Real Time Distributed Systems Group

The Real Time Distributed Systems Group is lead by Prof. Vana Kalogeraki. bestcanvas

We explore the world around us by turning sensed data into information. For years, research in fields such as distributed systems, participatory sensing systems, crowdsourcing, social networks and machine learning (ML), has steadily improved techniques for revealing underlying and hidden information from crowdsensed data. Together these trends have the potential for ushering in a new era in understanding and improving the world we live in.

Research Highlights

Featured Project

On Topic Aware Recommendation to Increase Popularity in Microblogging Services, OTM Confederated International Conferences, Rhodes, Greece, 24-28 October 2016

INSIGHT: Dynamic Traffic Management Using Heterogeneous Urban Data, ECML, Riva del Garda, Italy,19-23 September 2016

Intelligent Urban Data Monitoring for Smart Cities, ECML,Riva del Garda, Italy,19-23 September 2016

Location privacy for crowdsourcing applications, UbiComp, Heidelberg, Germany, September 12-16 2016

ChEsS: Cost-Effective Scheduling across multiple heterogeneous mapreduce clusters, ICAC, Wurzburg, Germany, 18-22 July 2016

A fast and efficient entity resolution approach for preserving privacy in mobile data, International Congress on Big Data, San Francisco, USA, June 27 – July 2, 2016

Dynamic Load Balancing Techniques for Distributed Complex Event Processing Systems, DAIS, Heraklion, Crete, Greece, June 6-9, 2016

Using Human Social Sensors for Robust Event Location Detection, DCOSS, Washington DC, USA, May 26 – 28 2016

Pareto-Based Scheduling of MapReduce Workloads, ISORC, York, UK, May 17-20, 2016

Our beta version of our CrowdAlert app is released

NGHCS: Creating the Next-Generation Mobile Human-Centered Systems

The goal of NGHCS is to develop a comprehensive framework to simplify the development of mobile human-centered systems, as well as make them predictable and reliable. Our work has the following research thrusts:

First, we develop techniques for dealing efficiently with dynamic unpredictable factors that such complex systems face, including dynamic workloads, unpredictable occurrence of events, real-time demands of applications, as well as user changes and urban dynamics
Second, we will develop the foundations needed to meet the end-to-end timeliness and reliability demands for the range of distributed systems that we will consider by developing novel techniques at different layers of the distributed environment and studying the tradeoffs involved
Third, we will develop general techniques to push computation and data storage as much as possible to the mobile devices, and to integrate participatory sensing and crowdsourcing techniques

The outcome of the proposed work is expected to have significant impact on a wide variety of distributed systems applications in domains as diverse as transportation systems, environmental systems, healthcare and emergency response.

For more information, visit the project page here