A range-based sleep scheduling algorithm for desired area coverage in solar-powered wireless sensor networks

Target Coverage and Network Connectivity in Wireless Sensor Networks (WSNs) plays a momentous role in the field of monitoring environment, habitant observing, disaster recovery, surveillance, etc. Coverage and Network Connectivity collectively can be considered as a proportion of Quality of Service (QoS) in a sensor network. It implies the coverage of each point in the detecting field while in the meantime fulfilling the measure that each node is surrounded by the equivalent neighbourhood of at least one other node. Many primary issues influence the outline and performance of WSN. A Comprehensive survey is made based on the scheduling algorithm and set cover approach, in which we analyze various approaches and their algorithm complexity. Firstly, the scheduling algorithm intermittently provides the required data service with guaranteed efficiency. This methodology can efficiently reduce the entire number of active nodes in the network, resulting in maximizing the network lifetime. Secondly, the set cover approach plays a major role in solving target coverage problem which group sensors into each cover set thereby, target coverage was achieved. Typical issues and open research challenges are addressed by classifying the approaches available in literature into three broad categories namely, adaptable coverage radius, coverage deployment strategy, and sleep scheduling. This survey aims to provide a better perceptive of the existing open challenges and possible futuristic approaches for target coverage and network connectivity in wireless sensor networks.

It is our great pleasure to welcome you to the 3rd ACM Workshop on Security of Ad Hoc and Sensor Networks (SASN'05), held in conjunction with the 12th ACM Conference on Computer and Communications Security (CCS'05), November 7, 2005, in Alexandria, Virginia.This year we received a total of 39 submissions on various aspects of ad-hoc and sensor network security. The program committee selected 6 as regular papers that cover a variety of topics, including trust establishment in Mobile Ad-Hoc Networks (MANETs), security of vehicular ad-hoc networks, secure group communication, key pre-distribution for sensor networks, jamming attacks against sensor network MAC protocols, and defense against Denial-of-Service (DoS) attacks. This year we continue the tradition of SASN'03 and SASN'04 to encourage the presentation and discussion of work-in-progress on ad-hoc and sensor network security. Among the 39 submissions, the program committee selected 7 papers to present in work-in-progress sessions, covering topics on anonymous routing for MANETs, key distribution for inter-group multicast in ad-hoc networks, improved topology assumptions for threshold cryptography in MANETs, RFID security, tracing in mobile wireless sensor networks, time synchronization attacks in sensor networks, and coordinated deployment for improving secure communications and sensing coverage in wireless sensor networks. In addition, the program includes a panel on Advances in Sensor and Ad-hoc Network Security and an invited keynote talk by Radha Poovandran (University of Washington) on Information Assurance in MANETs and Wireless Sensor Networks. We hope that these proceedings will serve as a valuable reference for security researchers and developers.

Aiming at the uneven random coverage distribution of wireless sensor networks sensor nodes, the sparrow search algorithm (SSA) is used to optimize the node coverage of wireless sensor networks. To improve the global search capability of SSA, the algorithm is improved and applied to the wireless sensor networks of bridge monitoring. For enhancing the coverage of the wireless sensor networks, this article uses two improved methods. One is to use the good point set theory to make the initial population evenly distributed; another is to introduce a weight factor to speed up its convergence. The experiments have proved the reliability and rationality of the algorithm. The improved algorithm is superior to other meta-heuristic algorithms and provides a new idea for optimizing bridge monitoring wireless sensor networks coverage.

In this paper, we are concerned with energy efficient area monitoring using information coverage in wireless sensor networks, where collaboration among multiple sensors can enable accurate sensing of a point in a given area-to-monitor even if that point falls outside the physical coverage of all the sensors. We refer to any set of sensors that can collectively sense all points in the entire area-to-monitor as a full area information cover. We first propose a low-complexity heuristic algorithm to obtain full area information covers. Using these covers, we then obtain the optimum schedule for activating the sensing activity of various sensors that maximizes the sensing lifetime. The scheduling of sensor activity using the optimum schedules obtained using the proposed algorithm is shown to achieve significantly longer sensing lifetimes compared to those achieved using physical coverage. Relaxing the full area coverage requirement to a partial area coverage (e.g., 95% of area coverage as adequate instead of 100% area coverage) further enhances the lifetime.

