Energy constraint is one of the main design issues of wireless sensor networks. Over the past few years, the concept of the wireless mobile charger (WMC) has been proposed in order to improve the energy efficiency of the networks. In such schemes, optimizing the moving trajectory and charging time of WMC are considered as two main problems. Several schemes attempt to optimize the moving trajectory of WMC without considering the balanced energy depletion time of nodes, which leads to degrading the energy efficiency and network lifetime. Thus, a route optimization of WMC algorithm is proposed to determine the optimal trajectory of WMC to move along sensor nodes in such a way that the balanced energy depletion time of the nodes is achieved. Moreover, in most of the existing schemes, WMCs charge the nodes as long as their batteries are fully charged. However, not considering the remaining lifetime of the other nodes leads to premature network death and decreases the network performance. Therefore, a charge time optimization of WMC algorithm is proposed to overcome the mentioned problem. Simulation results demonstrate that the proposed scheme remarkably enhance the network performance in terms of different evaluation metrics.

Wireless Sensor Networks (WSNs) have grown excessively due to their various applications and low installation cost. One of the design challenges of WSNs is to balance the energy consumption among sensor nodes, which results in enhanced network lifetime. In the past few years, several Mobile Sink (MS) based schemes exclusively focus on determining the optimal sojourn time of MS to balance the energy consumption among Cluster Heads (CH). However, most of them are evaluated under unpredictable mobility pattern. Although they significantly improve the network lifetime, however, unpredictable mobility pattern imposes extra overheads on the network. Therefore, Collaborative Mobile Sink Sojourn Time Optimization (CMS2TO) scheme is proposed in this paper. The CMS2TO aims to optimize the sojourn time of MS in each cluster in order to achieve balanced lifetime of CHs belonging to different layers of the network. The main contribution of CMS2TO is to utilize a collaborative mechanism in order to determine the optimal sojourn time of MS in each cluster. In fact, in the proposed scheme, the CHs belonging to other layers cooperate in calculating the sojourn time of MS at the residence cluster. Based on experimental results, proposed CMS2TO enhances the network performance in terms of different performance evaluation metrics.

Clustering has been accepted as one of the most efficient techniques for conserving the energy of wireless sensor networks (WSNs). In cluster-based WSN, the cluster heads (CH) consume more energy compared with normal nodes, which results in rising their energy consumption and reducing the network lifetime. There are several energy-efficient routing schemes which have been presented to reduce the energy consumption of CHs. In such schemes, further clustering of CHs will result in reducing the energy consumption of CHs. However, this rule has not been considered in previous related works. Likewise, unbalanced energy consumption of CHs is one the main design challenges which leads to increase the wasted energy and premature network death. A number of recent studies have sought to improve the balanced energy via utilizing devices equipped with large and expensive energy harvesters, which leads to extra cost Therefore, a feasible solution is needed to achieve balanced energy consumption of CHs. Consequently, to overcome the aforementioned limitations, we proposed a framework for energy-efficient clustering by utilizing a wireless energy balancer. Firstly, an n-level clustering is presented which results in fully leveraging and reducing the energy consumption of CHs. Secondly, an energy balancer is utilized in order to reduce the wasted energy to the fullest possible extent by zeroing the variance between the remaining energy of CHs. The performance of the proposed scheme has been compared against CMS2TO and DGOB mechanisms. Simulation results show that the proposed scheme achieved improved performance in terms of network lifetime by 20%, total energy consumption by 52%, network overhead by 20%, computation time by 46%, and wasted energy by 86% compared to existing schemes. In conclusion, the proposed framework proves to be a viable solution for enhancing the network lifetime and energy efficiency.

In Surveillance Wireless Sensor Networks (SWSN), the nodes are distributed at the borders to detect unauthorized intrusions. In such applications, as the nodes are usually equipped with limited batteries and the network area is harsh to be accessible for humans, energy efficiency is considered as one of the main issues in designing the sensor networks. In the last years, Wireless Rechargeable Sensor Networks (WRSN) provides valuable insights into solving the energy constraint problem in WSNs. In a WRSN, Wireless Mobile Chargers (WMC) are responsible to recharge the batteries of the sensor nodes in order to enhance the operation time of the network. In most of the previous WRSN based schemes, the WMCs recharge the nodes singly and directly, which results in increasing the travel time of WMC and waiting time of sensor nodes. In addition, despite of using WMC, the permanent network lifetime has not been addressed in most of the previous schemes. Therefore, to overcome the limitations of existing literature, this research work focuses on the design and development of Broker-based Nodes Recharging Scheme (BNRS) which significantly contributes to improved lifetime and performance of SWSN. In the proposed scheme, power banks are employed as brokers between sensor nodes and WMC. The main duty of a power bank is to receive energy from WMC and transfer to the sensor nodes. Based on the simulation experiments the proposed BNRS achieves the permanent network operation which results in increasing security in the border of countries.

Because of its extraordinary characteristics, this material has attracted researchers in various arenas. Among the numerous fields where this material can be applied is the gas sensor technology. The graphene experiences remarkable changes in its electrical and physical characteristics when exposed to different gases; and they are, therefore, the ideal candidates for gas sensing application. However, a deep understanding of the effects of gas molecules on the graphene energy band structure and its electronic properties, need to be further studied. In this paper, a new quantum capacitance model for the gas sensor employing the graphene field effect transistor platform is proposed. Hence, a general approach using the Tight-binding approximation based on the nearest neighbor incorporating Schrödinger equation is developed. Therefore, the adsorption effects of the CO, NO, and NH ₃ gases on the energy band structure, quantum capacitance, and I-V characteristics of the graphene FET are analytically modeled and investigated. The results indicated that, the gas adsorption can cause significant changes on the graphene band structure and quantum capacitance. The I-V characteristics evaluation indicated current decrement after gas adsorption because of the conductance decrement induced by the band gap increment. The proposed models for the capacitance were also compared with the published experimental data and a satisfactory agreement was achieved.