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) are considered producers of large amounts of rich data. Four types of data-driven models that correspond with various applications are identified as WSNs: query-driven, event-driven, time-driven, and hybrid-driven. The aim of the classification of data-driven models is to get real-time applications of specific data. Many challenges occur during data collection. Therefore, the main objective of these data-driven models is to save the WSN’s energy for processing and functioning during the data collection of any application. In this survey article, the recent advancement of data-driven models and application types for WSNs is presented in detail. Each type of WSN is elaborated with the help of its routing protocols, related applications, and issues. Furthermore, each data model is described in detail according to current studies. The open issues of each data model are highlighted with their challenges in order to encourage and give directions for further recommendation.

Wireless Sensor Networks (WSNs) play a significant role in providing an extraordinary infrastructure for monitoring environmental variations such as climate change, volcanoes, and other natural disasters. In a hostile environment, sensors’ energy is one of the crucial concerns in collecting and analyzing accurate data. However, various environmental conditions, short-distance adjacent devices, and extreme usage of resources, i.e., battery power in WSNs, lead to a high possibility of redundant data. Accordingly, the reduction in redundant data is required for both resources and accurate information. In this context, this paper presents a comprehensive review of the existing energy-efficient data redundancy reduction schemes with their benefits and limitations for WSNs. The entire concept of data redundancy reduction is classified into three levels, which are node, cluster head, and sink. Additionally, this paper highlights existing key issues and challenges and suggested future work in reducing data redundancy for future research.

With the fast development of wireless communication and semiconductor devices, home networking has gained considerable attention in the past few years. In Wireless Sensor Networks (WSNs), Sensing coverage is known as one of the most important standards in evaluating the performance of WSNs. The sensor nodes may have failures due to energy depletion during their service life which leads to incomplete coverage of the sensing area and coverage holes in the network which results in reducing the network performance. Therefore, designing an energy-efficient solution to prevent the coverage holes is vital. Employing Mobile Sink (MS) is a popular technique to enhance the energy efficiency of the network. Furthermore, sojourn location optimization is one of the main design issues of mobility based schemes. However, to the best of our knowledge, most of existing sojourn location optimization-based schemes are specially designed for homogeneous networks and much less attention has been devoted to optimizing this parameter in heterogeneous networks. Therefore, the aim behind this paper is to optimize the sojourn location of MS in a heterogeneous home network, which results in improving the coverage time and the performance of the network. Based on the experimental results, the scheme proposed in this paper remarkably improves the balanced energy consumption, which leads to enhanced network lifetime and performance.

The study aims to explore the access of mobile phone, emerging technologies, and use of the mobile phone by the youth of Gilgit-Baltistan (GB), Pakistan, for learning and safety and security purposes. Structured questionnaires were used to collect the data. The descriptive statistics was employed to test the research model. Among the 300 distributed sample size, 272 participants responded back including 133 male and 139 female students of Karakoram International University (KIU) from eight districts of GB as research participants for data collection. Only 1 male and 6 females responded that they do not have their own mobile phone, comprising of 90.6 response rate. The results show that 97 of students of rural mountainous areas own a mobile phone. The study contributes valuable findings about the access and positive use of mobile phones for learning and safety and security purposes. The result also shows that the youth of GB have enough skills of mobile phone technologies to cope with the future challenges of China Pakistan Economic Corridor (CPEC) by taking advantages of China Pakistan Information Corridor (CPIC is a fiber optics cable laid down from the China border to Islamabad Pakistan for the purpose of providing the fast internet facility including 5G). This is the baseline survey and future study will be based on this survey.