National School of Computer Science for Industry and Business
Evry, France
Time filter
Source Type

Cherrier S.,University Paris Est Creteil | Ghamri-Doudane Y.M.,National School of Computer Science for Industry and Business | Lohier S.,University Paris Est Creteil | Roussel G.,University Paris Est Creteil
Proceedings - 2011 IEEE International Conferences on Internet of Things and Cyber, Physical and Social Computing, iThings/CPSCom 2011 | Year: 2011

Smartphones, PDA, Sensors, Actuators, Phidgets and Smart Objects (i.e. objects with processing and networking capabilities) are more and more present in everyday's life. Merging all these technologies with the Internet is often described as'Internet of Things' (IoT). In the IoT vision, Things around us provide a pervasive network of interacting and interconnected devices. However building IoT applications is a long and arduous work, reserved for specialists, requiring specific knowledges in terms of network protocols and programming languages. The lack of widespread and easy-to-configure solutions is an obstacle for the development of this area. A universal framework, offering simplification and standardization, could facilitate the emergence of this promising field in terms of applications and business. IoT needs a solid foundation for rapid, simple development and deployment of new services. In this paper, we present DLITe, a universal framework for building IoT applications over heterogeneous sets of small devices. D-LITe offers solutions for deploying application's logic, and executing it on Smart Objects despite their heterogeneity. An implementation of DLITe on tiny devices, such as TelosB motes, allows to show that our framework is realistic even with the constraints of such devices. © 2011 IEEE.

Cherrier S.,University Paris Est Creteil | Ghamri-Doudane Y.M.,National School of Computer Science for Industry and Business | Lohier S.,University Paris Est Creteil | Roussel G.,University Paris Est Creteil
Proceedings - IEEE Symposium on Computers and Communications | Year: 2012

Wireless Sensor and Actuator Networks (WSAN) and permanent connections to the Internet converge to be an emerging and promising field: Machine-To-Machine (M2M) services. To take advantages of this new field, hardware and software infrastructure compliance must be verified. Services expected by M2M alter the organization of WSAN. The software design in this area can be divided into two main categories: a centralized approach (Orchestration) where a monolithic application collects data and sends orders, and a distributed approach (Choreography) in which nodes offer and use services in a collaborative way. In this paper, we study the impact of these two architectures over WSAN. First, a mathematical analysis shows the improvement offered by choreography, thanks to the use of shorter paths between nodes. Then, an application experiments these two architectural designs to measure the impact on a real testbed. Both the theoretical mathematical analysis and the real platform experiment gives better results for the Choreography in terms of network reliability and path length. Our work quantifies the benefits obtained and provides histograms and numerical results. © 2012 IEEE.

Haddadou N.,University Paris Est Creteil | Rachedi A.,University Paris Est Creteil | Rachedi A.,National School of Computer Science for Industry and Business | Ghamri-Doudane Y.,University Paris Est Creteil
Wireless Communications and Mobile Computing | Year: 2011

In this paper, we propose a newly distributed protocol called Advanced Diffusion of Classified Data (ADCD) to manage information harvesting and distribution in vehicular sensor networks. ADCD aims at reducing the generated overhead, avoiding network congestions as well as long latency to deliver the harvested information. The concept of ADCD is based on the characterization of sensed information (i.e., based on its importance, location, and time of collection) and the diffusion of this information accordingly. Furthermore, ADCD uses an adaptive broadcasting strategy to avoid overwhelming users with messages in which they have no interest. Also, we propose in this paper a new probabilistic model for ADCD based on Markov chain. This one aims to optimally tune the parameters of ADCD, such as the optimal number of broadcaster nodes. The analytical and simulation results based on different metrics, such as the overhead, the delivery ratio, the probability of a complete transmission, and the minimal number of hops, are presented. These results illustrate that ADCD allows mitigating the information redundancy and its delivery with an adequate latency while making the reception of interesting data for the drivers (related to their location) more adapted. Moreover, the ADCD protocol reduces the overhead by 90% compared with the classical broadcast and an adapted version of MobEyes. The ADCD overhead is kept stable whatever the vehicular density. Copyright © 2011 John Wiley & Sons, Ltd.

