BDDMC 2019 - Workshop on Big Data Driven Mobile Computing

The technological advancements and the ever-growing number of smart devices have increased the amount of mobile-generated data exponentially in the last years. This Big Data comprises digital content like texts, photos, videos, social connections and reactions, as well as sensor measurements, and can be turned into intelligence for solving real-life problems, such as traffic congestion, fraud detection, weather monitoring, and so forth.
New hardware and software tools have been proposed to advance the traditional data processing solutions in order to keep the pace with the Big Data generation. However, these solutions are usually tailored to the conventional commodity hardware. Big Data processing architectures for mobile de- vices have started to become a reality only recently, due to the widespread adoption of mobile devices and cloud computing in combination with the increasing storage and processing capabilities in both the edge and the cloud.
Moreover, thanks to the multitude of wireless interfaces, mobile devices can collaborate with each other to solve different problems. This recent topic, known as Device-to-Device (D2D) computing and edge/fog computing, has paved the way for innovative distributed applications, and contributions on making them faster, more energy efficient, as well as robust to challenges in connectivity are needed. Another open research problem is related to development of mobile computing frameworks that reward users contributing with their devices’ resources and sidelines the selfish ones. Finally, since much of the mobile-generated data is of sensitive nature, anonymizing and protecting such data should be of crucial concern.
Theme of the Workshop
The goal of this workshop is to solicit high-quality research articles on new solutions on advancing the processing of Big Data via mobile computing as well as on new mobile applications, systems, and services that utilize the intelligence generated by Big Data. Potential topics include, but are not limited to, the following:
Big Data driven mobile applications, systems, and services.
System architecture and theory for Big Data driven mobile computing.
Architectures for Big Data processing in mobile computing.

Privacy and security of Big Data in mobile computing.
Grid/Cloud/HPC/GPU techniques for Big Data processing in mobile computing.
Geographically referenced Big Data in mobile computing.
Data driven offloading for mobile traffic and computation.
Distributed computation on mobile devices.
Machine learning on mobile devices.
Collection, processing, and visualization of mobile-generated data.
Real-time and online mobile-data processing.
Distributed information spreading on mobile devices.
Incentive schemes for D2D computation.