PhD Position - Scalability of Data Processing

DistriNet Research Group, Department of Computer Science
September 08 2017
Position Type
Full Time
Organization Type
lmec-DistriNet collaborates with Philips (Netherlands) and the University of Macerata (Italy) in the MarieSklodowska-Curie project HEART (MSCA-ITN Industrial Doctorate- Grant Agreement No. 766139, HEART investigates the design and development of a "HEalth related Activity Recognition system based on the Internet-of-Things (loT); HEART is an international, intersectoral and interdisciplinary training program providing PhD Fellowships to 6 Early Stage Researchers (ESRs). This ESR will focus on distributed middleware for scalable processing of loT health data (e.g. end-to-end architecture design, distributed application deployment, privacy-preserving data collection algorithms). 

You will work in the imec-DistriNet research group (, which belongs to the Department of Computer Science of KU Leuven. The imec-DistriNet group brings together over 80 researchers, of which 11 are professors, 6 are research managers and 16 are postdoctoral researchers. imec-DistriNet is acknowledged for its leading role in secure and distributed software. Microsoft's academic ranking lists KU Leuven (mentioned as “Catholic University of Leuven”) first in the 100 top organizations in Europe in the category “security and privacy” over the past five years. Imec-DistriNet is actively involved in over 35 national and international research projects.
imec-DistriNet has considerable expertise in initiating, executing, and delivering application driven research, often in close collaboration with industry partners. Currently, imec-DistriNet is actively involved in about 35 national and international research projects, ranging from fundamental through strategic-basic to industrial/applied research. The know-how of imec-DistriNet was at the basis of multiple spin-offs, including Ubizen (now part of Verizon Business), a company that specializes in secure e-business and related security services, and VersaSense, which provides wireless Internet of Things (IoT) products and services that radically reduce the total cost of ownership for industrial sensing and control systems (
1) ESR3 will investigate the real-time and energy efficient in-network data analysis in large-scale wireless sensor networks by:
  • Benchmarking to what extent the network load can be decreased by pre-processing data on the sensor nodes (instead of sending large amounts of raw data to the cloud).

  • Modeling trade-offs between in-network processing and cloud processing, for example in terms of network load, energy efficiency, privacy, or data quality.

  • Investigating how to migrate data processing elements into or away from the sensor network, according to dynamically changing operational conditions (e.g. energy restrictions, connectivity or availability of the sensor device).

  • Designing and developing distributed middleware architecture that enables deployment of data processing algorithms to the available sensors, remote configuration of the sensors, and seamless integration of the sensor network with local gateways and the cloud.

2) ESR3 will investigate privacy and security risks (e.g. leaking sensitive information about a person's gender, illness, or activity patterns) associated with large-scale deployments of e-health applications by:
  • Designing & developing middleware services for privacy preservation and data protection.

  • Assessing the legal compliance of these privacy and security services in the European and Chinese context.

3) ESR3 will evaluate the middleware by designing and developing a Proof-of-Concept prototype, using state-of-the-art sensor devices and in close collaboration with the other ESRs.
  • An architecture, capable of providing transparency on the sensor network.

  • A model of a sensor network to simulate sensor/cloud deployment trade-off and to monitor the network and processing load.

  • Embedded software implementation that executes the protocols and algorithms.

  • Efficient privacy-preserving data algorithms developed based on trade-off determined by the place where the data is processed (cloud vs on-device computation).

INDICATIVE PLANNED SECONDMENTS - Institution, place and timing expressed in contract month (M)
  • Philips Electronics Nederland B.V. (Eindhoven, The Netherlands), M2-3,

  • University of Macerata (Italy), M4,

  • Philips Electronics Nederland B.V. (Eindhoven, The Netherlands), M9-11,

  • University of Macerata (Italy), M12-13,

  • Philips Research China (Shanghai, China), M15-19,

  • University of Macerata (Italy), M25,

  • Philips Electronics Nederland B.V. (Eindhoven, The Netherlands), M26,

  • Philips Electronics Nederland B.V. (Eindhoven, The Netherlands), M27-28; 29-34

Further analysis might be required, based on the development of research project.
SUPERVISORS: Hans Hallez (, Danny Hughes (, Dietwig Lowet (

This job comes from a partnership with Science Magazine and Euraxess

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