Data Reductions and Combinatorial Bounds for Improved Approximation Algorithms

Kernelization algorithms in the context of Parameterized Complexity are often based on a combination of reduction rules and combinatorial insights. We will expose in this paper a similar strategy for obtaining polynomial-time approximation algorithms. Our method features the use of approximation-preserving reductions, akin to the notion of parameterized reductions. We exemplify this method to obtain the currently best approximation algorithms for \textsc{Harmless Set}, \textsc{Differential} and \textsc{Multiple Nonblocker}, all of them can be considered in the context of securing networks or information propagation

Death receptor pathways mediate targeted and non-targeted effects of ionizing radiations in breast cancer cells

Delayed cell death by mitotic catastrophe is a frequent mode of solid tumor cell death after γ-irradiation, a widely used treatment of cancer. Whereas the mechanisms that underlie the early γ-irradiation-induced cell death are well documented, those that drive the delayed cell death are largely unknown. Here we show that the Fas, tumor necrosis factor-related apoptosis-inducing ligand (TRAIL) and tumor necrosis factor (TNF)-α death receptor pathways mediate the delayed cell death observed after γ-irradiation of breast cancer cells. Early after irradiation, we observe the increased expression of Fas, TRAIL-R and TNF-R that first sensitizes cells to apoptosis. Later, the increased expression of FasL, TRAIL and TNF-α permit the apoptosis engagement linked to mitotic catastrophe. Treatments with TNF-α, TRAIL or anti-Fas antibody, early after radiation exposure, induce apoptosis, whereas the neutralization of the three death receptors pathways impairs the delayed cell death. We also show for the first time that irradiated breast cancer cells excrete soluble forms of the three ligands that can induce the death of sensitive bystander cells. Overall, these results define the molecular basis of the delayed cell death of irradiated cancer cells and identify the death receptors pathways as crucial actors in apoptosis induced by targeted as well as non-targeted effects of ionizing radiation

Liability-aware security management for 5G

​© 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.Multi-party and multi-layer nature of 5G networks implies the inherent distribution of management and orchestration decisions across multiple entities. Therefore, responsibility for management decisions concerning end-to-end services become blurred if no efficient liability and accountability mechanism is used. In this paper, we present the design, building blocks and challenges of a Liability-Aware Security Management (LASM) system for 5G. We describe how existing security concepts such as manifests and Security-by-Contract, root cause analysis, remote attestation, proof of transit, and trust and reputation models can be composed and enhanced to take risk and responsibilities into account for security and liability management

The role of the pod in seed development: strategies for manipulating yield

Pods play a key role in encapsulating the developing seeds and protecting them from pests and pathogens. In addition to this protective function, it has been shown that the photosynthetically active pod wall contributes assimilates and nutrients to fuel seed growth. Recent work has revealed that signals originating from the pod may also act to coordinate grain filling and regulate the reallocation of reserves from damaged seeds to those that have retained viability. In this review we consider the evidence that pods can regulate seed growth and maturation, particularly in members of the Brassicaceae family, and explore how the timing and duration of pod development might be manipulated to enhance either the quantity of crop yield or its nutritional properties

Problèmes d'optimisation avec propagation dans les graphes : complexité paramétrée et approximation

In this thesis, we investigate the computational complexity of optimization problems involving a “diffusion process” in a graph. More specifically, we are first interested to the target set selection problem. This problem consists of finding the smallest set of initially “activated” vertices of a graph such that all the other vertices become activated after a finite number of propagation steps. If we modify this process by allowing the possibility of ``protecting'' a vertex at each step, we end up with the firefighter problem that asks for minimizing the total number of activated vertices by protecting some particular vertices. In fact, we introduce and study a generalized version of this problem where more than one vertex can be protected at each step. We propose several complexity results for these problems from an approximation point of view and a parameterized complexity perspective according to standard parameterizations as well as parameters related to the graph structure.Dans cette thèse, nous étudions la complexité algorithmique de problèmes d'optimisation impliquant un processus de diffusion dans un graphe. Plus précisément, nous nous intéressons tout d'abord au problème de sélection d'un ensemble cible. Ce problème consiste à trouver le plus petit ensemble de sommets d'un graphe à “activer” au départ tel que tous les autres sommets soient activés après un nombre fini d'étapes de propagation. Si nous modifions ce processus en permettant de “protéger” un sommet à chaque étape, nous obtenons le problème du pompier dont le but est de minimiser le nombre total de sommets activés en protégeant certains sommets. Dans ce travail, nous introduisons et étudions une version généralisée de ce problème dans laquelle plus d'un sommet peut être protégé à chaque étape. Nous proposons plusieurs résultats de complexité pour ces problèmes à la fois du point de vue de l'approximation mais également de la complexité paramétrée selon des paramètres standards ainsi que des paramètres liés à la structure du graphe

