Md. Mosaddek Khan

Work place: University of Dhaka, Dhaka, Bangladesh

E-mail: mosaddek@cse.univdhaka.edu

Website:

Research Interests: Robotics, Computer Networks, Data Mining, Data Structures and Algorithms

Biography

Md. Mosaddek Khan received the B.Sc. (Hons.) in CSE and M.S. in CSE degrees from University of Dhaka, Bangladesh in 2010 and 2012, respectively. He is currently working as a Lecturer at Department of Computer Science and Engineering, University of Dhaka, Bangladesh. His research interests include Mobile Adhoc Networks, Wireless Sensor Networks, Cloud Computing, Wireless Body Area Networks, Robotics, and Data Mining.

Author Articles
Improved Adaptive Routing for Multihop IEEE 802.15.6 Wireless Body Area Networks

By Shariar Imtiaz Md. Mosaddek Khan Md. Mamun-or-Rashid Md. Mustafizur Rahman

DOI: https://doi.org/10.5815/ijisa.2013.12.05, Pub. Date: 8 Nov. 2013

Wireless Body Area Network has the ability to collect and send data on body measurement to the server through PDA or other device. Nodes (sensors) collect vital signs from the body or environmental factor and check them. In IEEE 802.15.6 routing is discussed as a part of the link layer where multihop is not fully considered. Improving network performance, reducing energy consumption, thus extending the network lifetime is the main challenge in BANs. Several studies mention that multihop for BANs helps for achieving network performance, reducing energy consumption and extending network lifetime. One work presents the Adaptive multihop tree-based Routing (AMR) protocol that is extensively evaluated in a real testbed deployment. They use fuzzy logic to combine all metrics they use. Another limitation is that they have used Prim's algorithm which is not a realistic approach. So in this work we have improved their multihop tree-based Routing (AMR) protocol using Kruskal's algorithm instead of Prim's algorithm. The time complexity of Kruskal's algorithm is way less than prims's algorithm. We have used network simulator 3 (NS3) to simulate and found that our algorithm is better than AMR if many of nodes.

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