Distributed Query Evaluation in Dynamic Multi-Hop Networks

MARTINEZ Lourdes
under the direction of Christine Collet and Christophe Bobineau.
Funding: ANR UBIQUEST (Sep 10 - Jan 14)

Available data in ubiquitous environments is accelerated with wireless technologies interconnecting an increasing number of heterogeneous devices such as sensors, PDA’s, wearable computers, etc. that can store or produce data.Therefore, more and more devices will be interconnected temporarily in dynamic networks, and cooperate to carry on common tasks such as evaluating distributed queries on these data. The constraints of the participants, such as their limited energy, their communication capabilities, their mobility, as well as the distribution of the resources, make data and network management very challenging.
In ubiquitous environments, meta-information on data such as its location and distribution, cardinalities or data value distribution, are not always available due to the dynamicity of the environment and to the heterogeneity of devices. This invalidates classical distributed query evaluation techniques relying on metainformation.
The objective of this thesis is to design new distributed optimization approaches for these environments. These approaches may rely on distributed algorithms (i.e. protocols) that can perform efficiently in such environments (e.g. for computing aggregates) and on machine learning techniques to minimize needed meta-information.