On the scalable collection of metering data in smart grids through message concatenation

Karimi, Babak; Namboodiri, Vinod; Jadliwala, Murtuza

doi:10.1109/smartgridcomm.2013.6687977

Cited by 19 publications

(9 citation statements)

References 4 publications

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“…Para crear una infraestructura de medición avanzada se han realizado varios aportes científicos que han buscado dar solución desde diferentes frentes y así conseguir una medición inteligente de energía eléctrica; sin embargo, las restricciones propias de la tecnología, las zonas, el costo, hacen de la planeación de la red de comunicaciones un problema no trivial que en términos de optimización se describe como un problema NP-Complete dentro de los capítulos propios de problemas combinatorios; por lo tanto, conseguir una única solución que nos entregue el óptimo global de la planeación de la red de comunicaciones resulta inviable; sin embargo, es posible advertir que las tecnologías se encuentran maduras y/o ya desplegadas con el objeto de minimizar el costo y garantizar la confiabilidad de la red [2], [5], [23]- [25].…”

Section: Figura 1 Infraestructura De Medición Avanzada Usando Redes unclassified

Óptima planeación de recursos para redes eléctricas inteligentes usando modelos heurísticos

Inga¹,

Campaña²

2019

Aplicaciones E Innovación De La Ingeniería en Ciencia Y Tecnología

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All the contents of this work, except where otherwise noted, is licensed under a Creative Commons Attribution 4.0 International license. Todo o conteúdo deste trabalho, exceto quando houver ressalva, é publicado sob a licença Creative Commons Atribição 4.0. Todo el contenido de esta obra, excepto donde se indique lo contrario, está bajo licencia de la licencia Creative Commons Reconocimento 4.0.

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Section: Figura 1 Infraestructura De Medición Avanzada Usando Redes unclassified

Óptima planeación de recursos para redes eléctricas inteligentes usando modelos heurísticos

Inga¹,

Campaña²

2019

Aplicaciones E Innovación De La Ingeniería en Ciencia Y Tecnología

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“…All of the proposed heuristics (except EDF-FCFS) employ the 0−1 knapsack algorithm [16] to decide which messages to fit into the packet among the various options available. More details of the implementation of our proposed heuristics and associated pseudocode can be found in [17].…”

Section: B Heuristicsmentioning

confidence: 99%

Scalable Meter Data Collection in Smart Grids Through Message Concatenation

Karimi

Namboodiri

Jadliwala

2015

IEEE Trans. Smart Grid

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Advanced metering infrastructure (AMI) initiatives are a popular tool to incorporate changes for modernizing the electricity grid, reduce peak loads, and meet energy efficiency targets. There is the looming issue of how to communicate and handle consumer data collected by electric utilities and manage limited communication network resources. Several data relay points are required to collect data distributedly and send them through a communication backhaul. This paper studies the smart meter message concatenation (SMMC) problem of how to efficiently concatenate multiple small smart metering messages arriving at data concentrator units in order to reduce protocol overhead and thus network utilization. This problem needs to deal with the added constraint that each originating message from its source may have its own stated deadline that must be taken into account during the concatenation process. This paper provides hardness results for the SMMC problem, and proposes six heuristics and evaluates them to gain a better understanding of the best data volume reduction policies that can be applied at data concentrators of AMI infrastructures. These results are further tested for feasibility under practical settings based on aspects, such as network and processing delays, tightness of application deadlines, and lossy backhaul links.Index Terms-Advanced metering infrastructure (AMI), algorithms, communication networks, data management.

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“…These approaches, although providing strong guarantees of confidentiality, are very heavy from a computational and communicational stand-point and may not be feasible on lowend smart meters with limited computation capabilities [62]. Considering the huge scale of future smart meter deployment and the granularity of the data being gathered, existing communication networks will have difficulty handling this data because of resource constraints such as network capacity (bandwidth) [66,67,68]. Homomorphic cryptosystems usually generate an output of a huge fixed-length as compared with the data generated by smart meters.…”

Section: Introductionmentioning

confidence: 99%

“…This ciphertext can be up to one hundred times larger than the actual smart meter data [3]. Given the frequency of the data being sent and possible bandwidth scarcity, this can lead to unacceptable delay and network overhead [66].…”

Section: Introductionmentioning

confidence: 99%

Towards Efficient Privacy Preserving Data Aggregation for Advanced Metering Infrastructure

Alamatsaz¹,

Boustani²,

Alamatsaz³

et al. 2017

IJCNC

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Recent changes to the existing power grid are expected to influence the way energy is pro-vided and consumed by customers. Advanced Metering Infrastructure (AMI) is a tool to incorporate these changes for modernizing the electricity grid. Growing energy needs are forcing government agencies and utility companies to move towards AMI systems as part of larger smart grid initiatives. The smart grid promises to enable a more reliable, sustainable, and efficient power grid by taking advantage of information and communication technologies. However, this information-based power grid can reveal sensitive private information from the user's perspective due to its ability to gather highly-granular power consumption data. This has resulted in limited consumer acceptance and proliferation of the smart grid. Hence, it is crucial to design a mechanism to prevent the leakage of such sensitive consumer usage information in smart grid. Among different solutions for preserving consumer privacy in Smart Grid Networks (SGN), private data aggregation techniques have received a tremendous focus from security researchers. Existing privacy-preserving aggregation mechanisms in SGNs utilize cryptographic techniques, specifically homomorphic properties of public-key cryptosystems. Such homomorphic approaches are bandwidth-intensive (due to large output blocks they generate), and in most cases, are computationally complex. In this paper, we present a novel and efficient CDMA-based approach to achieve privacy-preserving aggregation in SGNs by utilizing random perturbation of power consumption data and with limited use of traditional cryptography. We evaluate and validate the efficiency and performance of our proposed privacy-preserving data ag-gregation scheme through extensive statistical analyses and simulations.

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On the scalable collection of metering data in smart grids through message concatenation

Cited by 19 publications

References 4 publications

Óptima planeación de recursos para redes eléctricas inteligentes usando modelos heurísticos

Óptima planeación de recursos para redes eléctricas inteligentes usando modelos heurísticos

Scalable Meter Data Collection in Smart Grids Through Message Concatenation

Towards Efficient Privacy Preserving Data Aggregation for Advanced Metering Infrastructure

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