Bosser A.-G.,University of Teesside | Courtieu P.,French National Conservatory of Arts and Crafts | Forest J.,National School of Computer Science for Industry and Business | Cavazza M.,University of Teesside
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) | Year: 2011

This paper proposes a novel application of Interactive Proof Assistants for studying the formal properties of Narratives, building on recent work demonstrating the suitability of Intuitionistic Linear Logic as a conceptual model. More specifically, we describe a method for modelling narrative resources and actions, together with constraints on the story endings in the form of an ILL sequent. We describe how well-formed narratives can be interpreted from cut-free proof trees of the sequent obtained using Coq. We finally describe how to reason about narratives at the structural level using Coq: by allowing one to prove 2nd order properties on the set of all the proofs generated by a sequent, Coq assists the verification of structural narrative properties traversing all possible variants of a given plot. © 2011 Springer-Verlag.

Billionnet A.,National School of Computer Science for Industry and Business
Systematic Biology | Year: 2013

The phylogenetic diversity (PD) of a set of species is a measure of the evolutionary distance among the species in the collection, based on a phylogenetic tree. Such a tree is composed of a root, internal nodes, and leaves that correspond to the set of taxa under study. With each edge of the tree is associated a non-negative branch length (evolutionary distance). If a particular survival probability is associated with each taxon, the PD measure becomes the expected PD measure. In the Noah's Ark Problem (NAP) introduced by Weitzman (1998), these survival probabilities can be increased at some cost. The problem is to determine how best to allocate a limited amount of resources to maximize the expected PD of the considered species. It is easy to formulate the NAP as a (difficult) nonlinear 0-1 programming problem. The aim of this article is to show that a general version of the NAP (GNAP) can be solved simply and efficiently with any set of edge weights and any set of survival probabilities by using standard mixed-integer linear programming software. The crucial point to move from a nonlinear program in binary variables to a mixed-integer linear program, is to approximate the logarithmic function by the lower envelope of a set of tangents to the curve. Solving the obtained mixed-integer linear program provides not only a near-optimal solution but also an upper bound on the value of the optimal solution. We also applied this approach to a generalization of the nature reserve problem (GNRP) that consists of selecting a set of regions to be conserved so that the expected PD of the set of species present in these regions is maximized. In this case, the survival probabilities of different taxa are not independent of each other. Computational results are presented to illustrate potentialities of the approach. Near-optimal solutions with hypothetical phylogenetic trees comprising about 4000 taxa are obtained in a few seconds or minutes of computing time for the GNAP, and in about 30 min for the GNRP. In all the cases the average guarantee varies from 0% to 1.20%. © 2012 The Author(s).

Burel G.,Max Planck Institute for Informatics | Burel G.,National School of Computer Science for Industry and Business
Logical Methods in Computer Science | Year: 2011

In deduction modulo, a theory is not represented by a set of axioms but by a congruence on propositions modulo which the inference rules of standard deductive systems-such as for instance natural deduction-are applied. Therefore, the reasoning that is intrinsic of the theory does not appear in the length of proofs. In general, the congruence is defined through a rewrite system over terms and propositions. We define a rigorous framework to study proof lengths in deduction modulo, where the congruence must be computed in polynomial time. We show that even very simple rewrite systems lead to arbitrary proof-length speed-ups in deduction modulo, compared to using axioms. As higher-order logic can be encoded as a first-order theory in deduction modulo, we also study how to reinterpret, thanks to deduction modulo, the speed-ups between higher order and first-order arithmetics that were stated by Gödel. We define a first-order rewrite system with a congruence decidable in polynomial time such that proofs of higher-order arithmetic can be linearly translated into first-order arithmetic modulo that system. We also present the whole higher-order arithmetic as a first-order system without resorting to any axiom, where proofs have the same length as in the axiomatic presentation. © G. Burel.

Billionnet A.,National School of Computer Science for Industry and Business
Management of Environmental Quality | Year: 2010

Purpose: Negative effects of habitat isolation that arise from landscape fragmentation can be mitigated, by connecting natural areas through a network of habitat corridors. To increase the permeability of a given network, i.e. to decrease the resistance to animal movements through this network, often many developments can be made. The available financial resources being limited, the most effective developments must be chosen. This optimization problem, suggested in Finke and Sonnenschein, can be treated by heuristics and simulation approaches, but the method is heavy and the obtained solutions are sub-optimal. The aim of the paper is to show that the problem can be efficiently solved to optimality by mathematical programming. Design/methodology/approach: The moves of the individual in the network are modeled by an absorbing Markov chain and the development problem is formulated as a mixed-integer quadratic program, then this program is linearized, and the best developments to make are determined by mixed-integer linear programming. Findings: First, the approach allows the development problem to be solved to optimality contrary to other methods. Second, the definition of the mathematical program is relatively simple, and its implementation is immediate by using standard, commercially available, software. Third, as it is well known with mixed-integer linear programming formulation it is possible to add new constraints easily if they are linear (or can be linearized). Research limitations/implications: With a view to propose a simple and efficient tool to solve a difficult combinatorial optimization problem arising in the improvement of permeability across habitat networks, the approach has been tested on simulated habitat networks. The research does not include the study of some precise species movements in a real network. Practical implications: The results provide a simple and efficient decision-aid tool to try to improve the permeability of habitat networks. Originality/value: The joint use of mathematical programming techniques and Markov chain theory is used to try to lessen the negative effects of landscape fragmentation. © Emerald Group Publishing Limited.

