CupCarbon: A new platform for the design, simulation and 2D/3D visualization of radio propagation and interferences in IoT networks

Bounceur, Ahcène; Clavier, Laurent; Combeau, Pierre; Olivier, M.; Vauzelle, Rodolphe; Masserann, Arnaud; Soler, Julien; Euler, Reinhardt; Alwajeeh, Taha; Vyas, Devendra,; Noreen, Umber; Soret, Émilie; Lounis, Massinissa

doi:10.1109/ccnc.2018.8319179

Cited by 33 publications

(13 citation statements)

References 8 publications

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“…Both scenarios are designed for small‐scale IoT and smart city networks. These scenarios are simulated and programmed with the CupCarbon simulator (CupCarbon Simulator, 2019 37 ). Here, the data for Figures 4 to 12 are gathered from “Google maps.” Further, it is uploaded and programmed over the CupCarbon simulator.…”

Section: Simulation Analysismentioning

confidence: 99%

A novel heuristic simulation‐optimization method for critical infrastructure in smart transportation systems

Kumar

Krishnamurthi

Jain

et al. 2020

Int J Communication

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Summary A simulation‐based optimization is a decision‐making tool that helps in identifying an optimal solution or a design for a system. An optimal solution and design are more meaningful if they enhance a smart system with sensing, computing, and monitoring capabilities with improved efficiency. In situations where testing the physical prototype is difficult, a computer‐based simulation and its optimization processes are helpful in providing low‐cost, speedy and lesser time‐ and resource‐consuming solutions. In this work, a comparative analysis of the proposed heuristic simulation‐optimization method for improving quality‐of‐service (QoS) is performed with generalized integrated optimization (a simulation approach based on genetic algorithms with evolutionary simulated annealing strategies having simplex search). In the proposed approach, feature‐based local (group) and global (network) formation processes are integrated with Internet of Things (IoT) based solutions for finding the optimum performance. Further, the simulated annealing method is applied for finding local and global optimum values supporting minimum traffic conditions. A small‐scale network of 50 to 100 nodes shows that genetic simulation optimization with multicriteria and multidimensional features performs better as compared to other simulation‐optimization approaches. Further, a minimum of 3.4% and a maximum of 16.2% improvement is observed in faster route identification for small‐scale IoT networks with simulation‐optimization constraints integrated model as compared to the traditional method. The proposed approach improves the critical infrastructure monitoring performance as compared to the generalized simulation‐optimization process in complex transportation scenarios with heavy traffic conditions. The communicational and computational‐cost complexities are least for the proposed approach.

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Section: Simulation Analysismentioning

confidence: 99%

A novel heuristic simulation‐optimization method for critical infrastructure in smart transportation systems

Kumar

Krishnamurthi

Jain

et al. 2020

Int J Communication

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“…CupCarbon [73]- [75] is a Smart City and Internet of Things WSN simulator for both scientific and educational purposes. Its objective is to provide reliable simulations for WSNs, mainly in terms of propagation and interference of signals.…”

Section: A Cupcarbonmentioning

confidence: 99%

An Efficient Ray-Tracing Based Model Dedicated to Wireless Sensor Network Simulators for Smart Cities Environments

2020

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“…CupCarbon [22] is a simulator that operates at the application layer of the nodes and will be next demonstrated adequate for network behavioural monitoring when in presence of a fire event. It integrates radio propagation and interference models which allows fast and accurate evaluation of link quality based on transmission conditions [23]. Sensor nodes can be placed on an actual geographical map through Open Street Map (OSM) framework.…”

Section: Wireless Sensor Networkmentioning

confidence: 99%

Simulation of an Early Warning Fire System

Lourenço

Fantoni

Vieira

2019

IFIP Advances in Information and Communication Technology

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In this paper, we will be using separate software tools (wireless network and Finite Differences Time Domain based simulators) to simulate the implementation of a wireless sensor network model based on low-rate/power transmission technology. The system operates in an unlicensed frequency range and the sensing nodes rely on surface plasmon resonance phenomenon for the detection of combustion by-products. More specifically, our simulations contemplate a system for early detection of fire in densely forested areas, which will then issue a warning in an automated way. As late detection of these events usually leads to severe flora, terrain, wild life and societal impact, an early warning system will provide better event assessment conditions, thus enabling efficient resources allocation, adequate response and would certainly be a promising improvement in minimizing such disruptive impairments.

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CupCarbon: A new platform for the design, simulation and 2D/3D visualization of radio propagation and interferences in IoT networks

Cited by 33 publications

References 8 publications

A novel heuristic simulation‐optimization method for critical infrastructure in smart transportation systems

A novel heuristic simulation‐optimization method for critical infrastructure in smart transportation systems

An Efficient Ray-Tracing Based Model Dedicated to Wireless Sensor Network Simulators for Smart Cities Environments

Simulation of an Early Warning Fire System

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