The Intellectual IoT-System for Monitoring the Base Station Quality of Service

Globa, Larysa; Kurdecha, Vasyl; Ishchenko, Ivan; Zakharchuk, Andrii; Kunieva, Nataliia

doi:10.1109/blackseacom.2018.8433715

Cited by 12 publications

(4 citation statements)

References 10 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Unfortunately the depicted V-factors for Big Data are growing faster than the performance of their analysis (in Mbyte/s or in GFLOPS) via classical computational techniques. Therefore, for Industry 4.0, IoT systems and M2M not only improvements in networking but also in analytic blocks became very significant [1][2][3][4][5][6][7]27,29], which aimed at decreasing of data streams and their algorithmic complexity. The "heavy-weighting approaches" involving precise analytical techniques and expensive specialized software are used for this aim.…”

Section: The 6v Prevention Factorsmentioning

confidence: 99%

“…In this regard, there is a need to systematize and classify data from various sources. Ontological models are used as a problem solution [27][28][29]. This is the first step for Big Data overcoming.…”

Section: Example 5: An Approachof Big Data Complexity Overcoming For mentioning

confidence: 99%

“…FKB correctness checking is discussed in [10]. The obtained FKB can be used as the basis for a decision block [29] for IoT or other telecoms platforms ( Fig.7). Fig.…”

Section: Example 5: An Approachof Big Data Complexity Overcoming For mentioning

confidence: 99%

See 2 more Smart Citations

Industry 4.0 and Modern Approaches for Big Data Analytics

Luntovskyy

Globa

2019

Information and Telecommunication Sciences

Self Cite

View full text Add to dashboard Cite

Background. With the acceleration of industrial development, i.e. with the new "Industry 4.0", structuring and processing of acquired voluminous and heterogeneous data become considerably more complicated and represents an important scientificpractical problem. Cyber-PHY, IoT, sensor networks, robotics, multiple real-time applications can generate large arrays of unmanaged, weakly structured and non-configured data of various types, known as "Big Data". However, the problem of "Big Data" is very hard to solve nowadays. Objective. The purpose of the presented in this paper research is to analyze the sources of Big data, determine their main characteristics and suggest the ways for overcoming the growing dimension of Big data. Methods. In contradistinction to traditional ways of the Big data problem solving, when only dealing with certain empirical approaches and models, the paper proposes to introduce ontologies for describing data groups, use compression of data volumes into knowledge that significantly reduces their volumes and improves understanding of their sense. Results. The effectiveness of given solutions is confirmed by the best known practices and our own case studies aimed at overcoming this well-known complex problem. Conclusions. To overcome the problem of "Big Data" there is no single universal solution. The analysis shows that the solution can be found by introducing ontologies, determining the mutual influences and correlations between the data, thus gaining knowledge based on a huge amount of data.

show abstract

Section: The 6v Prevention Factorsmentioning

confidence: 99%

Section: Example 5: An Approachof Big Data Complexity Overcoming For mentioning

confidence: 99%

See 1 more Smart Citation

Industry 4.0 and Modern Approaches for Big Data Analytics

Luntovskyy

Globa

2019

Information and Telecommunication Sciences

Self Cite

View full text Add to dashboard Cite

show abstract

“…These consist of a ship, a crane installed on the ship, a cable lifting gear, a winch, slings, or rigging, and a package to be put down or taken up [2,3] . During these operations, various risks are present: the imprecision of the position of the package, the collision between the package and the ship, sudden forces in the cables, etc [4]. This is why it is necessary to model and simulate this type of operation to prevent risks.…”

Section: Introductionmentioning

confidence: 99%

A Theoretical Approach of Deep-Water Drilling

2023

IRJMETS

View full text Add to dashboard Cite

Drilling in deep sea is an emerging research area that arouses interest of numerous researcher. Petroleum, mining, geology and many other areas are involve in deep water drilling. This research will present theatrically risks and cost of marine operation with focus on deep part of see. During these operations, various risks are present: the imprecision of the position of the package, the collision between the package and the ship, sudden forces in the cables.

show abstract

Conditionally Infinite Telecommunication Resource for Subscribers

Globa

Skulysh

Siemens

2020

Advances in Information and Communication Technology and Systems

Self Cite

View full text Add to dashboard Cite

Modern communication systems should provide the end user with a conditionally infinite telecommunication resource. To ensure guaranteed quality, services are combined into groups. A group of similar services with the same service process requirements is called a slice. Using software-defined networks (SDN) allows to deploy a management system slices and telecommunications resources that are allocated for their maintenance. This is possible only using the latest telecommunication technologies, and seamless user connection management. The article proposes an original methodology for managing the servicing streams process in network service providers tunnels. The methodology uses the allowable service node load calculation, overload prediction and live migration algorithms to seamlessly change the service node for the flow.

show abstract

The Intellectual IoT-System for Monitoring the Base Station Quality of Service

Cited by 12 publications

References 10 publications

Industry 4.0 and Modern Approaches for Big Data Analytics

Industry 4.0 and Modern Approaches for Big Data Analytics

A Theoretical Approach of Deep-Water Drilling

Conditionally Infinite Telecommunication Resource for Subscribers

Contact Info

Product

Resources

About