Brahmi I.H.,National School of Computer Science for Industry and Business | Djahel S.,Lero | Ghamri-Doudane Y.,National School of Computer Science for Industry and Business | Ghamri-Doudane Y.,University of Marne-la-Vallée
GLOBECOM - IEEE Global Telecommunications Conference | Year: 2012

Nowadays, Vehicle to Vehicle (V2V) communication is attracting an increasing attention from car manufacturers due to its expected impact in improving driving safety and comfort. IEEE 802.11P is the primary channel access scheme used by vehicles; however it does not provide sufficient spectrum to ensure reliable exchange of safety information. To overcome this issue, many efforts have been devoted to enhance the frequency spectrum utilization efficiency. To this end, the Cognitive Radio (CR) principle has been applied to assist the vehicles to gain extra bandwidth through an opportunistic use of the unused spectrums in their surrounding. In this paper, we focus on safety messages for which we propose an original scheme that makes their exchange among the nearby vehicles more reliable with a significant reduce in their dissemination delay. This improvement is due to the use of a Hidden Markov Model that enables the prediction of the available channels for the subsequent time slots, leading to faster channel allocation for the vehicles. The obtained simulation results confirm the efficiency of our scheme. © 2012 IEEE.

Abdennebi M.,University of Paris 13 | Ghamri-Doudane Y.,National School of Computer Science for Industry and Business
GLOBECOM - IEEE Global Telecommunications Conference | Year: 2012

Call Admission Control is a key function that guarantees the Quality of Service (QoS) for users. In radio networks, this function is usually based on traffic models and ensures that sessions are admitted only if the estimated available bandwidth is enough for the entire call duration. For video on IEEE 802.16, the CAC function must ensure that the bandwidth to be reserved is compatible with the resource availability. For the enhanced SVC (Scalable Video Coding) systems, the CAC function must take into account all the layers and their characteristics. In this paper, we propose an enhanced CAC function for SVC that adapts the admission according to the statistical behaviour of the video sessions. The main goal is to use measurements in the 802.16 base station (BS) to update the traffic model of SVC video flows, this for the different layers of SVC flows. We then use the variability of the traffics generated to adapt the CAC according to the characteristics of incoming flows. To perform that, we use a Markovian model that adapts for each flow instead of using a generic static one as used in most of the papers. Performance evaluation is given to illustrate the interest of our proposal. © 2012 IEEE.

Billionnet A.,National School of Computer Science for Industry and Business
Ecological Modelling | Year: 2011

The Reserve Selection Problem consists in selecting certain sites among a set of potential sites for biodiversity protection. In many models of the literature, the species present and able to survive in each site are supposed to be known. Here, for every potential site and for every species considered, only the probability that the species survives in the site is supposed to be known. The problem to select, under a budgetary constraint, a set of sites which maximizes the expected number of species is known in the literature under the name of probabilistic reserve selection problem. In this article, this problem is studied with species weighting to deal differently with common species and rare species. A spatial constraint is also considered preventing to obtain too fragmented reserve networks. As in Polasky et al. (2000), the problem is formulated by a nonlinear mathematical program in Boolean variables. Camm et al. (2002) developed a mixed-integer linear programming approximation that may be solved with standard integer programming software. The method gives tight approximate solutions but does not allow to tell how far these solutions are from the optimum. In this paper, a slightly different approach is proposed to approximate the problem. The interesting aspect of the approach, which also uses only standard mixed-integer programming software, is that it leads, not only to an approximate solution, but also to an upper limit on the true optimal value. In other words, the method gives an approximate solution with a guarantee on its accuracy. The linear reformulation is based on an upper approximation of the logarithmic function by a piecewise-linear function. The approach is very effective on artificial instances that include up to 400 sites and 300 species. Within an average CPU time of about 12 min, near-optimal solutions are obtained with an average relative error, in comparison to the optimum, of less than 0.2%. © 2010 Elsevier B.V.

Loading National School of Computer Science for Industry and Business collaborators
Loading National School of Computer Science for Industry and Business collaborators