A survey on area coverage in wireless sensor networks

Singh, Abhiram; Sharma, Teek Parval

doi:10.1109/iccicct.2014.6993073

Cited by 19 publications

(11 citation statements)

References 31 publications

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“…When sensors are placed for monitoring a large area for environmental changes, aftermath of natural disasters or military operations, it is not possible to place them deterministically due to the large number of nodes to be placed or the accessibility issues in these areas [14]. Generally during large scale sensor deployment in a geographically distributed manner, sensors are placed randomly by dropping them off from an airplane or some other method [15].…”

Section: Sensor Node Placementmentioning

confidence: 99%

Security Implementations in Smart Sensor Networks

Firdhous

2016

Trends in Ambient Intelligent Systems

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Wireless sensor networks have become one of the widely deployed networking technologies in the recent times due to the capabilities and advantages of them. The applications of wireless sensor networks include many civilian and industrial applications to military applications. Due to the distributed nature of these networks, deployment in remote and open areas and many constraints in individual nodes, these networks are vulnerable to several security threats. Many security mechanisms and algorithms proposed for the implementation in the traditional networks cannot be implemented in wireless sensor networks due to the unique nature of these networks and nodes. Many active research programmes have been carried out throughout the world for making wireless sensor networks more secure and user friendly. This chapter takes an in-depth look at some of the prominent mechanisms, schemes, algorithms and protocols published in the literature.

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Section: Sensor Node Placementmentioning

confidence: 99%

Security Implementations in Smart Sensor Networks

Firdhous

2016

Trends in Ambient Intelligent Systems

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“…Homogenous sensor nodes [16] have the same power processing capabilities, sensing range, communication range, and battery power. However, heterogeneous nodes are different in at least one of those capabilities.…”

Section: Classification Of Coverage Techniques In Wireless Sensormentioning

confidence: 99%

Deployment Techniques in Wireless Sensor Networks, Coverage and Connectivity: A Survey

et al. 2019

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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).

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“…Since those nodes are battery operated, energy is a critical issue in those networks. WSNs are used on various applications, such as in air pollution detection and area monitoring for military field (Singh and Sharma, 2014). In those applications, the replacement of dead nodes with new ones to offer energy is very difficult.…”

Section: Introductionmentioning

confidence: 99%

K-Means Clustering in WSN with Koheneon SOM and Conscience Function

Bataineh¹,

Samkari²,

Abdualla³

et al. 2019

MAS

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Wireless Sensor Networks (WSNs) are broadly utilized in the recent years to monitor dynamic environments which vary in a rapid way over time. The most used technique is the clustering one, such as Kohenon Self Organizing Map (KSOM) and K means. This paper introduces a hybrid clustering technique that represents the use of K means clustering algorithm with the KSOM with conscience function of Neural Networks and applies it on a certain WSN in order to measure and evaluate its performance in terms of both energy and lifetime criteria. The application of this algorithm in a WSN is performed using the MATLAB software program. Results demonstrate that the application of K-means clustering algorithm with KSOM algorithm enhanced the performance of the WSN which depends on using KSOM algorithm only in which it offers an enhancement of 11.11% and 3.33% in terms of network average lifetime and consumed energy, respectively. The comparison among the current work and a previous one demonstrated the effectiveness of the proposed approach in this work in terms of reducing the energy consumption.

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A survey on area coverage in wireless sensor networks

Cited by 19 publications

References 31 publications

Security Implementations in Smart Sensor Networks

Security Implementations in Smart Sensor Networks

Deployment Techniques in Wireless Sensor Networks, Coverage and Connectivity: A Survey

K-Means Clustering in WSN with Koheneon SOM and Conscience Function

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