Congratulations, kudos, and Mabruk to Ayalet Arditi, who had successfully defended her Master thesis work “Evaluating Crowdsourcing Package Delivery Architectures with Mobility Data”. In her work, Ayalet had used massive datasets of location traces to simulate and predict how systems for crowdsourcing package delivery will work in the real world.
While crowdsourcing has the potential of addressing the growing need for faster and cheaper package delivery, without actually deploying the system, it is unclear what are the best ways to deploy those systems in the real world and what is the effect of their design on their performance. Ayelet had implemented a method for simulating package delivery architectures using massive datasets of anonymized real-world location traces, using Spark and other parallel processing techniques to efficiently analyzing them.
Ayelet’s findings show that multi-hop architectures, which allow couriers to transfer packages to their destination by leaving them at intermediate stop points until the next courier picks them up, outperforms one-hop architectures, in which packages can be transferred between origin and destination stop points by one courier. Her analysis also shows that both systems have performance challenges in non-urban areas and in small cities. More generally, this kind of work demonstrates how mobility-based simulation methods can be used to assess the performance of mobile crowdsourcing systems before they are built.