# An Efficient Grid-Based Geocasting Scheme for Wireless Sensor Networks
## 2 Related Work  
A WSN usually consists of a large number of sensor nodes and a sink. In general, a sink has infinite power, whereas sensors are usually equipped with low-capacity batteries. Because sensors have limited power resources, researchers aim to build a power-saving algorithm and employ an energy efficient mechanism to extend network lifetime [10]. Recently, a lot of research has focused on the power-limited issue in WSN by using a grid-based structure. [PERSON] and [PERSON] [11] proposed an energy-aware grid-based routing scheme with mobile observers (EAGER) for WSN. In the scheme, a virtual grid structure is constructed and keeps the grid head to disseminate data. Other sensor nodes in a cell apply a time-scheduling method to sleep at specific periods for the purpose of energy saving. Regarding the routing maintenance process, EAGER presents a re-routing approach to reduce the overheads to decrease the energy utilization of routing construction. [PERSON] et al. [12] proposed a virtual grid-based dynamic routes adjustment scheme (VGDRA). VGDRA aims to reduce the energy cost by minimizing the routing reconstruction. The communication rules applied to the data delivery route re-adjustment toward the mobile sink only requiring a limited number of sensor nodes. [PERSON] et al. [13] proposed a grid-based reliable routing protocol (GBRR), which creates a virtual cluster based on a square grid. This is achieved by the intra-cluster and inter-cluster communication quality. The scheme calculates the best paths along the cluster to avoid the overload of head nodes. [PERSON] et al. [14] proposed a grid-based multicast routing approach for WSNs. This approach achieves better overall performance through the concept of game balance in game theory. The scheme deals fairly with all factors, namely space, energy, and data factors to solve the multicast problem of the Nash Equilibrium. There is also a significant amount of literature that conducts the geocasting problem in WSNs, and the application often needs to collect or monitor the information in several location-based regions [15]. [PERSON] et al. [16] designed a geographical and energy-aware routing protocol (GEAR) to disseminate the packet from regions. GEAR utilizes a recursive geographical forwarding strategy by using energy-aware and geographically-informed neighbor selection. [PERSON] et al. [17] proposed an efficient geocasting protocol for WSNs with multiple target regions, called FERMA. FERMA utilizes the characteristics of Fermat point [18; 19] to construct the shortest path for data transmission and minimize energy consumption. This scheme constructs a shared path among multiple target regions via Fermat points to decrease the cost of packet forwarding. [PERSON] et al. [20] developed a mobile geocasting protocol (M-Geocasting) to deal with the data delivery issue between the regions and the mobile sink. The mobile sink has geographically collective mobility, and M-Geocasting provides the location information of a sink group to all sensor nodes in the target regions. [PERSON] et al. [21] proposed energy-efficient Q-learning-based geocasting (FERMA-QL) for WSNs, where the nodes closest to the Fermat points become relay nodes, and then Q-learning is used to construct a shared path for further data transmission. [PERSON] and [PERSON] [22] proposed a geometrical link-aware geocasting scheme with energy balancing (GeoLE) for WSNs. GeoLE selects different groups of relay sensors to balance the energy consumption of the sensors according to the predictive relay selection (PRS) metric. The PRS metric contains the transmission count, forwarding progress, delay, and remaining energy. [PERSON] (2018) explored the impact of mobility on the energy consumption and transmission delay for Wireless Adhoc and Sensor Networks (WASNs). The proposed protocol uses the Fermat point-based routing with mobility assisted to reduce energy consumption and transmission delay in WASNs. In this paper, we propose an efficient grid-based geocasting scheme (GB-FERMA) for WSNs.