| dc.description.abstract | 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. | en_US |
