Coati is a joint team between Inria Sophia Antipolis - Méditerranée and the I3S laboratory (Informatique Signaux et Systèmes de Sophia Antipolis) which itself belongs to CNRS (Centre National de la Recherche Scientifique) and UNS (Univ. Nice Sophia Antipolis). Its research fields are Algorithmics, Discrete Mathematics, and Combinatorial Optimization, with applications to telecommunication networks.

The objectives of the Coati project-team are to design networks and communication algorithms. In order to meet these objectives, the team studies various theoretical problems in Discrete Mathematics, Graph Theory, and Algorithmics and develops applied techniques and tools, especially for Combinatorial Optimization and Computer Simulation. In particular, Coati used in the last years both these theoretical and applied tools for the design of various networks, such as WDM, wireless (radio), satellite, overlay, and peer-to-peer networks. This research has been done within various industrial and international collaborations.

This results also in the production of advanced software such as Grph and DRMSim, and in the contribution to large open source software such as Sage.

Members of Coati have a good expertise in the design and management of wired and wireless backbone, backhaul, broadband, and complex networks. On the one hand, we cope with specific problems such as energy efficiency in backhaul and backbone networks, routing reconfiguration in connection oriented networks (MPLS, WDM), traffic agregation in SONET networks, compact routing in large-scale networks, survivability to single and multiple failures, etc. These specific problems often come from questions of our industrial partners. On the other hand, we study fondamental problems mainly related to routing and reliability that appear in many networks (not restricted to our main fields of applications) and that have been widely studied in the past. However, previous solutions do not take into account the constraints of current networks/traffic such as their huge size and their dynamics. Coati thus puts a significant research effort in the following directions:

**Energy efficiency** at both the design and management levels. More
precisely, we plan to develop accurate modeling of the power consumption of
various parts and components of the networks through measurement done in
collaboration with industrial partners (Alcatel-Lucent, 3Roam, Orange labs,
etc.). Then, we shall propose new designs of the networks and new
routing algorithms in order to lower the power consumption.

**Larger networks:** Another challenge one has to face is the
increase in size of practical instances. It is
already difficult, if not impossible, to solve practical instances optimally
using existing tools. Therefore, we have to find new ways to solve
problems using reduction and decomposition methods, characterization of
polynomial instances (which are surprisingly often the practical ones), or
algorithms with acceptable practical performances.

**Stochastic behaviors:** Larger topologies mean frequent changes due
to traffic and radio fluctuations, failures, maintenance
operations, growth, routing policy changes, etc. We aim at including these
stochastic behaviors in our combinatorial optimization process to handle the
dynamics of the system and to obtain robust designs of networks.

Coati is mostly interested in telecommunications networks. Within this domain, we consider applications that follow the needs and interests of our industrial partners, in particular Orange Labs or Alcatel-Lucent Bell-Labs, but also SME like 3-Roam.

We focus on the design and management of heterogeneous networks. The project has kept working on the design of backbone networks (optical networks, radio networks, IP networks). We also study routing algorithms such as dynamic and compact routing schemes in the context of the FP7 EULER leaded by Alcatel-Lucent Bell-Labs (Belgium), and the evolution of the routing in case of any kind of topological modifications (maintenance operations, failures, capacity variations, etc.).

Our combinatorial tools may be well applied to solve many other problems in various areas (transport, biology, resource allocation, chemistry, smart-grids, speleology, etc.) and we intend to collaborate with teams of these other domains.

For instance, we have recently started a collaboration in Structural Biology with EPI ABS (Algorithms Biology Structure) from Sophia Antipolis (described in Section ). Furthermore, we are also working on robot moving problems coming from Artificial Intelligence/Robotic with Xavier Defago (Associate Professor at Japan Advanded Institute of Science and Technology, Japan). We have also started a collaboration with Amadeus on complex journey planning.

JourneyPlanner is a Java implementation of a recursive algorithm to solve a TSP problem on small dense graphs, where non-trivial constraints must be satisfied, that make commonly used paradigms (as dynamic programming) unfit to the task.

