Optimization of System’s Performance with Kernel Tracing by Cohort Intelligence | Zendy

Aniket B. Tate | Zendy; Laxmi Bewoor | Zendy

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Optimization of System’s Performance with Kernel Tracing by Cohort Intelligence

Author(s) -

Aniket B. Tate,

Laxmi Bewoor

Publication year - 2017

Publication title -

international journal of information technology and computer science

Language(s) - English

Resource type - Journals

eISSN - 2074-9015

pISSN - 2074-9007

DOI - 10.5815/ijitcs.2017.06.08

Subject(s) - tracing , computer science , cohort , trace (psycholinguistics) , cohort effect , kernel (algebra) , field (mathematics) , artificial intelligence , machine learning , data mining , statistics , operating system , mathematics , combinatorics , linguistics , philosophy , pure mathematics

Linux tracing tools are used to record the events running in the background on the system. But these tools lack to analyze the log data. In the field of Artificial Intelligence Cohort Intelligence (CI) is recently proposed technique, which works on the principle of selflearning within a cohort. This paper presents an approach to optimize the performance of the system by tracing the system, then extract the information from trace data and pass it to cohort intelligence algorithm. The output of cohort intelligence algorithm shows, how the load of the system should be balanced to optimize the performance.

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