Abstract
Wireless (smart) sensor networks (WSNs), networks made up of embedded wireless smart sensors, are an important paradigm with a wide range of applications, including the internet of things (IoT), smart grids, smart production systems, smart buildings and many others. WSNs achieve better execution efficiency if their energy consumption can be better controlled, because their component sensors are either difficult or impossible to recharge, and have a finite battery life. In addition, transmission cost must be minimized, and signal transmission quantity must be maximized to improve WSN performance. Thus, a multi-objective involving energy consumption, cost and signal transmission quantity in WSNs needs to be studied. Energy consumption, cost and signal transmission quantity usually have uncertain characteristics, and can often be represented by fuzzy numbers. Therefore, this work suggests a fuzzy simplified swarm optimization algorithm (fSSO) to resolve the multi-objective optimization problem consisting of energy consumption, cost and signal transmission quantity of the transmission process in WSNs under uncertainty. Finally, an experiment of ten benchmarks from smaller to larger scale WSNs is conducted to demonstrate the effectiveness and efficiency of the proposed fSSO algorithm.
Highlights
Wireless sensor networks (WSN) consist of smart sensors deployed and operated in wireless sensor networks, and have rapidly become an important design widely applied in many modern applications, such as the Internet of Things (IoT) [1,2], smart grids [3], healthcare and medical systems [4], wind energy systems [5], industrial automation [6], the smart transportation industry [7,8], the semiconductor industry [9] and smart cities [10]
Optimization of process with respect consumption, cost and signal transmission quantity in a was studied in this paper
0.01400000 this may result in uncertainty consumption, cost and signal transmission quantity of the this may result in uncertainty of energy consumption, cost and signal transmission quantity of the
Summary
Wireless (smart) sensor networks (WSN) consist of smart sensors deployed and operated in wireless sensor networks, and have rapidly become an important design widely applied in many modern applications, such as the Internet of Things (IoT) [1,2], smart grids [3], healthcare and medical systems [4], wind energy systems [5], industrial automation [6], the smart transportation industry [7,8], the semiconductor industry [9] and smart cities [10]. Have considered parameter optimization in WSN and the details can be found in [28,29,30] In this this study, study, aa fuzzy-based fuzzy-based algorithm algorithm is is adopted adopted to to solve solve the the uncertain uncertain characteristics characteristics of of energy energy. To the best of the authors’ knowledge, this is the first work to use a fuzzy-based algorithm to effectively resolve uncertain problems of energy consumption measurement in a WSN system. In. REVIEW knowledge, this is the first work to use a fuzzy-based algorithm to effectively resolve uncertain problems of energy consumption measurement in a WSN system.
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