Open AccessClustered chain founded on ant colony optimization energy efficient routing scheme for under-water wireless sensor networks
Author(s) -
Djilali Moussaoui,
Mourad Hadjila,
Sidi Mohammed Hadj Irid,
Sihem Souiki
Publication year - 2021
Publication title -
international journal of power electronics and drive systems/international journal of electrical and computer engineering
Language(s) - English
Resource type - Journals
eISSN - 2722-2578
pISSN - 2722-256X
DOI - 10.11591/ijece.v11i6.pp5197-5205
Subject(s) - computer science , ant colony optimization algorithms , wireless sensor network , routing protocol , computer network , efficient energy use , fuzzy logic , energy consumption , distributed computing , routing (electronic design automation) , load balancing (electrical power) , energy (signal processing) , real time computing , algorithm , artificial intelligence , engineering , geometry , mathematics , grid , electrical engineering , statistics
One challenge in under-water wireless sensor networks (UWSN) is to find ways to improve the life duration of networks, since it is difficult to replace or recharge batteries in sensors by the solar energy. Thus, designing an energy-efficient protocol remains as a critical task. Many cluster-based routing protocols have been suggested with the goal of reducing overall energy consumption through data aggregation and balancing energy through cluster-head rotation. However, the majority of current protocols are concerned with load balancing within each cluster. In this paper we propose a clustered chain-based energy efficient routing algorithm called CCRA that can combine fuzzy c-means (FCM) and ant colony optimization (ACO) create and manage the data transmission in the network. Our analysis and results of simulations show a better energy management in the network.