Wireless networks exhibit diversity, ranging from mostly disconnected delay tolerant networks and partially connected mobile ad hoc networks, to mostly connected cellular networks. Besides having useful applications, including, vehicular communications, emergency response networks, battlefield networks, and wildlife monitoring, wireless networks face numerous challenges, such as unreliable connectivity, bandwidth restrictions, interference, frequent disruptions and delays, power outages, message loss, and malicious attacks. Moreover, when nodes are mobile, communication may be disrupted frequently for longer time periods. Designing protocols to tolerate such disruptions is challenging because of the extreme uncertainty in mobile wireless environments. Most of the existing approaches either require exact knowledge about future connectivity schedules, or perform message flooding in an attempt to improve message delivery rate. However, message flooding results in an increased overhead and loss of messages in resource constrained environments. Moreover, it is almost impossible to acquire precise future contact schedules in real-life scenarios. The goal of this dissertation is to architect robust protocols that overcome disruptions and enable applications in diverse wireless networks. We propose a suite of protocols for wireless environments where nodes transfer messages during opportunistic contacts. To conserve resources, the protocols control flooding by autonomously adapting to the changing network conditions, to find optimal temporal routes between source and destination nodes. Moreover, the dissertation presents novel approaches that utilize time-series forecasting on nodes’ contact patterns. Such routing schemes learn from nodes’ temporal contacts and mobility patterns, and forecasts the future contact opportunities among the nodes. By making precise predictions about future contacts, messages are forwarded to only those nodes that increase the message delivery likelihood. Simulation results proved that the proposed routing framework can be efficiently utilized in many real-life applications to disseminate delay tolerant data, such as electronic newspapers, weather forecasts, movie trailers, emergency information, and travel routes information in various parts of a city. The dissertation also proposes a novel application for mobile social networks that generates real-time recommendation of venues for a group of mobile users. The proposed framework utilizes Ant colony algorithm, social filtering, and hub and authority scores on the users’ contextual information to produce optimal recommendations.