull mechanism, significant cost savings can be obtained (e.g., between 30% and 70%) depending on the coverage of the high-degree nodes. Their work provides interesting theoretical results for line topologies showing that when cluster-heads have a coverage of k nodes to the right and left and are uniformly distributed, a fraction of 4/5k J Sign Process Syst (2009) 57:381–383 DOI 10.1007/s11265-009-0377-9

Critical Density for Coverage and Connectivity in Three-Dimensional Wireless Sensor Networks Using Continuum Percolation

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.

Fault tolerance measures for large-scale wireless sensor networks

Connectivity , primarily a graph-theoretic concept, helps define the fault tolerance of wireless sensor networks (WSNs) in the sense that it enables the sensors to communicate with each other so their sensed data can reach the sink. On the other hand, sensing coverage , an intrinsic architectural feature of WSNs plays an important role in meeting application-specific requirements, for example, to reliably extract relevant data about a sensed field. Sensing coverage and network connectivity are not quite orthogonal concepts. In fact, it has been proven that connectivity strongly depends on coverage and hence considerable attention has been paid to establish tighter connection between them although only loose lower bound on network connectivity of WSNs is known. In this article, we investigate connectivity based on the degree of sensing coverage by studying k-covered WSNs, where every location in the field is simultaneously covered (or sensed) by at least k sensors (property known as k-coverage , where k is the degree of coverage ). We observe that to derive network connectivity of k -covered WSNs, it is necessary to compute the sensor spatial density required to guarantee k -coverage. More precisely, we propose to use a model, called the Reuleaux Triangle , to characterize k -coverage with the help of Helly's Theorem and the analysis of the intersection of sensing disks of k sensors. Using a deterministic approach, we show that the sensor spatial density to guarantee k -coverage of a convex field is proportional to k and inversely proportional to the sensing range of the sensors. We also prove that network connectivity of k -covered WSNs is higher than their sensing coverage k . Furthermore, we propose a new measure of fault tolerance for k -covered WSNs, called conditional fault tolerance , based on the concepts of conditional connectivity and forbidden faulty sensor set that includes all the neighbors of a given sensor. We prove that k -covered WSNs can sustain a large number of sensor failures provided that the faulty sensor set does not include a forbidden faulty sensor set.

Lifetime Maximization Based on Coverage and Connectivity in Wireless Sensor Networks

We consider information retrieval in a wireless sensor network deployed to monitor a spatially correlated random field. We address optimal sensor scheduling and information routing under the performance measure of network lifetime. Both single-hop and multi-hop transmissions from sensors to an access point are considered. For both cases, we formulate the problems as integer programming based on the theories of coverage and connectivity in sensor networks. We derive upper bounds for the network lifetime that provide performance benchmarks for suboptimal solutions. Suboptimal sensor scheduling and data routing algorithms are proposed to approach the lifetime upper bounds with reduced complexity. In the proposed algorithms, we consider the impact of both the network geometry and the energy consumption in communications and relaying on the network lifetime. Simulation examples are used to demonstrate the performance of the proposed algorithms as compared to the lifetime upper bounds.

Integrated Coverage and Connectivity in Wireless Sensor Networks: A Two-Dimensional Percolation Problem

While sensing coverage reflects the surveillance quality provided by a wireless sensor network (WSN), network connectivity enables data gathered by sensors to reach a central node, called the sink. Given an initially uncovered field and as more and more sensors are continuously added to a WSN, the size of partial covered areas increases. At some point, the situation abruptly changes from small fragmented covered areas to a single large covered area. We call this abrupt change as the sensing-coverage phase transition (SCPT). Also, given an originally disconnected WSN and as more and more sensors are added, the number of connected components changes such that the WSN suddenly becomes connected at some point. We call this sudden change as the network-connectivity phase transition (NCPT). The nature of such phase transitions is a central topic in percolation theory of Boolean models. In this paper, we propose a probabilistic approach to compute the covered area fraction at critical percolation for both of the SCPT and NCPT problems. Because sensing coverage and network connectivity are not totally orthogonal, we also propose a model for percolation in WSNs, called correlated disk model, which provides a basis for solving the SCPT and NCPT problems together.

Modeling wireless sensor networks using random graph theory

A critical issue in wireless sensor networks (WSNs) is represented by limited availability of energy within network nodes. Therefore, making good use of energy is necessary in modeling sensor networks. In this paper we proposed a new model of WSNs on a two-dimensional plane using site percolation model, a kind of random graph in which edges are formed only between neighbouring nodes. Then we investigated WSNs connectivity and energy consumption at percolation threshold when a so-called phase transition phenomena happen. Furthermore, we proposed an algorithm to improve the model; as a result the lifetime of networks is prolonged. We analyzed the energy consumption with Markov process and applied these results to simulation.

Impact of Radio Link Unreliability on the Connectivity of Wireless Sensor Networks

Many works have been devoted to connectivity of ad hoc networks. This is an important feature for wireless sensor networks (WSNs) to provide the nodes with the capability of communicating with one or several sinks. In most of these works, radio links are assumed ideal, that is, with no transmission errors. To fulfil this assumption, the reception threshold should be high enough to guarantee that radio links have a low transmission error probability. As a consequence, all unreliable links are dismissed. This approach is suboptimal concerning energy consumption because unreliable links should permit to reduce either the transmission power or the number of active nodes. The aim of this paper is to quantify the contribution of unreliable long hops to an increase of the connectivity of WSNs. In our model, each node is assumed to be connected to each other node in a probabilistic manner. Such a network is modeled as a complete random graph, that is, all edges exist. The instantaneous node degree is then defined as the number of simultaneous valid single-hop receptions of the same message, and finally the mean node degree is computed analytically in both AWGN and block-fading channels. We show the impact on connectivity of two MACs and routing parameters. The first one is the energy detection level such as the one used in carrier sense mechanisms. The second one is the reliability threshold used by the routing layer to select stable links only. Both analytic and simulation results show that using opportunistic protocols is challenging.

On optimal placement of relay nodes for reliable connectivity in wireless sensor networks

The paper addresses the relay node placement problem in two-tiered wireless sensor networks. Given a set of sensor nodes in Euclidean plane, our objective is to place minimum number of relay nodes to forward data packets from sensor nodes to the sink, such that: 1) the network is connected, 2) the network is 2-connected. For case one, we propose a (6+e)-approximation algorithm for any e > 0 with polynomial running time when e is fixed. For case two, we propose two approximation algorithms with (24+e) and (6/T+12+e), respectively, where T is the ratio of the number of relay nodes placed in case one to the number of sensors. We further extend the results to the cases where communication radiuses of sensor nodes and relay nodes are different from each other.