This work is done in collaboration with the R&D service of the "Train Transportation" division of Amadeus.

During this year, we have maintained and augmented already existing softwares. In particular:

DRMSim (http://

Grph (http://

Sage (http://

The objective of BigGraphs is to provide a distributed middleware for very large graphs processing. This new project has received a development grant (ADT) from Inria and is a joint work of three EPI from Inria: COATI, DIANA and SCALE.

The first phase of the project consists in the evaluation of the existing middlewares such as GraphX/Spark or Giraph/Hadoop with respect to the following criteria: ease of deployment, maintenance and use; variety of programming models (Map/Reduce, BSP, (a)synchronous message passing, centralized programming, mobile agent-based, etc.); overall efficiency and memory footprint; etc. One of the chosen use cases is a subgraph of the Twitter graph with 3 millions of nodes and 200 millions of edges. The experiments are run on the NEF cluster at Inria. We have implemented and tested the classic algorithms (using the BSP model): page rank, BFS, connected components as well as the iFUB algorithm for computing the diameter of large graphs.

In parallel, we are testing new ideas through the development of custom solutions for the deployment of application code in heterogeneous environments, for automatic discovery of cluster architecture, for the design of distributed object oriented applications, and techniques for distributed graph computing (asynchronous BSP, messaging, multi-core parallelism, etc.).

The next phase is to decide whether one framework is matching our needs (and use it as a basis for further developments) or if we have to produce our own.

More information on several results presented in this section may be found in the PhD thesis of A. Kodjo , B. Li and T. K. Phan .

The notion of Shared Risk Link Groups (SRLG) captures survivability issues when a set of links of a network may fail simultaneously. The theory of survivable network design relies on basic combinatorial objects that are rather easy to compute in the classical graph models: shortest paths, minimum cuts, or pairs of disjoint paths. In the SRLG context, the optimization criterion for these objects is no longer the number of edges they use, but the number of SRLGs involved. Unfortunately, computing these combinatorial objects is NP-hard and hard to approximate with this objective in general. Nevertheless some objects can be computed in polynomial time when the SRLGs satisfy certain structural properties of locality which correspond to practical ones, namely the star property (all links affected by a given SRLG are incident to a unique node) and the span 1 property (the links affected by a given SRLG form a connected component of the network). The star property is defined in a multi-colored model where a link can be affected by several SRLGs while the span property is defined only in a mono-colored model where a link can be affected by at most one SRLG. In , we extend these notions to characterize new cases in which these optimization problems can be solved in polynomial time or are fixed parameter tractable. We also investigate on the computational impact of the transformation from the multi-colored model to the mono-colored one. Experimental results are presented to validate the proposed algorithms and principles.

Elastic Optical Networks (EONs) promises a better utilization of the spectrum in optical networks. In fact, as the optical transmission spectrum is carved into fixed-length bands in the traditional WDM networks, small bit rates are over-provisioned and very high bit rates do not fit. EONs are moving away from this fixed-grid and allow the spectrum to be divided flexibly: each request is allocated exactly the resources it needs. In , we present two exact algorithms to route and allocate spectrum to a new request in an EON using only Non-Disruptive Defragmentation (Push-Pull). In the first algorithm, we find the shortest routing path for the new request (i.e., the shortest path from source to destination where contiguous spectrum to satisfy the request can be freed) and then find the position that gives the overall minimum delay on that path. In the second algorithm, we find at the same time a routing path and a position in the spectrum, that minimize the delay of insertion (over all other paths and positions). Both algorithms are polynomial in the size of the network, its bandwidth and the number of provisioned requests.

