Deployment and Coverage in Wireless Sensor Networks: A Perspective

Singh, Yashwant; Lone, Jahangir Ahmad; Singh, Pradeep; Pólkowski, Zdzisław; Tanwar, Sudeep; Tyagi, Sudhanshu

doi:10.1109/ecai46879.2019.9042091

Cited by 4 publications

(4 citation statements)

References 19 publications

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“…The most important advantage of this strategy is the fast and simple implementation. However, problems such as energy imbalance and coverage gaps may arise with these methods [10], [16]- [18].…”

Section: A Coverage In Wsnsmentioning

confidence: 99%

Vibrational Genetic Algorithm-Based Deployment of Wireless Sensor Networks With Heterogeneous Nodes in Irregularly Shaped Areas

Birtane,

Sahingoz,

Korkmaz

2024

IEEE Access

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Over the past few years, there has been a significant emphasis on improving the capabilities of Wireless Sensor Networks (WSNs) by making advancements in communication protocols, energy efficiency, optimal deployment, data analytics, and integration with emerging technologies such as the Internet of Things and artificial intelligence. The deployment of WSN nodes can greatly enhance the effectiveness, scalability, and capability of different systems, resulting in cost reductions, enhanced performance, and improved safety in which the deployment of WSN involves determining the best positioning of sensor nodes to attain maximum coverage and connectivity while minimizing the number of nodes needed. WSNs often face challenges in deploying nodes effectively and Genetic Algorithms (GAs) offer a valuable approach for tackling this problem due to their ability to efficiently search large and complex solution spaces, such as those of complex network design, taking into account various constraints and objectives, which are common characteristics of real-world WSN deployment scenarios. The objective of this study is to use a new method, called the vibrational genetic algorithm, which can be used to optimize the placement of sensor nodes more efficiently. Apart from the other research, it is preferred to use heterogeneous sensor nodes to increase the coverage rate in an irregularly shaped area. The results of the experiments demonstrate that the proposed model offers an effective solution for achieving maximum coverage in application theaters that are more realistic and complex.

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Section: A Coverage In Wsnsmentioning

confidence: 99%

Vibrational Genetic Algorithm-Based Deployment of Wireless Sensor Networks With Heterogeneous Nodes in Irregularly Shaped Areas

Birtane,

Sahingoz,

Korkmaz

2024

IEEE Access

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“…The sensor nodes' optimal numbers are computed using various methods like disk model, sector model, and geometry pattern model [11]. Whereas if the localization is known, then the problem of the optimal deployment in the Urban area of monitoring and deployment of WSN prefer an integer programming where popular method like i) divide-andconquer, ii) simulated annealing, and iii) Genetic Algorithm, but these methods pose additional overhead of time complexity [12]. Irrespective of these methods, there exist some unique challenges for the deployment of the WSN for UEMS.…”

Section: Intelligent Systemmentioning

confidence: 99%

A Secure Communication Process of Wireless Sensor Network Architecture for Smart Urban Environment Monitoring Applications

Bhaskar¹,

Chakravarthi²

2021

IJACSA

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Wireless Sensor Network has been increasingly used for remote monitoring system and its adoption in increasing exponentially for larger application too. However, there are various challenges associated with both resource management and security that roots up when the deployment scale goes massive and distributed in order. The proposed system considers a case study of smart city management where the problems associated with data transmission and security has been addressed. This is carried out using the provisioning of urban environment monitoring system that is an essential system for smart city projects to assure the citizens' better-quality wellbeing. The scalable and effective urban environment monitoring system requires a seamless transmission of the data from the sensor nodes to the analytics engine. The existing architectures are more designed to suit very specifically the use-cases. As a contribution, the proposed system introduces a cost-effective architecture for environmental monitoring in urban zones of smart city named as a Smart Sensor Surveillance System (4S-UEM). The core idea of the proposed system is to offer a balance between resource efficiency and resilience secure communication in large scale deployment of WSN considering smart city as deployment and assessment area. The proposed system makes use of urban geographical clustering process in order to develop an organized structure of sensor nodes. Different from any existing studies, the proposed system introduces data analytical engine followed by secure routing using gateway. The design of the proposed system is carried out using layered architecture of the communication model targeting towards a cost-effective, energy optimal, and secure data transmission to the analytics engine.

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“…The proposed framework for e-healthcare is shown in Figure 10 . As the proposed algorithm saves energy, the healthcare devices that are sensor-enabled can work for longer duration, and easy deployment and data analysis is possible due to IoT integration [ 34 , 35 , 36 , 37 , 38 ]. According to the proposed architecture, there can be any different kind of sensor nodes, such as smart wearables, sensors collecting health data like temperature, heartbeat, number of steps taken every day, sleep patterns, etc.…”

Section: Proposed Frameworkmentioning

confidence: 99%

An Intelligent Opportunistic Routing Algorithm for Wireless Sensor Networks and Its Application Towards e-Healthcare

Bangotra¹,

Singh

Selwal

et al. 2020

Sensors

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The lifetime of a node in wireless sensor networks (WSN) is directly responsible for the longevity of the wireless network. The routing of packets is the most energy-consuming activity for a sensor node. Thus, finding an energy-efficient routing strategy for transmission of packets becomes of utmost importance. The opportunistic routing (OR) protocol is one of the new routing protocol that promises reliability and energy efficiency during transmission of packets in wireless sensor networks (WSN). In this paper, we propose an intelligent opportunistic routing protocol (IOP) using a machine learning technique, to select a relay node from the list of potential forwarder nodes to achieve energy efficiency and reliability in the network. The proposed approach might have applications including e-healthcare services. As the proposed method might achieve reliability in the network because it can connect several healthcare network devices in a better way and good healthcare services might be offered. In addition to this, the proposed method saves energy, therefore, it helps the remote patient to connect with healthcare services for a longer duration with the integration of IoT services.

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Deployment and Coverage in Wireless Sensor Networks: A Perspective

Cited by 4 publications

References 19 publications

Vibrational Genetic Algorithm-Based Deployment of Wireless Sensor Networks With Heterogeneous Nodes in Irregularly Shaped Areas

Vibrational Genetic Algorithm-Based Deployment of Wireless Sensor Networks With Heterogeneous Nodes in Irregularly Shaped Areas

A Secure Communication Process of Wireless Sensor Network Architecture for Smart Urban Environment Monitoring Applications

An Intelligent Opportunistic Routing Algorithm for Wireless Sensor Networks and Its Application Towards e-Healthcare

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