A comprehensive evaluation of NoSQL datastores in the context of historians and sensor data analysis

Kalakanti, Arun Kumar; Sudhakaran, Vinay; Raveendran, Varsha; Menon, Nisha

doi:10.1109/bigdata.2015.7363952

Cited by 8 publications

(3 citation statements)

References 6 publications

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“…The growth of volume and heterogeneity of data sources, systems, workloads, and environment variability contributes to the complexity of data management. Traditional approaches, such as Relational Database Management Systems (RDBMS), might not be able to handle the deluge of industrial data they are experiencing, especially while addressing the need for improved performance, reliability, and user experience [10]. Gaining critical business insights by querying and analyzing such massive amounts of data is becoming a vital requirement [11].…”

Section: A the Challenge Of Protecting Critical Infrastructuresmentioning

confidence: 99%

“…Big Data NoSQL databases address such challenges with technologies such as MongoDB, HyperTable, Cassandra, and Amazon Dynamo offering scalability and performance predictability that is suitable for storing and indexing real-time streams of big datasets [283]. Kalakanti et al [10] evaluated different NoSQL datastores as a solution to the data and knowledge management challenges to meet the requirements of performance, reliability and scale imposed by the next generation of data historians as a central repository of SCADA systems.…”

Section: B the Impact Of Big Data Technologies On Cipmentioning

confidence: 99%

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A Survey on Forensics and Compliance Auditing for Critical Infrastructure Protection

Henriques,

Caldeira,

Cruz

et al. 2024

IEEE Access

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The broadening dependency and reliance that modern societies have on essential services provided by Critical Infrastructures is increasing the relevance of their trustworthiness. However, Critical Infrastructures are attractive targets for cyberattacks, due to the potential for considerable impact, not just at the economic level but also in terms of physical damage and even loss of human life. Complementing traditional security mechanisms, forensics and compliance audit processes play an important role in ensuring Critical Infrastructure trustworthiness. Compliance auditing contributes to checking if security measures are in place and compliant with standards and internal policies. Forensics assist the investigation of past security incidents. Since these two areas significantly overlap, in terms of data sources, tools and techniques, they can be merged into unified Forensics and Compliance Auditing (FCA) frameworks. In this paper, we survey the latest developments, methodologies, challenges, and solutions addressing forensics and compliance auditing in the scope of Critical Infrastructure Protection. This survey focuses on relevant contributions, capable of tackling the requirements imposed by massively distributed and complex Industrial Automation and Control Systems, in terms of handling large volumes of heterogeneous data (that can be noisy, ambiguous, and redundant) for analytic purposes, with adequate performance and reliability. The achieved results produced a taxonomy in the field of FCA whose key categories denote the relevant topics in the literature. Also, the collected knowledge resulted in the establishment of a reference FCA architecture, proposed as a generic template for a converged platform. These results are intended to guide future research on forensics and compliance auditing for Critical Infrastructure Protection.

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Section: A the Challenge Of Protecting Critical Infrastructuresmentioning

confidence: 99%

Section: B the Impact Of Big Data Technologies On Cipmentioning

confidence: 99%

A Survey on Forensics and Compliance Auditing for Critical Infrastructure Protection

Henriques,

Caldeira,

Cruz

et al. 2024

IEEE Access

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“…Last, in addition to the systems proposed by academia or produced through industrial research, many open-source and proprietary TSMSs have been developed, with the systems OpenTSDB, KairosDB, Druid, InfluxDB, and IBM Informix being popular examples. For information about selecting a TSMS for a particular workload see the following papers [12], [24], [25], [26], [27], [28], [29].…”

Section: Introductionmentioning

confidence: 99%

Time Series Management Systems: A Survey

Jensen

Pedersen

Thomsen

2017

IEEE Trans. Knowl. Data Eng.

137

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The collection of time series data increases as more monitoring and automation are being deployed. These deployments range in scale from an Internet of things (IoT) device located in a household to enormous distributed Cyber-Physical Systems (CPSs) producing large volumes of data at high velocity. To store and analyze these vast amounts of data, specialized Time Series Management Systems (TSMSs) have been developed to overcome the limitations of general purpose Database Management Systems (DBMSs) for times series management. In this paper, we present a thorough analysis and classification of TSMSs developed through academic or industrial research and documented through publications. Our classification is organized into categories based on the architectures observed during our analysis. In addition, we provide an overview of each system with a focus on the motivational use case that drove the development of the system, the functionality for storage and querying of time series a system implements, the components the system is composed of, and the capabilities of each system with regard to Stream Processing and Approximate Query Processing (AQP). Last, we provide a summary of research directions proposed by other researchers in the field and present our vision for a next generation TSMS.Comment: 20 Pages, 15 Figures, 2 Tables, Accepted for publication in IEEE TKD

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Designing a Recommender System for Touristic Activities in a Big Data as a Service Platform

Bellandi

Ceravolo

Damiani

et al. 2019

Intelligent Systems Reference Library

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A comprehensive evaluation of NoSQL datastores in the context of historians and sensor data analysis

Cited by 8 publications

References 6 publications

A Survey on Forensics and Compliance Auditing for Critical Infrastructure Protection

A Survey on Forensics and Compliance Auditing for Critical Infrastructure Protection

Time Series Management Systems: A Survey

Designing a Recommender System for Touristic Activities in a Big Data as a Service Platform

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