Zobrazeno 1 - 10
of 92
pro vyhledávání: '"Umamaheswari, E"'
Publikováno v:
In Heliyon 15 September 2024 10(17)
An efficient proactive VM consolidation technique with improved LSTM network in a cloud environment.
Autor:
Dinesh Kumar, K.1 (AUTHOR) kdinesh.kumar2015@vit.ac.in, Umamaheswari, E.2 (AUTHOR)
Publikováno v:
Computing. Jan2024, Vol. 106 Issue 1, p1-28. 28p.
Publikováno v:
In Materials Today: Proceedings 2022 62 Part 7:4788-4794
Autor:
Kumar K. Dinesh, Umamaheswari E.
Publikováno v:
Cybernetics and Information Technologies, Vol 20, Iss 4, Pp 55-73 (2020)
For cloud providers, workload prediction is a challenging task due to irregular incoming workloads from users. Accurate workload prediction is essential for scheduling the resources to the cloud applications. Thus, in this paper, the authors propose
Externí odkaz:
https://doaj.org/article/537d13f67ce948e28c11eeb780aed5a7
Autor:
Kumar, K. Dinesh, Umamaheswari, E.
Publikováno v:
In Procedia Computer Science 2019 165:151-157
Akademický článek
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Publikováno v:
In Energy Procedia June 2017 117:501-508
Publikováno v:
ITM Web of Conferences, Vol 37, p 01020 (2021)
The COVID-19 corona virus has affected 81.9 million people with 1.79 million deaths in the entire world and has transformed into a global pandemic. The disease has effected 10.2 million people in India with about 148K deaths till December 2020. The C
Externí odkaz:
https://doaj.org/article/34289b9e8c1a43ae87ab47d798e63751
Publikováno v:
International Journal of Information Security and Privacy. 16:1-17
This paper presents a proposed Objective Function (OF) design using various routing metrics for improving the performance of IoT applications. The most important idea of the proposed design is the selection of the routing metrics with respect to the
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a25ee9797b76cf03a37326bde8b6200c
https://doi.org/10.4018/ijisp.285583
https://doi.org/10.4018/ijisp.285583
Autor:
Umamaheswari E., Geetha T.V.
Publikováno v:
Journal of Intelligent Systems, Vol 23, Iss 1, Pp 59-73 (2014)
Traditional document clustering algorithms consider text-based features such as unique word count, concept count, etc. to cluster documents. Meanwhile, event mining is the extraction of specific events, their related sub-events, and the associated se
Externí odkaz:
https://doaj.org/article/d952049b6c77482ab713be5d0054267e