Multiple point of interest discovery and coverage with mobile wireless sensors

Erdelj, Milan; Natalizio, Enrico; Razafindralambo, Tahiry

doi:10.1109/iccnc.2012.6167394

Cited by 14 publications

(11 citation statements)

References 25 publications

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“…The outcome of the study still misses the benchmarking. Similar direction of the study considering mobility was also seen the work of Erdelj et al [15]. However, this study was evaluated using percentage covering time as the performance factor in both circular and random route approach.…”

Section: Related Worksupporting

confidence: 56%

Energy efficient scheme to Jointly Optimize Coverage and Connectivity in Large Scale Wireless Sensor Network

Sakkari

Basavaraju²

2015

IJECE

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Efficient coverage and connectivity are two important factors that ensures better service quality especially during tracking targets or monitoring events in wireless sensor network. Although massive amount of studies has been carried out in the past to enhance coverage and connectivity issues, till date very few studies have witnessed a significant and standard outcomes that can opt further. Hence, this paper introduces a computationally efficient technique for jointly addressing both coverage and connectivity problems in large-scale wireless sensor network that ensures optimal network lifetime too. The proposed system has been empirically designed, and algorithms formulated to ensure energy efficient monitoring of event. The outcomes of the study are compared with standard energy efficient hierarchical protocol to benchmark the results.

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Section: Related Worksupporting

confidence: 56%

Energy efficient scheme to Jointly Optimize Coverage and Connectivity in Large Scale Wireless Sensor Network

Sakkari

Basavaraju²

2015

IJECE

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“…Each of this point (called point of interest (PoI)) should therefore be covered by at least one sensor node. [18] assume that PoI are static and guarantee temporary coverage and intermittent connectivity with random deployment and distributed algorithm. [19] resolved a similar problem differently, and consider that PoI are not static.…”

Section: Point Coverage and Connectivitymentioning

confidence: 99%

A2CDC: Area Coverage, Connectivity and Data Collection in Wireless Sensor Networks

Bomgni

Mdemaya

2019

NPA

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Wireless sensor networks are increasingly being deployed in areas where several types of information need to be harvested. Monitoring a given area is one of the main goals of this technology. This consists in deploying sensor nodes in the Area of Interest (AoI) in order to detect any event occurring in this area, collect information and send them to the base station. However, in this type of configuration, the quantity and the quality of data collected are important factors in making better decisions by the end user. It therefore becomes crucial to deploy sensors in the AoI so that the latters can cover as much as possible the AoI, and propose mechanism to collect and send data to the base station while minimizing the energy consumption of the sensors. In this paper, we bring into focus a solution (A2CDC) to resolve this problem which performs in two main stages: in the first stage, we propose an algorithm that guarantees a maximal coverage of the AoI after a random deployment of static sensors and mobile sensors; and in the second stage, we propose a node activity scheduling that minimizes energy consumption of both static and mobile nodes while sending collected data to the base station. Compared to many other algorithms in the literature, our solution is better in term of coverage percentage of the AoI, data received by the base station and in term of energy minimization.

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“…Furthermore, a minimal safety distance among the UAVs needs to be defined prior to the UAV fleet deployment. To address the failure issues and keep the fleet functional, we advocate the usage of distributed multi-robot deployment algorithms [ 19 ] that can automatically reconfigure the fleet even with multiple simultaneous UAV failures.…”

Section: Architecture Implementationmentioning

confidence: 99%

From the Eye of the Storm: An IoT Ecosystem Made of Sensors, Smartphones and UAVs

Erdelj

Uk²,

Konam

et al. 2018

Sensors

Self Cite

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The development of Unmanned Aerial Vehicles (UAV) along with the ubiquity of Internet of Things (IoT) enables the creation of systems that, leveraging 5G enhancements, can provide real-time multimedia communications and data streaming. However, the usage of the UAVs introduces new constraints, such as unstable network communications and security pitfalls. In this work, the experience of implementing a system architecture for data and multimedia transmission using a multi-UAV system is presented. The system aims at creating an IoT ecosystem to bridge UAVs and other types of devices, such as smartphones and sensors, while coping with the fallback in an unstable communication environment. Furthermore, this work proposes a detailed description of a system architecture designed for remote drone fleet control. The proposed system provides an efficient, reliable and secure system for multi-UAV remote control that will offer the on-demand usage of available sensors, smartphones and unmanned vehicle infrastructure.

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Multiple point of interest discovery and coverage with mobile wireless sensors

Cited by 14 publications

References 25 publications

Energy efficient scheme to Jointly Optimize Coverage and Connectivity in Large Scale Wireless Sensor Network

Energy efficient scheme to Jointly Optimize Coverage and Connectivity in Large Scale Wireless Sensor Network

A2CDC: Area Coverage, Connectivity and Data Collection in Wireless Sensor Networks

From the Eye of the Storm: An IoT Ecosystem Made of Sensors, Smartphones and UAVs

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