# Design Considerations and Performance Evaluation of Gossi Routing in LoRa-Based Linear Networks
## 2 Related Work  
Typically, LoRa technology has been deployed as a hub and spoke topology based on the Layer 3 LoRaWAN protocol [14]. LoRa exhibits substantial potential, particularly as a candidate for a long-range multi-hop network. With its capacity to reliably cover distances of up to 103 km, LoRa emerges as a compelling choice [15]. A small number of researchers have focused on adopting LoRa as a mesh network technology. Very few have considered the issues related to using it as a linear network technology. We summarise the key contributions in this context. [PERSON] et al. explored the issues of concurrent transmission in LoRa communications [16]. A Received-Signal-Strength-Indicator (RSSI)-based evaluation model was proposed that shows LoRa has an unusual communications property, whereby concurrent transmissions do not necessarily result in all communications being corrupted. By synchronising with one transmitter, a receiver will treat other concurrent transmissions as noise. The authors described this as a \"non-destructive communications property\". A slight difference in RSSI values (2 dBm to 3 dBm) increases the chances of a Packet Delivery Rate (PDR) from 82% to 97%, respectively, during concurrent transmission [16]. Chain-type wireless sensor networks can be very effective, especially for underground mine monitoring. The consideration of the new deployment strategy of \"chain-type\" networks promotes the WSNs for special types of environment monitoring such as mines, roads, tunnels, bridges, rivers, pipelines, and greenhouses [17; 18]. Chain-type networks are fundamentally different from other types of networks naturally fit for these types of applications, which may spread over hundreds of miles in distance. These types of networks are also referred to as linear WSNs [19]. Furthermore, in a chain-type network, sensor nodes can be deployed randomly, forming a near-linear pattern (as shown in Figure 2); such a type of formation is still technically known as a chain-type WSN [20]. Simulation results have shown that chain-type WSNs are considered ideal for optimal energy consumption, which results in the extended lifespan of the network [21]. Much research on linear (chain)-type networks has been performed, but very few researchers have considered LoRa as a linear network. The feasibility of LoRa as a linear network has been proposed for pipeline monitoring [22]. The simulation outcomes indicated that LoRa could be regarded as a viable relaying technology for enhancing the reliability and network coverage of IoT applications [23]. The adoption of LoRa technology as a linear network and employing different time slots has great potential and establishes a high degree of reliability [24]. In LoRaWAN, the introduction of a LoRa gateway as a relay node significantly extends the network coverage and improves the packet delivery rate by up to 50% compared to direct communication [25]. An analytical model was proposed, providing new insights by considering LoRaWAN as a multi-hop technology. The proposed model investigates power consumption and throughput using both single-hop and multi-hop relay networks [26]. The LoRaWAN protocol within the thin linear network has been proposed as a multi-hop solution for monitoring applications. Experimental results have demonstrated that the synchronisation of different nodes, considering various time slots and active periods, has a significant impact on network performance, affecting network packet loss and power consumption [27]. LoRa technology has been proposed as an effective solution for implementing a railway signalling system. The performances of network architectures with reference scenarios have also been compared, laying the foundation for innovative railway communication systems [28]. The potential of LoRa LPWAN as a communications technology for underground mining was explored in [29]. LoRa as a multi-hop solution has been proposed for underground sensor networks.