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BMC based Data Logger for Performance Analysis

Nikhilesh Nayak, Dheerendra Singh Tomar, Shanmugasundaram M. Published in Information Sciences

International Journal of Applied Information Systems
Year of Publication: 2017
Publisher: Foundation of Computer Science (FCS), NY, USA
Authors:Nikhilesh Nayak, Dheerendra Singh Tomar, Shanmugasundaram M.
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  1. Nikhilesh Nayak, Dheerendra Singh Tomar and Shanmugasundaram M.. BMC based Data Logger for Performance Analysis. International Journal of Applied Information Systems 12(9):37-40, December 2017. URL, DOI BibTeX

    	author = "Nikhilesh Nayak and Dheerendra Singh Tomar and Shanmugasundaram M.",
    	title = "BMC based Data Logger for Performance Analysis",
    	journal = "International Journal of Applied Information Systems",
    	issue_date = "December 2017",
    	volume = 12,
    	number = 9,
    	month = "Dec",
    	year = 2017,
    	issn = "2249-0868",
    	pages = "37-40",
    	url = "",
    	doi = "10.5120/ijais2017451732",
    	publisher = "Foundation of Computer Science (FCS), NY, USA",
    	address = "New York, USA"


In the present scenario, a server rack has multiple platforms attached to it, each designed to perform a different set of actions, thus, having different hardware requirements. To increase the throughput of such a platform either the hardware requirements are multiplied or the platform is replaced completely. This unoptimized method is rather expensive and inefficient. [1] This paper focuses on improving the performance of a system by providing accurate analysis and predict hardware requirements to improve overall throughput. For this, data logs are collected over a period of time which take performance data dumps of sensors connected to the platform via BMC. These sensors monitor the platform and measure its internal physical parameters. This data is then used to create a database and a training set. This set is used to train a machine learning algorithm which gives an efficient algorithm to analyze the present performance and give accurate prediction. This gives an optimal solution to increase throughput of a platform. [2]


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Data logger, sensors, python, IPMI, BMC, machine learning, database and performance