# Energy-Efficient Spatial Query-Centric Geographic Routing Protocol in Wireless Sensor Networks
## 2 Related Work
### Energy Efficiency and Load Balancing  
GeoGrid evenly divides a monitoring area into several same-sized grids, and a CH is selected in each grid. CHs are responsible for forwarding data packets. In accordance with the distance between the current and target grids, GeoGrid performs data packet transmission in a grid-by-grid manner through CHs. Once a node is selected as the CH, it continues to work until it moves out of the grid or until the remaining energy reaches the minimum survival threshold. Then, a CH is re-selected. Hence, the premature death of several nodes easily occurs, leading to an energy hole [36]. Moreover, the division of network topology is simple and not efficient for spatial queries.  
A grid-based fault-tolerant clustering and routing algorithm (GFTCRA) was proposed in a previous study [37] to address the hot spot problem by addressing the failure of CHs. GFTCRA follows a distributed approach and distributed run time management is used for all nodes of any cluster in case their CHs fail. The simulation results of the study showed that GFTCRA outperforms two relevant algorithms in terms of tolerance of CH sudden failure and network lifetime. However, GFTCRA does not consider any delay/hop count for data delivery to the sink, and spatial query efficiency must be improved.  
A cost-based energy-balanced clustering and routing algorithm (CEBCRA) was developed in another work [16] to reduce energy consumption and prolong the network lifetime. First, CEBCRA selects CHs in a distributed manner on the basis of residual energy and neighbor cardinality. Second, each non-CH sensor node (also called a cluster member node (CM)) selects a CH within its communication range on the basis of the cost value of the CHs. Third, CEBCRA uses single-hop communication within each cluster and performs multihop communication among the clusters in data routing. For inter-cluster routing, a CH measures the cost of each path from itself toward the base station while selecting other CHs as a relay node for data forwarding on such paths. However, the algorithm complexity of CEBCRA is high, and additional communication overhead with surrounding nodes is required.  
Another study proposed grid-based clustering protocol (GCP) [38] to enhance the energy efficiency and prolong the lifetime of large-scale WSNs. GCP divides the sensing field into a series of logical grid cells to form a cluster. CHs are selected based on the residual energy and location information of nodes. However, the location information encoded in GCP occupies a large space. Moreover, the complex topology in each cluster is not conducive for spatial queries.  
The energy-efficient grid-based routing algorithm (EEGBR) [39] was proposed to prolong the network lifetime. In EEGBR, each grid selects its grid coordinator in consideration of the leftover energy of the nodes within the grid and separates the nodes to the sink by utilizing fuzzy logic. Therefore, energy consumption is reduced at the sensor nodes. Given that information transmitted from the source to the sink is performed by the grid coordinator, which acts as a relay node, the energy consumption in the routing process is minimized and network lifetime is improved. Although the selection of relay nodes shares the tasks and energy consumption of CHs, it increases the cost of node management and algorithm complexity.