## 2 Related Work
When the application of the sensor network is specified, QoS helps support and overcome the challenges mentioned above. Firstly, the applications that run on WSNs are not end-to-end applications like they used to be. Secondly, the bandwidth is not the main concern for a single-sensor node [14]. However, the bandwidth may be an essential concern for a group of sensors for specific periods due to the burst nature of sensor traffic. Thirdly, packet losses in traffic generated by one sensor node can be tolerated to a certain extent, since there is always redundancy in the data. Finally, most applications in WSNs are mission-critical, reflecting the importance of applications. Consequently, they are confident that the QoS support in WSNs cannot be gauged using end-to-end network QoS metrics alone. Thus, there is a knowledge gap for non-end-to-end QoS parameters that must be proposed. QoS parameters are collectively called \"collective QoS parameters\", referring to these non-end-to-end characteristics. These are collective latency, collective packet loss, collective bandwidth, and information throughput [14]. The hybrid cluster approach for homogeneous and heterogeneous networks to increase the QoS parameters of wireless sensor networks based on MATLAB simulation results is devised in [15]. Based on throughput and network lifetime parameters, the proposed WSN QoS-based energy-efficient protocol outperforms ATEER (average threshold energy-efficient routing), DEEC (developed distributive energy-efficient clustering), and EDDEEC (enhanced developed distributive energy-efficient clustering) by 10%, 26%, and 63%, respectively. The study concludes that the protocol based on throughput and network lifetime parameters is well suited and well positioned for designing WSNs in real-world and real-time scenarios. In the node status and score-based route optimisation protocol (NSSROP), each node stores some additional data to balance the routing burden among all nodes [16]. A sensor node may have the shortest route to a base station in an IoT configuration. The WSN's block-listing method is established to cope with non-cooperative nodes and the NSSROP has achieved exceptional results in terms of average energy usage, throughput, and end-to-end delay [16]. Unlike other standard routing protocols, the proposed technique considers various QoS criteria related to routing and energy optimisation in WSNs. To determine the node densities, each node is evaluated based on its energy consumption and closed neighbours (CNs). A hybrid method for obtaining the probability distribution of report latency in random access (RA) WSN protocols [17] is studied and it is beneficial for assessing the QoS of WSNsin time-critical applications. In this manner, event reporting is time-constrained and fault-sensitive. In specific applications such as target tracking and positioning, transmitting a certain number of event packets is required to characterise the occurring phenomena accurately. Our methodology considers a basic structure, and the distribution of the number of detecting nodes is obtained by simulation, allowing the analysis of the desired QoS parameters. Most WSN technologies are designed to monitor and manage various processes effectively. A \"smart environment\" is equipped with sensors, microcontrollers, and adaptive software programs for self-protection and self-monitoring. For designing a WSN, several factors need to be considered. Such factors include scalability, fault tolerance, high sensing accuracy, inexpensive deployment costs, rapid scaling up, and application needs. The sensor networks will become an integral part of our lives in the future because of their wide range of applications. However, before sensor networks can be implemented, constraints such as cost, hardware, topology alteration, environment, and power consumption must be addressed. In addition, sensitive networks demand particular wireless ad hoc networking protocols because of the tight restrictions.