## 2 Related Works
The main disadvantages of direct communication are high power consumption and short network lifetime [24]. To overcome this issue, the multi-hop routing approach was developed to extend the network lifetime. However, it also addresses the problem of temporal synchronization due to the lack of centralized coordination. As a result, the collisions and interference may occur if numerous sensor nodes attempt to send their sensed data to the sink at the same time [25]. Additionally, during the setup phase, each node makes an effort to create a route in a proactive or on-demand way by exchanging a large number of control packets, resulting in high energy and memory consumption [17]. One of the most popular routing mechanisms utilized in WSNs was Low energy Adaptive Clustering Hierarchy (LEACH) [24], in which the clustering mechanism was introduced to improve the energy efficiency and scalability of networks. The LEACH protocol fails to distribute the cluster head (CH) uniformly as a result of the CHs' random rotation, which leads in link failure and isolated node issues. To overcome this issue, the waiting time based CH selection was introduced in [26] which ensures load balance and even energy consumption, thereby extending the network lifetime. Mobility Based Clustering (MBC) was presented in [27] to select CHs based on residual energy and speed as similar to that of LEACH. In MBC, inter-cluster communication is carried out using the CSMA/CA through the defined tree topology; thus it encounters a large delay. Efficient Distributed Clustering and Gradient based Routing Protocol (EDCGRP) was proposed in [28] to collect the data from sensor nodes periodically. Also, the CHs were selected based on the node degree, residual energy and received signal strength. Energy aware clustering and efficient CH selection was proposed in [29], in which the CHs were selected based on the distance to BS, distance to local neighbours, and remaining energy. The residual energy prediction with fuzzy logic based clustering method was proposed in [30] to uniformly distribute the work load of the sensor node and improve the network lifetime. The optimal selection of the CHs in the grid was proposed in [31], in which the sensing area is divided into cluster grids and the CHs selection is based on their distance from the BS and remaining energy. The moving speed, residual energy, and pass time were proposed as the input parameters for an improved LEACH protocol that uses fuzzy logic to increase the packet delivery ratio [32]. Several data aggregation strategies have been proposed for cluster-based WSNs to eliminate redundant packets. The choice of data aggregation techniques is determined by the energy requirements of the application. In WSN, the cluster based data aggregation eliminates redundancy in the sensed data, in which the cluster head collects the data from cluster members and sends the aggregated data to the base station [33]. As a result, it avoids sending of the entire sensed data and conserves significant amount of battery energy [34]. However, the majority of the currently used protocols do not take into account the sensor's position information, making it difficult for them to function well in real-time strategies because the sensed data is useless without a valid location (e.g., rescue applications). Data communication mode is related to the three different types of WSN applications, such as event-driven, periodic, and on-demand reporting. In the event-driven mode, the sensor node sends data to the base station whenever a specified event (for example, a gas leak) takes place in the sensing region. In a periodic drive, the sensor nodes send data to the BS on a regular basis at specified intervals (for example, environmental monitoring). In the demand-driven mode, the BS transmits commands to the specified sensor nodes, indicating that they ready receive data (for example, stock verification at storage room) [26].