## 3 Literature Review  
The authors proposed a new energy efficient and delay sensitive scheme for U-WSNs in [15]. The scheme enhances the performance of [16] by using the fuzzy logic technique (FLT), where the best forwarder nodes are selected by considering the node position and energy information. This technique reduces the interference between the nodes. The consideration of residual energy ratio (RER) and fuzzy logic interference technique in the scheme minimizes the expended energy. The node which has the lowest distance position and highest energy is selected as a destination, which transmits the packets to the desired sink through multi-hop paths. The scheme causes a small delay and reduces the energy consumption. However, it reduces the network reliability with high probability of information packet drop. [PERSON] et al. [17] access the IoT wireless network in random manner by facilitating two data collectors. Nodes and aggregators are used in order to transmit data packets in random access fashion. The aggregators use network-level cooperation to transmit data packets in slotted time. Moreover, they provide throughput to gain the scalability of network. By doing so, they obtain possibly finite queuing delay. They also attempt to facilitate data collection for IoT. The use of aggregators makes the system complicated. In [18], the entire network is split into three equal sub-regions. Division of network is an efficient step towards energy saving and ratio-of-delivered packet (RODP) enhancement. The approach considers the horizontal and vertical movement of the sink which helps to minimize the packet drop. Cooperation technique is applied to the network with the help of which nodes use cooperation to forward the data. This helps to achieve maximum RODP. The RLN amplifies and decodes the information and sends toward the DSN. During the routing at each destination node, the BER is checked. In case of BER lower than the threshold value, it proceeds the packet successfully in the direction of the desired destination. The nodes selection is set up based on the cost function. The selection of destination node is made on the maximum residual energy, lowest depth, and maximum signal-to-noise-ratio (SNR) values. The protocol achieves high RODP and increases battery life. To minimize the energy use and avoid the void zone occurrence, two new techniques are presented in [19]. In the first technique the mobile sink nodes play the key role to reduce consumption of the nodes' energy. The second technique combines routing with cooperation with the first one. The cooperative scheme enhances the network reliability by traveling the packets over multi-paths. In second scheme, the RODP increases, packet drop decreases, and the transmission delay maximizes with cost of maximum energy consumption. The first scheme reduces the energy consumption and keeps the nodes alive for long time. The authors presented a cooperative technique for energy harvesting in [20]. They presented an overview about the energy limitation for the stable throughput between the SRN, RLN, and the DSN. The SRN and RLN have an unlimited energy harvesting and saving capability. They consider the interior and exterior stability range for the given transmission region. Also relay assisted network is provided. The proposed system has identical performance in the case of intermediate traffic regime. The tracking interacting queue is a difficult task; however, this work obtains it by using insight from a simple model. Moreover, the stable throughput region is considered to achieve connectivity of nodes. The authors proposed a cooperative scheme in [21] for reliability and saving the nodes' energy. The cooperation is held among the DSN and the RLN. The selection of RLN and DSN bases on the highest residual energy, lowest depth and channel quality. The scheme uses the sink node mobility for balanced energy consumption. The mobile sink nodes secure the information sent by the sensor nodes and forward towards the final destination.