Traditional load shedding schemes can be inadequate in grids with high renewable penetration, leading to unstable events and unnecessary grid islanding. Although for both manual and automatic operating modes load shed...
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This paper addresses the problem of deploying complex systems in Kubernetes clusters. It discusses using the OperatorSDK framework supported by RedHat as a basis for implementing the Kubernetes operator for Lightweigh...
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The proliferation of data generation devices, including IoT and edge computing has led to the big data paradigm, which has considerably placed pressure on well-established relational databases during the last decade. ...
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ISBN:
(纸本)9781450398541
The proliferation of data generation devices, including IoT and edge computing has led to the big data paradigm, which has considerably placed pressure on well-established relational databases during the last decade. Researchers have proposed several alternative database models in order to model the captured data more efficiently. Among these approaches, graph databases seem the most promising candidate to supplement relational schemes. Within this study, a comparison is performed among Neo4j, one of the leading graph databases, and Apache Spark, a unified engine for distributed large-scale data processing environment, in terms of processing limits. More specifically, the two frameworks are compared on their capacity to execute community detection algorithms.
Fall is a serious health problem, it may threaten the life of many people in general and the life of the elderly in particular. That is why we tried very hard to develop a system to notify the mechanisms of their fall...
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The article explores the possibility of improving the reliability of a network with multipath routing. A feature of the proposed study is the analysis of the influence of the placement of switching nodes that switch p...
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The article proposes models of the structural reliability of a multipath routing network with the possibility of its reconfiguration when switching path segments. The models are focused on optimizing the placement of ...
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New storage requirements, analysis, and visualization of Big Data, which includes structured, semi-structured, and unstructured data, have caused the developers in the past decade to begin preferring Big Data database...
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A model for evaluating the availability of a fault-tolerant cluster with a constraint on the maximum query service time is proposed. Node recovery in the cluster involves replacing the entire computational node with t...
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In practice, extended Kalman filter (EKF) is one of the most popular lithium-ion battery (LIB) state of charge (SOC) estimation algorithms in electric vehicles onboard battery management system (BMS). With the increas...
In practice, extended Kalman filter (EKF) is one of the most popular lithium-ion battery (LIB) state of charge (SOC) estimation algorithms in electric vehicles onboard battery management system (BMS). With the increasing necessity of off-loading the computational burden and data storage capacity of onboard BMS, the application of battery digital twin and cloud-BMS are getting popularity. Therefore, to assess the performance of EKF in terms of accuracy, the computational time, and overall request and execution time, an EKF-based SOC estimation method is developed in the cloud platform of Amazon Web Services (AWS). For a specific battery test data set, the cloud-based EKF demonstrated a mean absolute error of 0.00226 and a request time of 0.028s that are highly satisfactory towards developing a digital twin enabled cloud-based BMS.
The rapid evolution of wireless communication technologies and the increasing demand for multi-functional systems have led to the emergence of integrated sensing and communication (ISAC) as a key enabler for future 6G...
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