Notice of Violation of IEEE Publication Principles Critical Density for Coverage and Connectivity in Two-Dimensional Aligned-Orientation Directional Sensor Networks Using Continuum Percolation, by Mohammad Khanjary, Masoud Sabaei, and Mohammad Reza Meybodi in IEEE Sensors Journal, vol. 14, no. 8, pp. 2856-2863, Aug. 2014 After careful and considered review of the content and authorship of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE's Publication Principles. This paper contains significant portions of original text from the paper cited below. The original text was copied without attribution (including appropriate references to the original author(s) and/or paper title) and without permission. Integrated Coverage and Connectivity in Wireless Sensor Networks: A Two-Dimensional Percolation Problem, by H. M. Ammari and S. K. Das, in IEEE Transactions on Computers, vol. 57, no. 10, pp. 1423-1434, Oct. 2008 Sensing coverage is one of the fundamental design issues in wireless sensor networks, which reflects the surveillance quality provided by them. Moreover, network connectivity enables the gathered data by sensors to reach to the sink node. Given an initially uncovered field, and as more and more directional sensors are continuously added to the sensor network, 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 the sensing-coverage phase transition (SCPT). Likewise, given an originally disconnected sensor network, as more and more sensors are added, the number of connected components changes such that the sensor network suddenly becomes connected at some point. We call this sudden change the network connectivity phase transition (NCPT). The nature of such phase transitions is a central topic in the percolation theory. In this paper, we introduce aligned-orientation directional sensor networks in which nodes are deployed based on Poisson point process and the orientation of all sensor nodes is the same. Then, we propose an approach to compute density of nodes at critical percolation for both of the SCPT and NCPT problems in such networks, for all angles of field-of-view between 0 and π by using continuum percolation. Due to percolation theory, the critical density is infimum density that for densities above it SCPT and NCPT almost surely occur. In addition, we propose a model for percolation in directional sensor networks, which provides a basis for solving the SCPT and NCPT problems together.

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.

Wireless sensor networks are a collection of specially designed nodes to provide support to sensor information propagation. Sensor nodes are basically designed to sense data as sensor and distribute to servers for further analysis. Based on the specific requirements, the numbers of sensor nodes can range from hundreds to thousands. All the communication will take place through predefined network characteristics. WSNs generally face energy issues. LEACH is designed for efficient cluster formation. It provides an efficient energy solution for data transmission from node to base station. Various enhanced version of LEACH has been proposed by Assuming LEACH as base protocol. The energy constraints are a critical aspect in developing the routing protocols for WSNs. Designers and researchers have contributed their effort through enhancement in energy saving procedure into WSNs. In this work, the LEACH based protocols and their performance in WSN has been analysed. This research paper evaluates recent advancement in LEACH based approaches for Wireless Wide Area Sensor Network with comparison table.

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

Coverage in wireless sensor networks is a critical issue since it reflects the cost and detection capability of the network. Sensor coverage model is closely to the sensing functions of different types of sensors while network coverage is a collaborative measure from geographically distributed sensors. The coverage problems in wireless sensor networks have been formulated in various ways with different assumptions, constraints and objectives. In this work, a collaborative coverage model is proposed in the target surveillance application, while sensor sensing probabilistic model is introduced. Furthermore, a collaborative target coverage optimization algorithm (CTCOMSN) is presented to prolong the network lifetime in energy constraint mobile sensor networks. Simulation results show that CTCOMSN can prolong the lifetime greatly while improving the sensing quality.

Wireless Sensor Networks (WSNs) can be used effectively to form barriers that monitor strips of land for applicaions such as homeland security and critical infrastructure protection. Sensors are highly constrained in their energy usage, so when they harvest energy, it is neccessary that this energy be used effectively. When WSNs are used as barriers, they are typically deployed for extended period of time, so it is of great importance that the network has a long lifetime. The lifetime problem for WSNs has been studied extensively. In this paper we give an exact solution to the problem of achieving maximum lifetime for the application of k-barrier coverage in energy harvesting wireless sensor networks.

