# Optimizing Routing Protocol Design for Long-Range Distributed Multi-Hop Networks  
[PERSON]  
College of Communication and Information Engineering, Xi'an University of Posts and Telecommunications, Xi'an710121, China; [EMAIL_ADDRESS] (S.P. ); [EMAIL_ADDRESS] (R.P. ); [EMAIL_ADDRESS] (H.W. ); [EMAIL_ADDRESS] (X.W. ); [EMAIL_ADDRESS] (Z.Y. ); fjryflyflyflyflyflyflyflyflyflyflyflyflyflyflyf  
networks provide better performance, although there are concerns regarding the scalability of their implementation. In reference [7], the authors compare packet transmission in LoRa single-hop and multi-hop networks, indicating that mesh topologies can effectively monitor large areas; however, there are significant limitations related to security and latency. This paper proposes an improved protocol based on the OLSR protocol, designed for LoRa distributed multi-hop networks. In distributed multi-hop networks, the OLSR protocol provides immediate routing information, meeting the transmission needs of various types of business data. During route establishment and maintenance, nodes exchange periodic broadcast Hello messages for link sensing and neighbor detection and broadcast Topology Control (TC) messages to transmit routing information and the overall network topology status. This consumes part of the channel's resources, causing network congestion. The OLSR protocol reduces the number of retransmissions of the same message within the same area through the Multipoint Relay (MPR) selection mechanism, thereby reducing the network overhead [8]. However, the traditional MPR selection algorithm results in redundant MPR sets, increasing the network overhead. It only uses the hop count as the routing criterion, making it difficult to adapt to actual network link conditions. To address the redundancy in the MPR set selected by the OLSR protocol's MPR selection mechanism, reference [9] proposes a Necessity-first Algorithm (NFA) to select the MPR set, reducing the number of topology control messages and MPRs. However, the authors did not extend their consideration to parameters such as PDR, throughput, delay, and energy consumption. Reference [10] proposes an enhanced MPR selection algorithm that retains the advantages of the traditional MPR selection algorithm and uses an extended local database of three-hop neighboring nodes for MPR selection, further reducing the number of topology control messages and the network overhead. Reference [11] introduces the min-max algorithm, considering Quality of Service (QoS) and node density, and selects MPR nodes based on the maximum signal range. By introducing the min-max algorithm to enhance OLSR performance, this algorithm considers QoS and node density. The min-max algorithm is used to select MPR nodes based on the maximum signal range, analyzing the QoS parameters using different numbers of nodes. Addressing the single routing criterion in the OLSR protocol, reference [12] proposes the ML-OLSR protocol, which calculates link reliability using distance information, derives node reliability (SDN), and introduces mobility-aware and load-aware algorithms. Reference [13] applies metrics such as Expected Transmission Count (ETX), minimum loss, and minimum delay to optimize the OLSR protocol's performance. Reference [14] proposes an optimal routing strategy based on the Dijkstra algorithm to establish predictive communication, though incorrect predictions may result in erroneous route selections, increasing the network overhead. After an in-depth study of the existing literature, this paper, addressing the shortcomings of the MPR selection algorithm in the OLSR protocol, proposes an improved MPR selection algorithm based on connection necessity, resolving redundancy by deleting neighbor nodes with minimal coverage. Addressing the single routing criterion issue in the OLSR protocol, this paper proposes allocating SF to different services in LoRa multi-hop networks, determining service priority, and considering constraints such as communication latency and link reliability.