# Comparing New Wireless Sensor Network Protocols through Simulation and Data Analysis +
## 1 Introduction  
There are many benefits to wireless communication over traditional wired networks, including the ability to create compact, affordable, low-power, and multi-functional sensing devices. These tiny sensors are characterized as sensors because they are capable of sensing, computing, self-organization, and communication. A sensor is a small device that senses the ambient conditions in its environment, collects data, and processes it to provide useful information that may be used to identify occurrences in the surrounding area. Using mesh networking protocols, these sensors can be joined together to create a network that communicates wirelessly across radio frequency channels. Wireless sensor network (WSN) is the term used to describe the grouping of these homogeneous or heterogeneous sensor nodes [1]. Sensor nodes can be placed in large numbers in an area that has to be explored due to their low cost, small size, and ease of deployment [2]. Weerdly, unlike other networks that get weaker and perform worse as their size increases, WSNs get stronger and perform better as the number of nodes increase. Additionally, the number of nodes in a network can be increased without any complicated settings. As a result, it is claimedthat connectivity employing mesh networking will use node-to-node hoping to occupy any available communication link in pursuit of the destination. Due to all these important benefits, WSNs have a wide range of applications, including real-time tracking, weather forecasting, health care applications, military operations, transportation, and security.  
WSN is a network made up of hundreds or thousands of tiny sensor nodes that can sense, compute, and communicate with one another and the base station. The four components that make up a sensor node's functional architecture are the sensor, CPU, radio, and power. Three of these four units are in charge of completing a task, while the power unit provides energy for the entire operation. The sensing unit's job is to measure environmental variables like temperature, humidity, and pressure [3; 4]. The processing unit's main duty is to process data (signals), and the communication unit's job is to transmit data from the sensor unit to the user via the base station (BS) [5]. These tiny sensor nodes are dispersed around the study area to gather environmental data, process it, and send it to the base station [6].  
One can assume that WSNs operate similarly to conventional wired or wireless networks by looking at their application domain. But in practice, things are very different since conventional wired or wireless networks have sufficient resources, including boundless power, memory, fixed network topologies, adequate communication ranges, and computing capabilities [7; 8]. On the other hand, WSNs are resource-constrained in terms of their ability to use energy, compute, and store data [9; 10]. Unfortunately, we have the same expectations for the WSNs as we have for regular computer networks despite the limited resources available.  
Because WSNs have limited resources, several difficulties in their design and operation affect how well they work. Communication management, unattended operations, network longevity, and fault tolerance rank highly among these difficulties [11]. Therefore, these problems are subject to research in order to enhance WSN performance. On the other hand, effective resource utilization can considerably improve WSN performance. By concentrating on the elements involved in WSN operations, resource consumption can be improved. The resources of WSNs are undoubtedly influenced by communication. Node-to-node, node-to-BS, and BS-to-node communication are all part of the WSN communication pattern. For this communication, the best route is used.