  Interest in smart cities is rapidly rising due to the global rise in
urbanization and the wide-scale instrumentation of modern cities. Due to the
considerable infrastructural cost of setting up smart cities and smart
communities, researchers are exploring the use of existing vehicles on the
roads as "message ferries" for the transport data for smart community
applications to avoid the cost of installing new communication infrastructure.
In this paper, we propose an opportunistic data ferry selection algorithm that
strives to select vehicles that can minimize the overall delay for data
delivery from a source to a given destination. Our proposed opportunistic
algorithm utilizes an ensemble of online hiring algorithms, which are run
together in passive mode, to select the online hiring algorithm that has
performed the best in recent history. The proposed ensemble based algorithm is
evaluated empirically using real-world traces from taxies plying routes in
Shanghai, China, and its performance is compared against a baseline of four
state-of-the-art online hiring algorithms. A number of experiments are
conducted and our results indicate that the proposed algorithm can reduce the
overall delay compared to the baseline by an impressive 13% to 258%.
