Sonia Toubaline

@article{Desmouceaux2018a,
title = {Flow-Aware Workload Migration in Data Centers},
author = {Yoann Desmouceaux and Sonia Toubaline and Thomas Clausen},
url = {https://link.springer.com/epdf/10.1007/s10922-018-9452-5?author_access_token=qm_40d91CsNLlZ_vZ0tZFPe4RwlQNchNByi7wbcMAY4xSrvbLplDMLQ3AN9vWEoUIxtZAIdnOGAzJH5W3YOrbGteOLvaEXsEE1xFv66lVxTKlL40BAS25fsaLf8w1RJAvY69owHWqhJkTmAZpvdCkQ%3D%3D
https://www.epizeuxis.net/wp-content/uploads/2018/03/jons-2018.pdf},
doi = {10.1007/s10922-018-9452-5},
year = {2018},
date = {2018-03-10},
journal = {Springer - Journal of Network and Systems Management (JONS)},
abstract = {In data centers, subject to workloads with heterogeneous (and sometimes short) lifetimes, workload migration is a way of attaining a more efficient utilization of the underlying physical machines.
To not introduce performance degradation, such workload migration must take into account not only machine resources, and per-task resource requirements, but also application dependencies in terms of network communication.

This articleformat presents a workload migration model capturing all of these constraints.
A linear programming framework is developed allowing accurate representation of per-task resources requirements and inter-task network demands. Using this, a multi-objective problem is formulated to compute a re-allocation of tasks that (i) maximizes the total inter-task throughput, while (ii) minimizing the cost incurred by migration and (iii) allocating the maximum number of new tasks.

A baseline algorithm, solving this multi-objective problem using the $epsilon$-constraint method is proposed, in order to generate the set of Pareto-optimal solutions. As this algorithm is compute-intensive for large topologies, a heuristic, which computes an approximation of the Pareto front, is then developed, and evaluated on different topologies and with different machine load factors. These evaluations show that the heuristic can provide close-to-optimal solutions, while reducing the solving time by one to two order of magnitudes.
},
keywords = {},
pubstate = {published},
tppubtype = {article}
}

@inproceedings{Toubaline2015,
title = {Observing the State of a Smart Grid Using Bilevel Programming},
author = {Sonia Toubaline and Pierre-Louis Poirion and Claudia D’Ambrosio and Leo Liberti},
url = {https://epizeuxis.net/site/wp-content/uploads/2016/01/cocoa15a.pdf},
year = {2015},
date = {2015-12-18},
booktitle = {In Proceeding of the 9th Annual International Conference on Combinatorial Optimization and Applications (COCOA'15),},
publisher = {LNCS 9486, 364-376},
abstract = {Monitoring an electrical network is an important and chal- lenging task. Phasor measurement units are measurement devices that can be used for a state estimation of this network. In this paper we consider a PMU placement problem without conventional measurements and with zero injection nodes for a full observability of the network. We propose two new approaches to model this problem, which take into ac- count a propagation rule based on Ohm’s and Kirchoff’s law. The natural binary linear programming description models an iterative observability process. We remove the iteration by reformulating its fixed point con- ditions to a bilevel program, which we then further reformulate to a single-level mixed-integer linear program. We also present a bilevel al- gorithm to solve directly the proposed bilevel model. We implemented and tested our models and algorithm: the results show that the bilevel algorithm is better in terms of running time and size of instances which can be solved.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}