# A Resilient LoRa-Based Solution to Support Pervasive Sensing
## 3 Related Work  
A few works have already tried implementing a mesh network using LoRa. In [15], [PERSON] and [PERSON] propose a solution where nodes have sort of a parent/child relationship, moving away from the typical idea of a mesh network and opting for a tree-shaped topology where the gateway is the root node. When a node wants to join the network, it will choose, based on the RSSI of messages and their closeness, its parent among the nearby nodes, thus only creating the strongest possible connections. Each node can only exchange messages with either their parent or, if they exist, their children. The paper states that the gateway has global knowledge of the network, but needs to state how this information is gathered. This is likely performed if the nodes are positioned in set places and never move. This would heavily limit the possible application of the solution proposed by the paper. Additionally, the work focuses mainly on message exchanges to and from the gateway, not allowing communication between nodes not part of a parent/child relationship. This would mean that every communication between nodes, even if they were close enough to exchange messages, would have to go through the gateway, thus posing significant limitations by not allowing packets to be re-routed around the dead node. Finally, while choosing a parent node based on the strength of their connection is a good idea, it needs to address the problem discussed in the previous paper: RSSI values may not be consistent if measured by different devices. In their work, [PERSON] et al. discussed a modified version of the routing protocol AODV to deliver packets from the LoRa Network to the back-end infrastructure [16]. This modified protocol is used by gateways to move messages to and from back-end-connected gateways. When a node has information to deliver to the mainframe, it forwards the message to its gateway, which will, in turn, search for a path to an internet-connected device. The paths considered in this search only consider gateway nodes and completely ignore end-node. This implementation does not resemble a mesh network since only gateways are considered for routing, and typically, they are way fewer than end nodes. The use of LoRaWAN imposes this limitation. Additionally, using a reactive routing protocol means that the network is flooded every time there is a search for a route, wasting time and decreasing the responsiveness of the network. [PERSON] and [PERSON] present the implementation and advantages of a LoRa-based mesh network specifically designed for IoT applications [17]. The paper discusses the network's architecture, deployment, and its ability to provide long-range and low-power communication. It emphasizes the scalability, robustness, and energy efficiency of LoRa technology for various IoT use cases. However, the paper has limitations, including a lack of comprehensive evaluation in real-world scenarios, a lack of comparative analysis, a specific application focus that may limit generalizability, and a limited discussion of challenges and unresolved issues. Further addressing these limitations would enhance understanding and potential improvements of the proposed network. [PERSON] et al. use a matrix to represent the nodes and the connection between nodes [18]. Each value in the matrix represents the signal strength between nodes (RSSI). The path towards a node is calculated using these values and the shortest distance between nodes. Basically, this algorithm chooses the path where the chance of an error occurring during transmission is the lowest. However, the paper needs to state how the nodes share signal strength information, and it seems like it should be static, meaning that the values would not change and should be known ahead of time. Consequently, this solution cannot be applied when nodes are at least somewhat mobile. Additionally, each node already knows the position of all the others, again limiting the use of the algorithm in environments with moving nodes.