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Julien Schleich
![]() Schleich, Julien ![]() ![]() ![]() in Applied Soft Computing (2014), 21(0), 637646 Detailed reference viewed: 219 (12 UL)![]() Schleich, Julien ![]() ![]() ![]() in Proceedings of the 16th European Conference on Applications of Evolutionary Computation (EvoApplications) (2013) Detailed reference viewed: 175 (9 UL)![]() Stathakis, Apostolos ![]() ![]() ![]() in Proceedings of the Genetic and Evolutionary Computation Conference, GECCO '13 (2013) Detailed reference viewed: 188 (14 UL)![]() Schleich, Julien ![]() ![]() in Proceedings of the 11th ACM International Symposium on Mobility Management and Wireless Access (MobiWac'13) (2013) Detailed reference viewed: 270 (18 UL)![]() Stathakis, Apostolos ![]() ![]() ![]() in 2nd ESA Workshop on Advanced Flexible Telecom Payloads (2012) Detailed reference viewed: 169 (18 UL)![]() Schleich, Julien ![]() Doctoral thesis (2010) Ad hoc networks are infrastructure-less spontaneous networks generally composed of wireless and mobile devices. From a practical point of view, ad hoc technologies offer solutions when infrastructure ... [more ▼] Ad hoc networks are infrastructure-less spontaneous networks generally composed of wireless and mobile devices. From a practical point of view, ad hoc technologies offer solutions when infrastructure-based network are too costly, damaged or not suitable. Despite a wide panel of scenarios and the huge number of ad hoc capable devices currently in use, this technology is not widely used because of technical considerations mainly related to the lack of a global coordinator. In this thesis, we propose two different approaches to create virtual backbones in order to organize ad hoc networks. In a first time, we propose a centralized algorithm based on DC programming and DCA to solve the Min m-Vertex Dominating Set Problem and in a second part, we develop distributed and asynchronous algorithms, relying on 2-hop knowledge only, to build k-Vertex Connected m-Vertex Dominating Set-based Virtual Backbones. A global overview of the domain is provided through an extensive state-of-the-art and a hierarchical classification. The efficiency of both approaches is demonstrated with a wide panels of simulations, from randomly generated graphs to more realistic scenarios. [less ▲] Detailed reference viewed: 102 (3 UL)![]() Schleich, Julien ![]() ![]() ![]() in ACM International Symposium on Mobility Management and Wireless Access (2010) We propose to study the quality of CDS-based virtual backbones generated by fully distributed algorithms in mobile environments. As virtual-backbones may be used for different purposes, the importance of ... [more ▼] We propose to study the quality of CDS-based virtual backbones generated by fully distributed algorithms in mobile environments. As virtual-backbones may be used for different purposes, the importance of a characteristic may vary accordingly. In order to deal with this variety issue, we provide a set of quality criteria quantifying different suitable aspects for virtual backbones in mobile ad hoc net- works. Distributed and localized algorithms are then compared through simulations with respect to these measures and criterion-specific optimizations are proposed for the Blackbone2 algorithm. [less ▲] Detailed reference viewed: 158 (10 UL)![]() Schleich, Julien ![]() ![]() ![]() in MOBIWAC - International Symposium on Mobility Management and Wireless Access (2009) This paper introduces Blackbone2, a novel fully decentralized algorithm that aims at creating a robust backbone in ad hoc networks. Backbone robustness is supported by a 2-Connected $m$-dominating Set, $2 ... [more ▼] This paper introduces Blackbone2, a novel fully decentralized algorithm that aims at creating a robust backbone in ad hoc networks. Backbone robustness is supported by a 2-Connected $m$-dominating Set, $2,m$-CDS, and decentralization relies on the usage of two rules that only require two-hop knowledge in order to reduce the use of bandwidth. Blackbone2 deterministic approach guarantees a density-independent valid solution and is proved correct. The algorithm is also characterized by its efficient theoretical computation time, $\mathcal{O}(\Delta^{2})$ with $\Delta$ the average number of neighbors, which outperforms known solutions. The domination parameter, $m$, can be increased without changing the theoretical computation time. Efficiency of the Blackbone2 algorithm compared to the equivalent literature solutions is illustrated through simulations of a large panel of networks with a wide density range. [less ▲] Detailed reference viewed: 186 (16 UL) |
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