Postdoc: Sensor Networks and Distributed Processing

Keywords: Models, Network analysis, Physic statistic, Process Dynamics

A. Contact:

B. Research program and methodology

An important task needed by the design of a global wireless sensor network is a precise and accurate characterization of the various measures. The challenge is due to the heterogeneous data resolution. Moreover, data will be multi modal and multi scale with possible irregularities and will offer much correlation (time /space).

Fundamental challenges lie in the current lack of tools, models, and methods for the characterization and analysis of time series describing dynamic sensing data. Data set collected by various sensors, may be characterized by the lack of most common simple statistical properties such as stationary, linearity, or Gaussianity. Relevant time scales may be difficult to identify, or may even not exist. Observed properties have non-trivial relations and even the choice of the time scale granularity that should be used in the analysis is a difficult problem, since it may bias the analysis in an uncontrolled way. The intrinsic heterogeneity of the dynamics itself makes it necessary to develop new approaches to handle it. These issues will therefore have to be addressed in order to obtain meaningful results in our context.

It is thus mandatory to be able to characterized sensing data in order to be able to select all appropriate sensors in order to fulfill the requirements of a given application in terms of sensing coverage, in terms of accuracy of the global measure. The Live E! data set available concerns a large scale sensor network ( and manage many kinds of sensors.

With these main challenges in mind, we define the following objectives for this research:

  • Characterize the various sensing measures that we can exploit. Such characterization must take into account the different correlations in space and time that exist between all sensors. The characterization must also handle the various time scales that may exist in the measures.
  • Methodology and design of a global sensing tool. In order to use multi variable/scale sensing data we need to normalize data format and access method. Moreover, based on the characterization described above, we will propose a methodology to select the appropriate measure in order to fulfill the application requirements.
  • Define the methodology of distributed processing that should be performed in order to guarantee an accurate measure. The goal here is to take advantage of the fact that computation could be delocalized closer to the sensing phenomena. Exploiting space/time correlation could be used in order to optimize the amount of data sent through the network.
  • Evaluate the proposed tools and methodologies on real data both publicly available (in priority Live E!).

B. Skills

The candidate is expected to work on a theoretical line. He/She should be be able to perform good critical analyzes of obtained results and be creative in proposing solutions.The candidate will have to possess strong expertise in Networking, especially with data processing and statistical signal processing. Candidates with experiences in international research programs related either to complex systems or sensor networks