{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/a-novel-energy-aware-node-clustering","title":"A Novel Energy Aware Node Clustering Algorithm for Wireless Sensor Networks Using a Modified Artificial Fish Swarm Algorithm","arxiv_id":"1506.00099","date":"2015-05-30","proceeding":null,"authors":["Reza Azizi","Hasan Sedghi","Hamid Shoja","Alireza Sepas-Moghaddam"],"abstract":"Clustering problems are considered amongst the prominent challenges in\nstatistics and computational science. Clustering of nodes in wireless sensor\nnetworks which is used to prolong the life-time of networks is one of the\ndifficult tasks of clustering procedure. In order to perform nodes clustering,\na number of nodes are determined as cluster heads and other ones are joined to\none of these heads, based on different criteria e.g. Euclidean distance. So\nfar, different approaches have been proposed for this process, where swarm and\nevolutionary algorithms contribute in this regard. In this study, a novel\nalgorithm is proposed based on Artificial Fish Swarm Algorithm (AFSA) for\nclustering procedure. In the proposed method, the performance of the standard\nAFSA is improved by increasing balance between local and global searches.\nFurthermore, a new mechanism has been added to the base algorithm for improving\nconvergence speed in clustering problems. Performance of the proposed technique\nis compared to a number of state-of-the-art techniques in this field and the\noutcomes indicate the supremacy of the proposed technique.","url_abs":"http://arxiv.org/abs/1506.00099v1","url_pdf":"http://arxiv.org/pdf/1506.00099v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"a-novel-energy-aware-node-clustering","repo_url":"https://github.com/nafiuny/AFSA-algorithm","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[{"task_slug":"clustering","task_name":"Clustering"},{"task_slug":"evolutionary-algorithms","task_name":"Evolutionary Algorithms"},{"task_slug":"node-clustering","task_name":"Node Clustering"}],"methods":[{"method_slug":"speed","method_name":"SPEED"}],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}