Rama Shankar Yadav

Work place: Motilal Nehru National Institute of Technology, Allahabad, India

E-mail: yadavrs64@gmail.com

Website:

Research Interests: Computer systems and computational processes, Embedded System, Systems Architecture, Network Architecture, Parallel Computing

Biography

Rama Shankar Yadav is currently a professor at Motilal Nehru National Institute of Technology, Allahabad, India. He received his Ph.D. degree from the Indian Institute of Technology (IIT) Roorkee, M.S. degree from Birla Institute of Technology and Science (BITS) Pilani, and B. Tech. degree from the Institute of Engineering and Technology (I.E.T.), Lucknow, India. Dr. Yadav has extensive research and academic experience. He has worked in leading institutions such as Govind Ballabh Pant Engineering College (GBPEC), Pauri, Garhwal, and Birla Technical Training Institute (BTTI), Pilani. He has authored more than 70 research papers in national/international conferences, refereed journals, and book chapters. Dr. Yadav’s areas of interest are real time systems, embedded systems, fault-tolerant systems, energy aware scheduling, network survivability, computer architecture, distributed computing, and cryptography.

Author Articles
Load Balancing in Multicore Systems using Heuristics Based Approach

By Shruti Jadon Rama Shankar Yadav

DOI: https://doi.org/10.5815/ijisa.2018.12.06, Pub. Date: 8 Dec. 2018

Multicore processing is advantageous over single core processors in the present highly advanced time critical applications. The tasks in real time applications need to be completed within the prescribed deadlines. Based on this philosophy, the proposed paper discusses the concept of load balancing algorithms in such a way that the work load is equally distributed amongst all cores in the processor. The equal distribution of work load amongst all the cores will result in enhanced utilization and increase in computing speed of application with all the deadlines met. In the heuristic based load balanced algorithm (HBLB), the best task from the set of tasks is selected using the feasibility check window and is assigned to the core. The application of HBLB reduces imbalance among the cores and results in lesser migration leading to low migration overhead. By utilizing all the cores of the multicore system, the computing speed of the application increases tremendously which results in the increase in efficiency of the system. The present paper also discusses the improved version of HBLB, known as Improved_Heuristic Based Load Balancing (Improved_HBLB), which focuses on further reducing the imbalance and the number of backtracks as compared to HBLB algorithm. It was observed that Improved_HBLB gives approximately 10% better results over the HBLB algorithm.

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