Improving Delivery Probability in Mobile Opportunistic Networks with Social-Based Routing

There are contexts where TCP/IP is not suitable for performing data transmission due to long delays, timeouts, network partitioning, and interruptions. In these scenarios, mobile opportunistic networks (MONs) a valid option, providing asynchronous transmissions in dynamic topologies. These architectures exploit physical encounters persistent storage communicate nodes that lack continuous end-to-end path. recent years, many routing algorithms have been based on social interactions. Smartphones wearables vogue, applying information optimize paths between nodes. This work proposes Refine Social Broadcast (RSB), algorithm. RSB uses behavior node interests refine the message broadcast network, improving delivery probability while reducing redundant duplication. The proposal combines identification of most influential carry toward destination with interest-based routing. To evaluate performance, applied simulated case use realistic loneliness detection methodology elderly adults. obtained probability, latency, overhead, hops compared popular social-based routers, namely, EpSoc, SimBet, BubbleRap. manifests successful exceeding second-best result (SimBet) by 17% highest overhead (EpSoc) 97%.