The IRMA Community
Newsletters
Research IRM
Click a keyword to search titles using our InfoSci-OnDemand powered search:
|
Proficient Clustering algorithm for Wireless Sensor Networks
Abstract
Enhancing the energy efficiency and maximizing the networking lifetime are the major challenges in Wireless Sensor Networks (WSN).Swarm Intelligence based algorithms are very efficient in solving nonlinear design problems with real-world applications.In this paper a Swarm based Fruit Fly Optimization Algorithm (FFOA) with the concept of K-Medoid clustering and swapping is implemented to increase the energy efficiency and lifetime of WSN. A comparative analysis is performed in terms of cluster compactness,cluster error and convergence. MATLAB Simulation results show that K-Medoid Swapping and Bunching Fruit Fly optimization (KMSB-FFOA) outperforms FFOA and K-Medoid Fruit Fly Optimization Algorithm (KM-FFOA).
Related Content
|
Rashmi Rani Samantaray, Zahira Tabassum, Abdul Azeez.
© 2024.
32 pages.
|
|
Sanjana Prasad, Deepashree Rajendra Prasad.
© 2024.
25 pages.
|
|
Deepak Varadam, Sahana P. Shankar, Aryan Bharadwaj, Tanvi Saxena, Sarthak Agrawal, Shraddha Dayananda.
© 2024.
24 pages.
|
|
Tarun Kumar Vashishth, Vikas Sharma, Kewal Krishan Sharma, Bhupendra Kumar, Sachin Chaudhary, Rajneesh Panwar.
© 2024.
29 pages.
|
|
Mrutyunjaya S. Hiremath, Rajashekhar C. Biradar.
© 2024.
30 pages.
|
|
C. L. Chayalakshmi, Mahabaleshwar S. Kakkasageri, Rajani S. Pujar, Nayana Hegde.
© 2024.
30 pages.
|
|
Amit Kumar Tyagi.
© 2024.
29 pages.
|
|
|