In this paper, we propose a method to build molecular cages designed to capture a specific substrate. We model a cage as a graph of atoms with coordinates in space, and several constraints on their edges (degree, length and angle). We use a simple method to place binding patterns which are able to interact with certain parts of the substrate. We then propose an algorithm which considers all possible ways of connecting these binding patterns and try to construct the smallest possible molecular paths realizing these connections. We investigate many variants of our method in order to obtain the most efficient algorithm, able to build cages of more than a hundred atoms.

We present a new approach for the prediction of the coarse-grain 3D structure of RNA molecules. We model a molecule as being made of helices and junctions. Those junctions are classified into topological families that determine their preferred 3D shapes. All the parts of the molecule are then allowed to establish long-distance contacts that induce a 3D folding of the molecule. An algorithm relying on game theory is proposed to discover such long-distance contacts that allow the molecule to reach a Nash equilibrium. As reported by our experiments, this approach allows one to predict the global shape of large molecules of several hundreds of nucleotides that are out of reach of the state-of-the-art methods.

Recent developments in optical communications have led to the creation of large scale optical networks allowing its users to run distributed applications with high QoS requirements. In this context, this paper focuses on a strategy of reservation of temporal virtualized resources in an high bandwidth optical network for service composition. In this strategy, the service composition requirements are modeled by a specific workflow graph with constraints. To satisfy such demands, the workflow graph is embedded in a graph modeling the network in which the availability of resources is scheduled in consecutive equal time periods. We first present the models of workflow and network graphs we use and the theoretical problems we focus on. Then, we describe an online embedding algorithm and we evaluate its performances on various demand scenarii.

In this paper we propose PARINET, a new access method to efficiently retrieve the trajectories of objects moving in networks. The structure of PARINET is based on a combination of graph partitioning and a set of composite B+-tree local indexes. PARINET is designed for historical data and relies on the distribution of the data over the network as for historical data, the data distribution is known in advance. Because the network can be modeled using graphs, the partitioning of the trajectory data is based on graph partitioning theory and can be tuned for a given query load. The data in each partition is indexed on the time component using B+-trees. We study different types of queries, and provide an optimal configuration for several scenarios. PARINET can easily be integrated into any RDBMS, which is an essential asset particularly for industrial or commercial applications. The experimental evaluation under an off-the-shelf DBMS shows that PARINET is robust. It also significantly outperforms both MON-tree and another R-tree based access method which are the reference indexing techniques for in-network trajectory databases.

Summary form only given. Broadcast operations are commonly used in a large variety of applications like: video-conference, television, etc. These applications need high level of QoS. Moreover, in such applications, each receiver has to pay to receive data. In the particular case of broadcast, the price paid by a given receiver is determined by multiple parameters like its location in the broadcasting structure. Several authors have studied the specific problem of broadcast pricing. Some of them have proposed particular cost allocation schemes satisfying economic notions of fairness. We investigate the problem of constructing broadcast trees taking into account one of such allocation schemes. Hence, our objective is to minimize simultaneously constraints on QoS parameters (latency) and (a part of) the maximal price paid by receivers. We have shown in a previous paper that this problem is NP-complete. In this paper we restrict the study to well known and widely used topologies: meshes networks. We propose spanning broadcast trees satisfying the following conditions in a large family of meshes: First, there are shortest paths trees rooted in the transmitter: The latency is minimal. Second, the transmitter can be any node of the network: Our method is general. Third, the maximal part of the cost (called assignment in the paper) paid by any receiver does not depend neither on its location in the tree nor on the total number of receivers: this is an important notion of fairness.