Optimal Placement of Data Aggregation Points for Smart Metering using Wireless Heterogeneous Networks

Inga, Esteban; Campaña, Miguel; Hincapié, Roberto; Céspedes, Sandra

doi:10.1109/colcomcon.2018.8466731

Cited by 6 publications

(10 citation statements)

References 11 publications

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“…In addition, it is essential to remember that all applications must be scalable, as noted in [ 19 ]. There were also contributions to the dimensioning of wireless sensor networks, as presented in [ 20 ]. Furthermore, when deploying a wireless network for smart cities, for more sensors to be incorporated daily to generate new services, the WSN must be flexible, and the proposed algorithms must converge to the optimal solution on time for fast management.…”

Section: Related Workmentioning

confidence: 99%

Novel Approach Sizing and Routing of Wireless Sensor Networks for Applications in Smart Cities

Inga

Ortega

2021

Sensors

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Citizens are expected to require the growth of multiple Internet of Things (IoT) -based applications to improve public and private services. According to their concept, smart cities seek to improve the efficiency, reliability, and resilience of these services. Consequently, this paper searches for a new vision for resolving problems related to the quick deployment of a wireless sensor network (WSN) by using a sizing model and considering the capacity and coverage of the concentrators. Additionally, three different routing models of these technology resources are presented as alternatives for each WSN deployment to ensure connectivity between smart meters and hubs required for smart metering. On the other hand, these solutions must reduce costs when this type of wireless communication network is deployed. The present work proposes various optimization models that consider the physical and network layers in order to integrate different wireless communication technologies, thus reducing costs in terms of the minimum number of data aggregation points. Using a heterogeneous wireless network can reduce resource costs and energy consumption in comparison to a single cellular technology, as proposed in previous works. This work proposes a sizing model and three different models for routing wireless networks. In each case, constraints are evaluated and can be associated with different real-world scenarios. This document provides an optimization model that encompasses all of the proposed constraints; due to the combinatorial nature of the problem, this would require a heuristic technique.

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Section: Related Workmentioning

confidence: 99%

Novel Approach Sizing and Routing of Wireless Sensor Networks for Applications in Smart Cities

Inga

Ortega

2021

Sensors

Self Cite

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“…Given small AMI networks, with a small number of smart meters (SMs) and concentrators (UDAPs) (e.g., 10 to 30 nodes), the optimization problem falls into a convex area and can be solved using linear programming. In [18], the authors proposed solutions that required reduced computational and time resources, aiming to achieve an optimal routing considering a set of feasible links placed in a small mesh network; such a scenario does not require a column generation algorithm or heuristic. Similar situations were shown in [19,20], which could also consider multi-hop routing and resource allocation problems.…”

Section: Related Workmentioning

confidence: 99%

Capacitated Multicommodity Flow Problem for Heterogeneous Smart Electricity Metering Communications Using Column Generation

2019

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This paper addresses the planning and deployment of wireless heterogeneous networks (WHNs) for smart metering, based on a cross-layer solution. We combine the constraints of the network layer that considers routing and flow demands at each link in the WHN, while at the same time, we account for the restrictions of the physical layer referred to the capacity of a short range technology when used in a multi-hop fashion. We propose a model based on a column generation approach to solve the capacitated multicommodity flow problem (CMCF); the model includes wireless links capacities, coverage, and cost. The work integrates the multi-hop routing of packets in a mesh network formed by smart meters and concentrators connected to a cellular network via base stations. The traffic of each link is represented in a multigraph with the occupation percentage, and we build a scalable routing tree on a georeferenced map to represent a real deployment. The results describe the behavior of the proposed model in terms of the traffic load per concentrator, the network coverage, and the reduction of energy consumption. We demonstrate that an infrastructure cost reduction is achieved with the inclusion of multi-hop short range technology, which reduces the number of smart meters that require a direct connection to cellular technology. The model guarantees 100% coverage of the smart meters analyzed in each scenario. The calculation time of the CMCF for advanced metering infrastructure (CMCF-AMI) based on the column generation algorithm as the population increases is reduced by 10%, and this is the expected return when the population is considerable.

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“…En los últimos años la penetración de energía renovable ha generado aportes significativos de potencia al sistema eléctrico convencional. En trabajos previos [28]- [30] advertimos la importancia de adecuados sistemas de comunicación para que su operación con los sistemas convencionales sea óptima y segura, de tal manera que, se garantice la calidad y continuidad del servicio eléctrico desde la empresa distribuidora hacia los consumidores finales.…”

Section: Impactos Por Integración Masiva De Veeunclassified

Despliegue óptimo georreferenciado de estaciones de carga vehicular pública considerando capacidad de flujo y distancias máximas habilitantes

Campaña

Inga

2019

I+D Tecnológico

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Los desafíos modernos están orientados a la reducción significativa de gases de efecto invernadero, los cuales, deterioran la calidad del aire. El parque automotor, suministros de energía (gas, vapor, aire acondicionado, agua para uso industrial y energía eléctrica) son fuentes de que se liberan en la atmosfera. Es por ello que, el presente artículo propone un modelo heurístico orientado a la reducción significativa de la dependencia de vehículos de combustión interna. El éxito o desacierto de la penetración masiva de vehículos eléctricos enchufables (VEE) no solo dependerá de la capacidad instalada en los sistemas eléctricos de distribución, sino que, además, de la autonomía y confort que los VEE logren brindar al usuario final. Por lo tanto, con el algoritmo Mínimo Emplazamiento de Estaciones de Carga Geolocalizadas (MEECG) se propone un modelo capaz de emplazar infraestructuras de estaciones de carga pública (IECP) considerando flujo vehicular y distancias máximas habilitantes. De tal manera que, se seleccione el mínimo número de estaciones de carga pública (ECP) garantizando la posibilidad de que un VEE pueda conectarse a una ECP reduciendo al máximo la ansiedad de alcance de parte del operador del VEE.

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Optimal Placement of Data Aggregation Points for Smart Metering using Wireless Heterogeneous Networks

Cited by 6 publications

References 11 publications

Novel Approach Sizing and Routing of Wireless Sensor Networks for Applications in Smart Cities

Novel Approach Sizing and Routing of Wireless Sensor Networks for Applications in Smart Cities

Capacitated Multicommodity Flow Problem for Heterogeneous Smart Electricity Metering Communications Using Column Generation

Despliegue óptimo georreferenciado de estaciones de carga vehicular pública considerando capacidad de flujo y distancias máximas habilitantes

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