Evaluation of monitoring tools for cloud computing environments

Sandoval, Yosandra; Gallizo, Georgina; Curiel, Mariela

doi:10.1109/clei.2012.6427251

Cited by 6 publications

(3 citation statements)

References 11 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…A comprehensive discussion on open source and commercial monitoring tools can be found in Sandoval et al 14 Some of these tools impose the use of a specific monitoring agent, while many commercial solutions do not provide the logic behind their functionalities. Moreover, all these applications still require someone to set the network baselines and to manually adapt them.…”

Section: Related Workmentioning

confidence: 99%

“…Forecast approaches can be divided into two categories, namely, parametric approaches and nonparametric approaches. Among the parametric approaches, autoregressive integrated moving average (ARIMA) model is widely recognized as an accepted framework to build traffic forecast model 14 . Proved to be theoretically well defined and practically effective, ARIMA has gradually been a benchmark in newly developed forecast model comparison.…”

Section: Related Workmentioning

confidence: 99%

See 1 more Smart Citation

Design, implementation, and evaluation of learning algorithms for dynamic real‐time network monitoring

et al. 2020

View full text Add to dashboard Cite

Network monitoring is necessary so as to ensure high reliability and availability in telecom networks. One of the main challenges posed by state‐of‐the‐art monitoring tools is the creation of network baselines. Such baselines include thresholds that can be used to determine whether monitored values (with a given context, e.g., time) represent normal network operation or not. The size and complexity of current (and future) networks make it infeasible to manually determine and set baselines for each network operator and metric, let alone adapting the thresholds to changes in network conditions. This leads to the use of default baselines and/or setting baselines only once and never changing them throughout the lifetime of network elements. This does not only cause inefficient operation but could have implications for network reliability and availability. In this paper, we present the design, implementation, and evaluation of DARN: a collection of analytics and machine learning‐based algorithms aimed at ensuring that network baselines are automatically adapted to different metric evolution. DARN has been comprehensively evaluated on a deployment with real traffic to confirm accuracy of generated baselines, a 22% improvement in accuracy due to baseline adaptation and a 72% reduction in false alarms.

show abstract

Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Design, implementation, and evaluation of learning algorithms for dynamic real‐time network monitoring

et al. 2020

View full text Add to dashboard Cite

show abstract

“…In the paper [16], the existing tools of monitoring are assessed, which can be used in cloud environments and later they include follow-up components of projects.…”

Section: Related Workmentioning

confidence: 99%

Use of body knowledge and cloud computing tools to develop software projects based in innovation

Quezada–Sarmiento

Enciso

Garbajosa

2016

2016 IEEE Global Engineering Education Conference (EDUCON)

View full text Add to dashboard Cite

A Body of Knowledge (BOK) is a term used to represent the complete set of concepts, terms, and activities that make up a professional domain. It encompasses the core teaching skills and research in a field or industry [13]. One of the main concerns of the software industry is to develop the talent of its human resources since the quality and innovation of its products and services depend of a great extent on the Knowledge, the ability, and the talent of technical engineers.In the educational area the used of BOK and Cloud Computing Tools are becoming the best way to provide solutions that meet the current need for greater collaboration between business,industry, education, and society; for this reason, the development of software products based in innovation is important for the professional life of a software engineering, since it leads to transform routine tasks into automated tasks; in the same way, it allows to manage processes focused on aligning services of Information Technology (IT) to the needs of companies with an emphasis on the benefits that the final customer added may perceive to the factor of I+D+I in order to create an innovative product. The current study focuses on the use of computer tools in the cloud in its phases: definition, planning, and control of software project based on the innovation as a tool for development and knowledge generation based in BOK.The tools of Computing in the Cloud analyzed were: Alfresco, Redbooth, DotProject, Dealines, and Redmine. The use of these tools permitted to obtain information to formulate a BOK in the context of projects.

show abstract

Comparative analysis of architectures for monitoring cloud computing infrastructures

Calero

Aguado

2015

Future Generation Computer Systems

View full text Add to dashboard Cite

Evaluation of monitoring tools for cloud computing environments

Cited by 6 publications

References 11 publications

Design, implementation, and evaluation of learning algorithms for dynamic real‐time network monitoring

Design, implementation, and evaluation of learning algorithms for dynamic real‐time network monitoring

Use of body knowledge and cloud computing tools to develop software projects based in innovation

Comparative analysis of architectures for monitoring cloud computing infrastructures

Contact Info

Product

Resources

About