Many studies in literature have shown that energy-aware routing (EAR) can significantly reduce energy consumption for backbone networks. Also, as an arising concern in networking research area, the protocol-independent traffic redundancy elimination (RE) technique helps to reduce (a.k.a compress) traffic load on backbone network. In , , we present an extended model of the classical multi-commodity flow problem with compressible flows. Our model is robust with fluctuation of traffic demand and compression rate. In details, we allow any set of a predefined size of traffic flows to deviate simultaneously from their nominal volumes or compression rates. As an applicable example, we use this model to combine redundancy elimination and energy-aware routing to increase energy efficiency for a backbone network. Using this extra knowledge on the dynamics of the traffic pattern, we are able to significantly increase energy efficiency for the network. We formally define the problem and model it as a Mixed Integer Linear Program (MILP). We then propose an efficient heuristic algorithm that is suitable for large networks. Simulation results with real traffic traces on Abilene, Geant and Germany50 networks show that our approach allows for 16−28% extra energy savings with respect to the classical EAR model.

Recently, due to the increasing power consumption and worldwide gas emissions in ICT (Information and Communication Technology), energy efficient ways to design and operate backbone networks are becoming a new concern for network operators. Since these networks are usually overprovisioned and since traffic load has a small influence on power consumption of network equipments, the most common approach to save energy is to put unused line cards that drive links between neighbouring routers into sleep mode. To guarantee QoS, all traffic demands should be routed without violating capacity constraints and the network should keep its connectivity. From the perspective of traffic engineering, we argue that stability in routing configuration also plays an important role in QoS. In details, frequent changes in network configuration (link weights, slept and activated links) to adapt with traffic fluctuation in daily time cause network oscillations. We propose in a novel optimization method to adjust the link weights of Open Shortest Path First (OSPF) protocol while limiting the changes in network configurations when multi-period traffic matrices are considered. We formally define the problem and model it as Mixed Integer Linear Program (MILP). We then propose an efficient heuristic algorithm that is suitable for large networks. Simulation results with real traffic traces on three different networks show that our approach achieves high energy saving while keeping the networks in stable state (less changes in network configuration).

A routing

Software-defined Networks (SDN), in particular OpenFlow, is a new networking paradigm enabling innovation through network programmability. Over past few years, many applications have been built using SDN such as server load balancing, virtual-machine migration, traffic engineering and access control. We focus on using SDN for energy-aware routing (EAR). SDN can collect traffic matrix and then computes routing solutions satisfying QoS while being minimal in energy consumption (with minimal number of active links). However, prior works on EAR have assumed that the table of OpenFlow switch can hold an infinite number of rules. In practice, this assumption does not hold since the flow table is implemented with Ternary Content Addressable Memory (TCAM) which is expensive and power-hungry. In , , we propose an optimization method to minimize energy consumption for a backbone network while respecting capacity constraints on links and rule space constraints on routers. In details, we present an exact formulation using Integer Linear Program (ILP) and introduce efficient greedy heuristic algorithm. Based on simulations, we show that using this smart rule space allocation, it is possible to save almost as much power consumption as the classical EAR approach.

A communication in a network is a pair of nodes

In the gathering problem, a particular node in a graph, the base station, aims at receiving messages from some nodes in the graph. At each step, a node can send one message to one of its neighbors (such an action is called a call ). However, a node cannot send and receive a message during the same step. Moreover, the communication is subject to interference constraints ; more precisely we consider a binary interference model where two calls interfere in a step, if the sender of one call is at distance at most

Coati is also interested in the algorithmic aspects of Graph Theory. In general we try to find the most efficient algorithms to solve various problems of Graph Theory and telecommunication networks. More information on several results presented in this section may be found in PhD thesis of B. Li and A. Lancin , and in the Habilitation thesis of N. Nisse .

We use graph theory to model various network problems. In general we study their complexity and then we investigate the structural properties of graphs that make these problems hard or easy. In particular, we try to find the most efficient algorithms to solve the problems, sometimes focusing on specific graph classes from which the problems are polynomial-time solvable.

