# Enhancement of RWSN Lifetime via Firework Clustering Algorithm Validated by ANN
###### Abstract  
Nowadays, wireless power transfer is ubiquitously used in wireless rechargeable sensor networks (WSNs). Currently, the energy limitation is a grave concern issue for WSNs. However, lifetime enhancement of sensor networks is a challenging task need to be resolved. For addressing this issue, a wireless charging vehicle is an emerging technology to expand the overall network efficiency. The present study focuses on the enhancement of overall network lifetime of the rechargeable wireless sensor network. To resolve the issues mentioned above, we propose swarm intelligence based hard clustering approach using fireworks algorithm with the adaptive transfer function (FWA-ATF). In this work, the virtual clustering method has been applied in the routing process which utilizes the firework optimization algorithm. Still now, an FWA-ATF algorithm yet not applied by any researcher for RWSN. Furthermore, the validation study of the proposed method using the artificial neural network (ANN) backpropagation algorithm incorporated in the present study. Different algorithms are applied to evaluate the performance of proposed technique that gives the best results in this mechanism. Numerical results indicate that our method outperforms existing methods and yield performance up to 80% regarding energy consumption and vacation time of wireless charging vehicle. W  WSN; FWA-ATF; swarm intelligence; vacation time; energy minimization +
Footnote †: journal: Information Information  
large scale in many applications, monitoring of environments, for instance [4]. At present, existing sensor networks are mostly operated by batteries. This reduces the age of these sensor nodes. To avoid the high cost of replacing batteries, some research experts have adopted energy-efficient routing protocols to minimize the energy consumption of the sensor nodes. The key concern related to the Internet of Things (IoT)'s applications aims to prolong the battery life of machine-to-machine devices. Thereby, it will ascertain the working of the Internet of Things (IoT)'s devices for a long period [5]. The primary objective of resource allocation of the Internet of things (IoT)'s devices will have a more sustainable energy supply. The latter exposes an even more critical issue because of the ever growing presence of machine-to-machine devices; they are deployed in the areas which reflect that even frequent human maintenance or replacing the battery will not be possible [6]. This study aims to improve the energy efficient communication as found in wireless sensor networks which aims to eradicate the congestion problem. Promising solutions of joint clustering of devices and resource management have been proposed in the recent study. Ultimately, the solution will hinder signal interference, noise ratio, transmission delay, etc. [7]. The use of clustering methods will show immediate effects and benefits at large scale. Data priority will be for devising energy efficient clustering algorithms for congestion alleviation. The energy harvesting technique is an emerging technology which offers a solution to the challenge of finite battery life in sensor nodes [8]. Presently, researchers are focusing on applying energy harvesting techniques to eradicate the energy limitations, exist in battery-operated WSNs. The energy harvesting techniques may integrate with WSNs to enhance the network age and sensor nodes to gather ambient energy. These harvesting technologies are powered by sensor nodes via renewable energy resources like solar, wind, heat, radio frequency (RF) signal, etc. [9]. Nevertheless, due to the dynamic nature of such energy sources, either replacing or charging batteries could prove inconvenient due to the hazardous atmosphere. Renewable energy sources make deployment of wireless rechargeable sensor network (WRSN) possible by enabling sensor nodes to charge their batteries without any physical connection or even to make the WRSN battery-less. This advancement and great enhancement in wireless power transfer (WPT) can transfer energy wirelessly.