Devesh Pratap Singh

Work place: Dept. of Computer Science and Engineering, Graphic Era Deemed to be University, Dehradun, Uttarakhand, India

E-mail: deveshpratap.85@gmail.com

Website:

Research Interests: Information-Theoretic Security, Data Structures and Algorithms, Wireless Communication, Wireless Networks, Computer Networks, Information Security, Network Security

Biography

Dr. Devesh Pratap Singh received the M.Tech. degree in computer science and engineering from Uttarakhand Technical University, Dehradun, India, in 2009, and the Ph.D. degree, in 2015. He is currently a Professor and the Head of the Computer Science and Engineering Department, Graphic Era deemed to be University, Dehradun, India. He has published more than 50 research articles in his area of expertise. His research interests include information security, wireless sensor networks, the Internet of Things, and soft computing.

Author Articles
A Theoretical Graph based Framework for Parameter Tuning of Multi-core Systems

By Surendra Kumar Shukla Devesh Pratap Singh Shaili Gupta Kireet Joshi Vishan Kumar Gupta

DOI: https://doi.org/10.5815/ijwmt.2022.04.02, Pub. Date: 8 Aug. 2022

Multi-core systems are outperforming nowadays. Therefore, various computing paradigms are intrinsically incorporated in the multicore domain to exploit its potential and solve well known computing problems. Parameter tuning is a well-known computing problem in the field of Multicore domain. Addressing the said hurdle would leverage in the performance enhancement of Multicore systems. Various efforts in this direction have been made through the conventional parameter tuning algorithms in a limited scope; however, the problem is yet not addressed completely. In this research article, we have addressed parameter tuning problem by employing applications of graph theory, especially Dijkstra shortest path algorithm to address the said issue. Dijkstra’s principle has been applied to establish correlation among the parameters further tuning by finding the pair of suitable parameters. Two other algorithms which are based on application feedback (to provide performance goals to the system) has been introduced. The proposed algorithms collectively (as a framework), addressed the parameter tuning problem. The effectiveness of the algorithms is verified and further measured in distinct parameter tuning scenarios and promising outcome has been achieved.

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