Optimization problems with propagation in graphs : Parameterized complexity and approximation

Dans cette thèse, nous étudions la complexité algorithmique de problèmes d'optimisation impliquant un processus de diffusion dans un graphe. Plus précisément, nous nous intéressons tout d'abord au problème de sélection d'un ensemble cible. Ce problème consiste à trouver le plus petit ensemble de sommets d'un graphe à “activer” au départ tel que tous les autres sommets soient activés après un nombre fini d'étapes de propagation. Si nous modifions ce processus en permettant de “protéger” un sommet à chaque étape, nous obtenons le problème du pompier dont le but est de minimiser le nombre total de sommets activés en protégeant certains sommets. Dans ce travail, nous introduisons et étudions une version généralisée de ce problème dans laquelle plus d'un sommet peut être protégé à chaque étape. Nous proposons plusieurs résultats de complexité pour ces problèmes à la fois du point de vue de l'approximation mais également de la complexité paramétrée selon des paramètres standards ainsi que des paramètres liés à la structure du graphe.In this thesis, we investigate the computational complexity of optimization problems involving a “diffusion process” in a graph. More specifically, we are first interested to the target set selection problem. This problem consists of finding the smallest set of initially “activated” vertices of a graph such that all the other vertices become activated after a finite number of propagation steps. If we modify this process by allowing the possibility of ``protecting'' a vertex at each step, we end up with the firefighter problem that asks for minimizing the total number of activated vertices by protecting some particular vertices. In fact, we introduce and study a generalized version of this problem where more than one vertex can be protected at each step. We propose several complexity results for these problems from an approximation point of view and a parameterized complexity perspective according to standard parameterizations as well as parameters related to the graph structure

Toward Scalable Algorithms for the Unsplittable Shortest Path Routing Problem

In this paper, we consider the Delay Constrained Unsplittable Shortest Path Routing problem which arises in the field of traffic engineering for IP networks. This problem consists, given a directed graph and a set of commodities, to compute a set of routing paths and the associated administrative weights such that each commodity is routed along the unique shortest path between its origin and its destination, according to these weights. We present a compact MILP formulation for the problem, extending the work in [5] along with some valid inequalities to strengthen its linear relaxation. This formulation is used as the bulding block of an iterative approach that we develop to tackle large scale instances. We further propose a dynamic programming algorithm based on a tree decomposition of the graph. To the best of our knowledge, this is the first exact combinatorial algorithm for the problem. Finally, we assess the efficiency of our approaches through a set of experiments on state-of-the-art instances

The Robust Set problem: parameterized complexity and approximation

Abstract. In this paper, we introduce the k-Robust Set problem: given a graph G = (V, E), a threshold function t: V → N and an integer k, find a subset of vertices V ′ ⊆ V of size at least k such that every vertex v in G has less than t(v) neighbors in V ′. This problem occurs in the context of the spread of undesirable agents through a network (virus, ideas, fire,...). Informally speaking, the problem asks to find the largest subset of vertices with the property that if anything bad happens in it then this will have no consequences on the remaining graph. The threshold t(v) of a vertex v represents its reliability regarding its neighborhood; that is, how many neighbors can be infected before v gets himself infected. We study in this paper the parameterized complexity of k-Robust Set and the approximation of the associated maximization problem. When the parameter is k, we show that this problem is W[2]-complete in general and W[1]-complete if all thresholds are constant bounded. Moreover, we prove that, if P = NP, the maximization version is not n 1−ɛ- approximable for any ɛ> 0 even when all thresholds are at most two. When each threshold is equal to the degree of the vertex, we show that k-Robust Set is fixed-parameter tractable for parameter k and the maximization version is APX-complete. We give a polynomial-time algorithm for graphs of bounded treewidth and a PTAS for planar graphs. Finally, we show that the parametric dual problem (n − k)-Robust Set is fixedparameter tractable for a large family of threshold functions.