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Ph.D de

Ph.D
Group : Human-Centered Computing

Reified visual properties for composition tasks

Starts on 01/10/2013
Advisor : MACKAY, Wendy

Funding : contrat doctoral INRIA
Affiliation : Université Paris-Sud
Laboratory : LRI

Defended on 16/12/2016, committee :
M. HALSKOV Kim
M. PRIÉ Yannick
M. FEKETE Jean-Daniel
M. CHATTY Stéphane
Mme. MACKAY Wendy

Research activities :

Abstract :


Ph.D. dissertations & Faculty habilitations
DESIGN AND IMPLEMENTATION OF SOFTWARE TOOLS FOR PROGRAMMING ENVIRONMENTS AND FORMAL SPECIFICATIONS.


DISSéMINATION OPTIMALE DE L’INFORMATION DANS LES RéSEAUX


POWER-AWARE PROTOCOLS FOR WIRELESS SENSOR NETWORKS
In this thesis, we propose a formal energy model which allows an analytical study of energy consumption, for the first time in the context of population protocols. Population protocols model one special kind of sensor networks where anonymous and uniformly bounded memory sensors move unpredictably and communicate in pairs. To illustrate the power and the usefulness of the proposed energy model, we present formal analyses on time and energy, for the worst and the average cases, for accomplishing the fundamental task of data collection. Two power-aware population protocols, (deterministic) EB-TTFM and (randomized) lazy-TTF, are proposed and studied for two different fairness conditions, respectively. Moreover, to obtain the best parameters in lazy-TTF, we adopt optimization techniques and evaluate the resulting performance by experiments. Then, we continue the study on optimization for the poweraware data collection problem in wireless body area networks. A minmax multi-commodity netow formulation is proposed to optimally route data packets by minimizing the worst power consumption. Then, a variable neighborhood search approach is developed and the numerical results show its efficiency. At last, a stochastic optimization model, namely the chance constrained semidefinite programs, is considered for the realistic decision making problems with random parameters. A novel simulation-based algorithm is proposed with experiments on a real control theory problem. We show that our method allows a less conservative solution, than other approaches, within reasonable time.