# Blockchain-Assisted Adaptive Reconfiguration Method for Trusted UAV Network
## 2 Related Work  
Mobile self-organizing networks have frequent topology changes due to the mobility of nodes, making it impossible to complete data transmission using static routing protocols. Nodes on the transmission path must be dynamically configured according to specific convergence metrics, such as link state or some vector distance, in order to adapt to network changes. MANET networks are thus dynamically reconfigured networks with a family of a priori routing protocols with optimal link states (OLSR, FSR etc.) [7; 8; 9], as well as reactive routing protocols with distance vectors as convergence conditions, such as AODV [10; 11], DSR [12], and some hybrid routing protocols have been extensively studied. According to OLSR (Optimal Link States Routing Protocol), nodes discover neighboring nodes by sending probe packets periodically, broadcast topology information, and select multipoint relays (MPR) to reduce topology control information (TC), and pre-construct routing tables with optimal link states as the convergence condition.FSR (Fisheye State Routing Protocol) uses probing packets of different frequencies to reduce routing overhead based on OLSR, and employs the principle that the closer the fisheye view is, the clearer it is for nodes of different ranges. AODV (Ad hoc on-demand vector routing protocol) builds routes on-demand with vector distance as the convergence condition AODV (Ad Hoc on-demand vector routing protocol) uses vector distance as a convergence condition to build routes on demand and initiates route discovery and maintenance at the start of transmission, reducing routing overhead but increasing data transmission delay. The above methods of routing reconstruction have a large node search range, are somewhat blind and increase the communication overhead. Some researchers have introduced location information to aid routing, such as the Location Assisted Routing Protocol (LAR) [13] which uses GPS location information to determine transmission nodes, reducing the overhead of route discovery and speeding up network reconfiguration. However, the complex operating environment of UAV networks also increases the likelihood of GPS decoy-like attacks. Due to the limitations of routing overhead and transmission delay, the routing protocols studied above can only be used in small-scale, flat network architectures for MANET and cannot be applied to large-scale, multi-node MANET applications. To enhance the scalability of MANET networks, routing protocols suitable for hierarchical network architectures have received attention, such as the Zone Routing Protocol (ZRP) [14] and its family [15; 16], hierarchical routing protocol (LANMAR) [17; 18], etc. ZRP is a hybrid routing protocol that divides the network into small overlapping areas based on a set range of areas (number of hops). Proactive routing protocols are used within areas to reduce transmission delays, and reactive routing protocols are used between areas to generate routes on demand and reduce inter-area routing overhead. Network routes are dynamically reconfigured via Border Broadcast Resolution Protocol (BRP) based on the central node of the partition and the boundary nodes of the overlapping zones. LANMAR marks the nodes in the MANET network whose neighboring nodes exceed a set threshold number as seek points and configures all seek points as upper layer management networks. Inter-regional node communication is performed through the upper layer network. The common feature of ZRP and LANMAR routing protocols is the dynamic selection of special state nodes in the network to form the upper logical network, and the establishment of a hierarchical network architecture with dynamically configured optimal states in the MANET network, which effectively narrows the scope of routing selection and enhances the network scale operation. The routing protocols studied above assume a secure network and do not take into account unauthorized access, or compromised nodes.