A Modified Sensor Network Boundary Discovery Algorithm (original) (raw)
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A survey of boundary detection algorithms for sensor networks
One of the exigent problems in wireless sensor networks is the detection of boundary nodes at the whole network's boundary or at the boundary of the holes inside the network. In this paper we have described the various boundary detection schemes that have been proposed in order to trace out holes inside the sensor network and properly arrange the nodes residing on the boundary of the whole network as well as that of the holes. We have also provided with a detailed literature review of networks boundary and hole identification and various issues related to each of them. We have categorized the algorithms into proper categories for better understanding and have identified various issues in each category. At the end we have given a summary of our own contribution. We are working on a boundary detection algorithm in which nodes will utilize only the connectivity information to identify their position. I.
Maximum Coverage Range Based Sensor Node Selection Approach to Optimize in WSN
International Journal for Research in Applied Science and Engineering Technology, 2018
Wireless communication is one which plays very important role in all aspects of upgrading technologies today. Energy savings, Delay, Range, Efficiency, Power etc. are some of the factors which affect the performance of wireless communication. One of the important type of wireless communication is wireless sensor network, in which energy saving and coverage range optimization is major issues to be concentrated. Since most of embedded sensor nodes are equipped with limited power resources. The idea of this paper focuses on reducing the expenditure of energy with maximum sensing range of sensor node and finding shortest path between the nodes, thereby improving network lifetime and reducing the delay. By using the sensor node selection approach, an energy effective minimum hop path is selected over the network between the source and destination nodes. An algorithm called Minimum Hop Maximum Range routing (MHMR) has been designed to save energy and provide maximum coverage range of sensor nodes. Results and graph simulations shows that proposed algorithm can significantly improve the network life time and provide energy savings.
International Journal of Autonomous and Adaptive Communications Systems
Wireless Sensor Networks (WSNs) have many fields of application, including industrial, environmental, military, health and home domains. Monitoring a given zone is one of the main goals of this technology. This consists in deploying sensor nodes in order to detect any event occurring in the zone of interest considered and report this event to the sink. The monitoring task can vary depending on the application domain concerned. In the industrial domain, the fast and easy deployment of wireless sensor nodes allows a better monitoring of the area of interest in temporary worksites. This deployment must be able to cope with obstacles and be energy efficient in order to maximize the network lifetime. If the deployment is made after a disaster, it will operate in an unfriendly environment that is discovered dynamically. We present a survey that focuses on two major issues in WSNs: coverage and connectivity. We motivate our study by giving different use cases corresponding to different coverage, connectivity, latency and robustness requirements of the applications considered. We present a general and detailed analysis of deployment problems, while highlighting the impacting factors, the common assumptions and models adopted in the literature, as well as performance criteria for evaluation purposes. Different deployment algorithms for area, barrier, and points of interest are studied and classified according to their characteristics and properties. Several recapitulative tables illustrate and summarize our study. The designer in charge of setting up such a network will find some useful recommendations, as well as some pitfalls to avoid. Before concluding, we look at current trends and discuss some open issues.
Deployment Techniques in Wireless Sensor Networks, Coverage and Connectivity: A Survey
IEEE Access, 2019
Wireless sensor networks (WSNs) have gained wide attention from researchers in the last few years because it has a vital role in countless applications. The main function of WSN is to process extracted data and to transmit it to remote locations. A large number of sensor nodes are deployed in the monitoring area. Therefore, deploying the minimum number of nodes that maintain full coverage and connectivity is of immense importance for research. Hence, coverage and connectivity issues, besides maximizing the network lifetime, represented the main concern to be considered in this paper. The key point of this paper is to classify different coverage techniques in WSNs into three main parts: coverage based on classical deployment techniques, coverage based on meta-heuristic techniques, and coverage based on self-scheduling techniques. Moreover, multiple comparisons among these techniques are provided considering their advantages and disadvantages. Additionally, performance metrics that must be considered in WSNs and comparison among different WSNs simulators are provided. Finally, open research issues, as well as recommendations for researchers, are discussed. INDEX TERMS Coverage, connectivity, deployment techniques, power consumption, wireless sensor network (WSN).
An Energy Efficient Barrier Coverage Algorithm for Wireless Sensor Networks
Intrusion detection is one of the most important applications of wireless sensor networks. When mobile objects are entering into the boundary of a sensor field or are moving cross the sensor field, they should be detected by the scattered sensor nodes before they pierce through the field of sensor (barrier coverage). In this paper, we propose an energy efficient scheduling method based on learning automata, in which each node is equipped with a learning automaton, which helps the node to select best node to guarantee barrier coverage, at any given time. To apply our method, we used coverage graph of deployed networks and learning automata of each node operates based on nodes that located in adjacency of current node. Our algorithm tries to select minimum number of required nodes to monitor barriers in deployed network. To investigate the efficiency of the proposed barrier coverage algorithm several computer simulation experiments are conducted. Numerical results show the superiority of the proposed method over the existing methods in term of the network lifetime and our proposed algorithm can operate very close to optimal method.
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Review of Coverage and Connectivity Issues in Deployment Algorithms for Wireless Sensor Networks
There are various applications of Wireless Sensor Networks (WSNs) including industrial, environmental, military, health applications etc. Gathering information about a given condition of environment in a given zone is the main task of these networks. The sensors are being deployed manually or randomly in the area to be monitored. Sensors are very small size and having different constraints like low energy, low communication range and low storage. The deployment strategies for WSN must be able to cope with obstacles and be energy efficient in order to increase the network lifetime. The deployment process is very much important in WSNs because coverage and connectivity is totally dependent on this. Here in this paper we present a review of coverage and connectivity issues and the impact of deployment on these factors. The paper presents the analysis of deployment issues and the factors influencing the deployment of WSNs. In conclusion he paper gives current trends and open issues in this area.
Sensor Deployment and Scheduling using Optimization Techniques in WSN
Network lifetime assumes an essential part in setting up an effective remote sensor network. This should be possible by conveying sensor nodes at ideal area and sensing these nodes in a manner that network accomplishes the most extreme network lifetime .In this report manufactured honey bee state calculation" and Particle swarm advancement " are utilized for sensor sending issue and Heuristics for planning reason. A similar study demonstrates artificial bee colony algorithm performs exceptional for sensor organization issues.
Self organization of sensor networks for energy-efficient border coverage
Journal of Communications and Networks, 2009
Networking together hundreds or thousands of cheap sensor nodes allows users to accurately monitor a remote environment by intelligently combining the data from the individual nodes. As sensor nodes are typically battery operated, it is important to efficiently use the limited energy of the nodes to extend the lifetime of the wireless sensor network (WSN). One of the fundamental issues in WSNs is the coverage problem. In this paper, the border coverage problem in WSNs is rigorously analyzed. Most existing results related to the coverage problem in wireless sensor networks focused on planar networks; however, three dimensional (3D) modeling of the sensor network would reflect more accurately real-life situations. Unlike previous works in this area, we provide distributed algorithms that allow the selection and activation of an optimal border cover for both 2D and 3D regions of interest. We also provide self-healing algorithms as an optimization to our border coverage algorithms which allow the sensor network to adaptively reconfigure and repair itself in order to improve its own performance. Border coverage is crucial for optimizing sensor placement for intrusion detection and a number of other practical applications.