As the Internet of Things (IoT) evolves, more and more Wireless Sensor Networks (WSNs) are being deployed in the real world. Connected vehicles, smart grids, smart cities, smart healthcare, networks of robots, and disaster recovery networks are some examples. In WSNs, the area coverage is one of the most important quality of service metrics. A WSN without enough area coverage yields incorrect results. So calculating the covered area of a WSN is mandatory. Previous studies have used a simple approach: all nodes send their location to the sink, and it calculates the covered area centrally which makes huge unnecessary communication overhead. In our previous work titled Distributed Exact Coverage Rate Calculation, we calculated the covered area of a homogenous WSN in a distributed manner. In this paper, we provide a Heterogeneous Distributed Precise Coverage Rate (HDPCR) mechanism that calculates the covered area of a Heterogeneous Wireless Sensor Network by using a localized mechanism. With the use of boundary detection mechanisms, the HDPCR detects the boundary of the network and calculates its area. HDPCR also detects holes and calculates their area precisely. By subtracting these two calculated values, the covered area of the network can be computed. Many related studies have evaluated the coverage rate approximately with error and require more calculations to reduce the error rate. HDPCR calculates the coverage rate precisely without an error rate using simple arithmetic calculations. The exhaustive simulation also shows the superiority of HDPCR as compared to the previous approaches.

Exploring coverage and security challenges in wireless sensor networks: A survey

Many wireless sensor network applications must resolve the inherent conflict between energy efficient and nodes of coverage in wireless sensor networks to achieve desired quality of service (QoS). The wireless sensor networks (WSNs) have been the main focus in the past few years, and it is becoming a special issue. We study the problem of controlling the node locations and energy within ad-hoc sensor networks. Network survivability is a very important measure for deciding the efficiency of network protocols. It includes a measure of the network lifetime as well as the quality of service. In fact, these dynamics are very important in evaluating networks. The wireless network applications can be found in battlefield communication, homeland security, pollution sensing and traffic monitoring. As such, there has been an increasing need for defining and developing simulation frameworks for carrying out high-fidelity WSN simulation. In this cause, we present a simulation by including factors such as energy-consumption, Bandwidth, nodes, and coverage and provides an object-oriented definition of target, sensor and sink nodes, sensor and wireless communication nodes, and physical radio such as relating of nodes, mobility model and power model both energy-producing and energy-consuming components, the simulation was developed using C#.

In recent times although there is lot of research in field of localization application but very few aims at localization module with optimal energy consumption. Localization, being inevitable for a range of applications, is also a basis for many network operations such as data packet forwarding i.e. routing and sensing coverage in wireless sensor networks. With a range of application scenario, it is a challenging task to design a localization module for a wireless sensor network consisting of sensor nodes with limited capacity in terms of power, processing and storage etc. This paper presents a simple model of a range based localization system that employs distributed computing in a collaborative and cooperative manner. The aim of this work is to modify a range based localization algorithm to utilize scarce resources optimally along with improved performance by changing the inherent methodologies of position estimation. In this research work basically the role of a media access control scheme (MAC) in the localization module is investigated. A MAC is basically used to save the energy by reducing collisions and retransmission of range packets. Further, energy is conserved by restricting the coverage to a smaller part containing the neighbours up to certain hops and that is formed by dividing the whole network area into clusters. To analyse the performance spectrum, we have simulated the localization method under a variety of application scenarios and lead to the conclusion that this approach increases the efficiency of localization in wireless sensor networks. In the simulation process, every minute aspect of sensor network localization model including the topology, range, mobility, channel, propagation schemes etc. were considered and the performance was finally analyzed.

In large scale Wireless Sensor Networks (WSNs), the random deployment of the sensor nodes does not guarantee the desired level of the area coverage especially when the network is sparse. One of the solutions to overcome this problem is to use a mobile robot that is equipped with, in addition to the sensing unit, an actuator unit that controls its movement. In this case, the mobile robot is considered as a mobile sensor node that has the capability to monitor the uncovered regions in the sensor field. However, the main challenge in this case is how to control the movement of the mobile robot such that the area coverage is maximized and the time required to sample the uncovered regions is minimized. In this paper, we propose a fuzzy logic-based approach that controls the mobile robot movement in the sensor field in order to maximize the area coverage. The inputs of the fuzzy system determine the next point that the mobile node will select when it moves in the sensor field. Simulation results have shown that the proposed approach outperforms the random and standard moving patterns.