Work place: Department of Electronics and Communication Engineering, Birla Institute of Technology, Mesra, Ranchi- 835215, India
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Research Interests: Computational Engineering, Engineering
Biography
Nisha Gupta Nisha Gupta Nisha Gupta received the Bachelors and Masters degrees in Electronics and Telecommunication and Electrical and Electronics engineering both from Birla Institute of Technology, Mesra, Ranchi, India and Ph.D. degree from the Indian Institute of Technology, Kharagpur, India. She was a post-doctoral fellow at University of Manitoba, Canada from 1997-1998 before joining the department of Electronics and Communication Engineering, Birla Institute of Technology in 1999 as a Reader. Currently, she is a Professor in the same department. She has authored and co-authored more than 100 technical journal articles and conference papers. Her research interests are Computational Electromagnetics, Antennas for Wireless Communication, AI techniques in Wireless, Mobile Communication and EMI/EMC and Wireless sensor networks.
By Atul Kumar Pandey Nisha Gupta
DOI: https://doi.org/10.5815/ijwmt.2019.05.04, Pub. Date: 8 Sep. 2019
Recent advancement in microelectronics and sensor devices have led to the development of a new family of networks called Internet of things (IoT). One of the challenges of IoT is the integration of autonomous and smart devices with multiple constraints specific to the wireless sensor network (WSN) environment. Among these constraints, the most important constraint is the energy efficiency of medium access control (MAC) protocol. To solve this problem, we propose an improved protocol called clustering based load adaptive MAC (CLA-MAC) for WSNs in IoT scenario, which involves mainly traffic load balancing within each cluster to provide a tuneable trade-off between energy consumption, delay, and throughput. The proposed solution makes the MAC protocol more energy efficient by reducing competition between sensor nodes with the adoption of clustering scheme and traffic distribution, which can significantly reduce the probability of collision and idle listening. Simulation results indicate that the proposed approach performs better compared with load adaptive MAC (LA-MAC) protocol in typical IoT scenario.
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