# Design of a Technique for Accelerating the WSN Convergence Process
## 2 Related Works
#### Problem Areas  
Current research in WSNs deals with various problem areas that present new challenges for researchers. Their solution is essential for creating efficient and reliable sensor networks with many applications, such as environmental monitoring, smart cities, etc. Problem areas in WSNs are, for example:  
* Energy efficiency: One of the main problems in WSNs is the limited energy capacity of sensor devices. Research seeks to find ways to minimize energy consumption at the level of sensors, communication protocols, and algorithms to extend network lifetime and enable long-term deployment [44]. * Data processing: Sensors in WSNs acquire a huge amount of data that need to be processed and interpreted. Research focuses on the development of algorithms for data processing and analysis, including clustering, classification, aggregation, and anomaly detection [45]. * Security: Considering sensitive data and critical applications, research deals with the development of mechanisms to ensure authentication, encryption, data integrity, and protection against attacks [46]. * Network topology: WSNs often have a dynamic topology, as sensors can be mobile or out of service. The research deals with the design of algorithms for topology management, change detection, network reconfiguration, and ensuring reliable connection in a dynamic environment [47; 48]. * Efficient routing: It is an important aspect of WSNs. Since sensors are often spread over large areas, it is necessary to find optimal paths for data transmission from one point to another. Research in this area deals with the design of efficient routing protocols that consider energy constraints, network topological properties, FRR mechanisms, and others [8]. As part of our research, we are focusing on the last-mentioned research area, effective direction, and we established the following subproblem areas:  
* Fast network recovery (Fast Reroute, FRR): This area deals with the development of techniques and protocols that enable fast connection recovery in the event of a link or node failure in the network. The goal is to minimize the impact of outages on operations and ensure that the network restores its functionality as quickly as possible. * Fault detection and traffic rerouting: This area focuses on identifying outages and faults in the network and then rerouting traffic to alternative paths. The goal is to minimize the impact of a failure on the connection and ensure continuous operation of the network. \begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline  & **B-REP** & **EM-REP** & **MRC** & **MRT** & **LFA** & **R-LFA** & **D-LFA** \\ \hline
100\% Repair Coverage & Yes & Yes & Yes & Yes & No & No & Yes \\ Custom Alternative Path & Yes & No & Yes & No & No & No & No \\ Precomputing & Yes & No & Yes & Yes & Yes & Yes & Yes \\ Packet Modification & Yes & Yes & Yes & Yes & No & Yes & Yes \\ Link-State Dependency & Yes & No & Yes & Yes & No & Yes & Yes \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Comparison of existing FRR mechanisms. * Ad hoc On-demand Distance Vector protocol (AODV): The AODV routing protocol is widely used in ad hoc wireless networks. The goal is to verify the effectiveness and efficiency of this protocol in the context of rapid network recovery and traffic rerouting after an outage. * OMNET++ simulation environment: The OMNET++ simulation environment aims to test the designed add-on module and evaluate its impact on the speed of fault detection, packet loss prevention, and network recovery process. * New add-on module based on RFC 5880 (BFD): This area deals with the design and implementation of a new module in the AODV routing protocol, which is based on RFC 5880 (Bidirectional Forwarding Detection--BFD) standards. The goal is to use BFD to speed up fault detection and improve network recovery after an outage. Overall, in this work, we investigate fast network recovery (FRR) techniques and their application to ad hoc wireless sensor networks.