# Node Screening Method Based on Federated Learning with IoT in Opportunistic Social Networks
## 2 Related Work  
Recently, the research of data transmission in opportunistic social networks has become a hot issue; how to improve the efficiency and reliability of transmission is worthy of further investigation. Up to now, many people proposed routing algorithms based on data transmission in opportunistic social networks. Here are some of the well-known routing algorithms. The main idea of [PERSON] and [PERSON] [13] was to use the First Contact algorithm [11] on the delay-tolerant network. The basic idea of the algorithm was to copy the message it carries, and then hand it to other nodes that are encountered first. [PERSON] and [PERSON] proposed the Floyd shortest path algorithm [14]. The algorithm took into account the time factor of the wireless link, and it can obtain the shortest delay path more effectively than the First Contact and Direct Delivery algorithms. [PERSON] and [PERSON] [15] believed that data transmission in opportunistic networks needs robustness and flexibility to deal with mobility issues caused by fading. They proposed new data transmission solutions to ensure low latency and low overhead and control unnecessary transmission/duplication, which mainly include two main algorithms: storage-carry-coordinated forwarding routing and information popularity control. [PERSON] [16] studied epidemic routing in energy-constrained delay-tolerant networks (DTN); they found that the optimal dynamic forwarding decision follows a simple threshold-based structure in the mean-field state. [PERSON] and [PERSON] [17] noticed an important social feature of epidemic routing and forwarding strategies in their research, namely degree centrality, and then proposed the EpSoc hybrid routing protocol, which uses the TTL of the message according to the centrality of the node. [PERSON] et al. [18] proposed an expansion method optimized for the reasons of energy consumption and message transmission when studying the epidemic algorithm, to solve the problem that the source node in the network cannot be guaranteed. In the study by DTN, [PERSON], and [PERSON] [19], they found that when the message is transmitted between nodes, the replication process consumes a lot of network resources, so they developed two different transmission paths and two Energy-saving probability forwarding methods for heterogeneous node sets with different available numbers. Among routing algorithms, the flooding routing algorithm is a simple and effective method, but this strategy will generate a large number of duplicate packets, which will greatly occupy network resources. To reduce the cost of flooding in delay-tolerant networks, [PERSON] et al. [20] proposed the ChitChat system, which is a new message routing system based on social context and focuses on sparse connections. Various factors such as buffer space, energy limitation, node density, and sparse network will affect the message transmission, so [PERSON] et al. [21] proposed a new routing protocol that put forward the concept of supernodes on the basis of flooding, and organized the network in the form of clusters to limit flooding. However, in mobile opportunistic networks, connection interruptions caused by node mobility and unreliable wireless links may trigger flooding operations in the route repair process. Therefore, [PERSON] et al. [22] proposed the LOFT algorithm on the basis of flooding, which reduces routing expansion based on the efficient cost of querying localized routing protocols, thus controlling the propagation of routing data packets in the routing discovery and routing repair mechanism. [PERSON] et al. [10] proposed an algorithm called \"Spray and Wait\". This new algorithm can avoid the performance dilemma of practical solutions based on complexity, and also overcome the epidemic and flooding algorithms' drawbacks. [PERSON] and [PERSON] [23] noticed the superiority of this algorithm when studying opportunistic networks, and improved them, then proposed a method of continuously selecting the next node and considering the number of copies that a node can deliver.