# Energy and Environment-Aware Path Planning in Wireless Sensor Networks with Mobile Sink
###### Abstract  
With the advances in sensing technologies, sensor networks became the core of several different networks, including the Internet of Things (IoT) and drone networks. This led to the use of sensor networks in many critical applications including military, health care, and commercial applications. In addition, sensors might be mobile or stationary. Stationary sensors, once deployed, will not move; however, mobile nodes can move from one place to another. In most current applications, mobile sensors are used to collect data from stationary sensors. This raises many energy consumption challenges, including sensor networks' energy consumption, urgent messages transfer for real-time analysis, and path planning. Moreover, sensors in sensor networks are usually exposed to environmental parameters and left unattended. These issues, up to our knowledge, are not deeply covered in the current research. This paper develops a complete framework to solve these challenges. It introduces novel path planning techniques considering areas' priority, environmental parameters, and urgent messages. Consequently, a novel energy-efficient and reliable clustering algorithm is proposed considering the residual energy of the sensor nodes, the quality of wireless links, and the distance parameter representing the average intra-cluster distance. Moreover, it proposes a real-time, energy-efficient, reliable and environment-aware routing, taking into account the environmental data, link quality, delay, hop count, nodes' residual energy, and load balancing. Furthermore, for the benefit of the sensor networks research community, all proposed algorithms are formed in integer linear programming (ILP) for optimal solutions. All proposed techniques are evaluated and compared to six recent algorithms. The results showed that the proposed framework outperforms the recent algorithms. p 20  
Therefore, cluster heads must be energy-efficient because of transmission and reception operations. The death of these nodes in an area might cause network partitioning and data loss. Thus, proper selection of cluster heads conserves sensor node energy, prolonging network life. Several clustering approaches assign cluster heads based on the average distance to maximize cluster head lifespan in this setting. So, cluster heads are close member nodes. Certainly, if the cluster head dies, it may generate a serious energy imbalance in the network. To increase network lifetime, an energy-balanced clustering strategy is required [4; 5]. It is obvious that high-quality, reliable wireless links enabling communication among sensor nodes would be required to successfully deliver the data packet from the member nodes to their cluster heads. However, due to wireless communication's inherent nature in sensor networks, packet losses are quite inevitable. Wireless connections are prone to network disturbances due to some environmental parameters such as interference and fading. This would increase the retransmission possibility of lost packets and thus causes more energy consumption and more delivery delay. Nevertheless, most of the existing clustering techniques attempted to select cluster heads based on energy factors to improve network lifetime. Such approaches lack knowledge related to data transmission interruptions due to lossy links. This eventually affects the network throughput and lifetime. Therefore, the quality of wireless links is another factor that needs to be considered when designing the clustering technique for WSNs [6; 7; 8; 9]. Although the clustering technique contributes to extending the network lifetime, there are still existing issues such as hotspot problems and connectivity. As the most consuming energy in sensor nodes comes from communication, the sensor nodes near to the static sink are at risk of dying more quickly than other nodes because they consume more energy by transmitting accumulative data to the static sink, causing hotspot problems. As a consequence, network lifetime decreases.