Work place: Information and Communication Engineering from Islamic University, Khustia, Bangladesh
E-mail: dmahbub_07@yahoo.com
Website:
Research Interests: Applied computer science, Computational Science and Engineering, Computer systems and computational processes, Theoretical Computer Science
Biography
Preofessor Dr. M. Mahbubur Rahman received the Bachelor’s and Master‘s Degree in Physics, Rajshahi University, in 1983, 1994 and PhD degree in Computer Science & Engineering in 1997. He is currently Professor in the department of ICE, Islamic University, Kushtia-7003, Bangladesh. He has twenty four published papers in international and national journals. His areas of interest include internetworking, AI & mobile communication.
By Md. Imran Hossain M. Mahbubur Rahman Tapan Kumar Godder Titasa Khatun
DOI: https://doi.org/10.5815/ijitcs.2013.09.07, Pub. Date: 8 Aug. 2013
Wireless sensor networks have recently emerged as important computing platform. These sensors are power-limited and have limited computing resources. Therefore the sensor energy has to be managed wisely in order to maximize the lifetime of the network. Simply speaking, LEACH requires the knowledge of energy for every node in the network topology used. In LEACHs threshold which selects the cluster head is fixed so this protocol does not consider network topology environments. We proposed IELP algorithm, which selects cluster heads using different thresholds. New cluster head selection probability consists of the initial energy and the number of neighbor nodes. On rotation basis, a head-set member receives data from the neighboring nodes and transmits the aggregated results to the distant base station. For a given number of data collecting sensor nodes, the number of control and management nodes can be systematically adjusted to reduce the energy consumption, which increases the network life.
The simulation results show that the performance of IELP has an improvement of 39% over LEACH and 20% over SEP in the area of 100m*100m for m=0.1, α =2 where advanced nodes (m) and the additional energy factor between advanced and normal nodes (α).
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