Efficient energy consumption is a critical factor for the deployment and operation of wireless sensor networks (WSNs). In general,\r\nWSNs performclustering and routing using localized neighbor information only. Therefore, some studies have used self-organized\r\nsystems and smart mechanisms as research methods. In this paper, we propose a self-organized and smart-adaptive clustering\r\n(SOSAC) and routing method, which performs clustering in WSNs, operates the formed clusters in a smart-adaptive way, and\r\nperforms cluster-based routing. SOSAC is comprised of three mechanisms, which are used to change the fitness value over time, to\r\nback up routing information in preparation for any potential breakdown in WSNs, and to adapt to the changes of the number of\r\nsensor nodes for aWSN.We compared the performance of the proposed SOSAC with that of a well-known clustering and routing\r\nprotocol for WSNs. Our computational experiments demonstrate that the network lifetime, energy consumption, and scalability\r\nof SOSAC are better than those of the compared method.
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