The Gromov hyperbolicity is an important parameter for analyzing complex networks since it expresses how the metric structure of a network looks like a tree. In other words, it provides bounds on the stretch resulting from the embedding of a network topology into a weighted tree. It is therefore used to provide bounds on the expected stretch of greedy-routing algorithms in Internet-like graphs. However, the best known algorithm for computing this parameter has time complexity in

The shortest-path metric

It is well known that many NP-hard problems are tractable in the class of bounded pathwidth graphs. In particular, path-decompositions of graphs are an important ingredient of dynamic programming algorithms for solving such problems. Therefore, computing the pathwidth and associated path-decomposition of graphs has both a theoretical and practical interest. In , , we design a Branch and Bound algorithm that computes the exact pathwidth of graphs and a corresponding path-decomposition. Our main contribution consists of several non-trivial techniques to reduce the size of the input graph (pre-processing) and to cut the exploration space during the search phase of the algorithm. We evaluate experimentally our algorithm by comparing it to existing algorithms of the literature. It appears from the simulations that our algorithm offers a significative gain with respect to previous work. In particular, it is able to compute the exact pathwidth of any graph with less than 60 nodes in a reasonable running-time (10 min.). Moreover, our algorithm also achieves good performance when used as a heuristic (i.e., when returning best result found within bounded time-limit). Our algorithm is not restricted to undirected graphs since it actually computes the vertex-separation of digraphs (which coincides with the pathwidth in case of undirected graphs).

Prefetching is a basic mechanism for faster data access and efficient computing. An important issue in prefetching is the tradeoff between the amount of network's resources wasted by the prefetching and the gain of time. For instance, in the Web, browsers may download documents in advance while a Web surfer is surfing. Since the Web surfer follows the hyperlinks in an unpredictable way, the choice of the Web pages to be prefetched must be computed online. The question is then to determine the minimum amount of resources used by prefetching that ensures that all documents accessed by the Web surfer have previously been loaded in the cache. In , we model this problem as a two-player game similar to Cops and Robber Games in graphs. Let

Tree-Decompositions are the corner-stone of many dynamic programming algorithms for solving graph problems. Since the complexity of such algorithms generally depends exponentially on the width (size of the bags) of the decomposition, much work has been devoted to compute tree-decompositions with small width. However, practical algorithms computing tree-decompositions only exist for graphs with treewidth less than 4. In such graphs, the time-complexity of dynamic programming algorithms based on tree-decompositions is dominated by the size (number of bags) of the tree-decompositions. It is then interesting to try to minimize the size of the tree-decompositions. In , , we consider the problem of computing a tree-decomposition of a graph with width at most

In Graph Searching, a team of searchers aims at capturing an invisible fugitive moving arbitrarily fast in a graph. Equivalently, the searchers try to clear a contaminated network. The problem is to compute the minimum number of searchers required to accomplish this task. Several variants of Graph Searching have been studied mainly because of their close relationship with the pathwidth of a graph. Blin et al. defined the Exclusive Graph Searching where searchers cannot "jump" and no node can be occupied by more than one searcher. In , we study the complexity of this new variant. We show that the problem is NP-hard in planar graphs with maximum degree 3 and it can be solved in linear time in the class of cographs. We also show that monotone Exclusive Graph Searching is NP-complete in split graphs where Pathwidth is known to be solvable in polynomial time. Moreover, we prove that monotone Exclusive Graph Searching is in P in a subclass of star-like graphs where Pathwidth is known to be NP-hard. Hence, the computational complexities of monotone Exclusive Graph Searching and Pathwidth cannot be compared. This is the first variant of Graph Searching for which such a difference is proved.

Our result easily implies that the *treelength* *treewidth* *apex graph*

Communication by stigmergy consists, for agents/robots devoid of other dedicated communication devices, in exchanging information by observing each other's movements, similar to how honeybees use a dance to inform each other on the location of food sources. Stigmergy, while a popular technique in soft computing (e.g., swarm intelligence and swarm robotics), has received little attention from a computational viewpoint, with only one study proposing a method in a continuous environment. An important question is whether there are limits intrinsic to the environment on the feasibility of stigmergy. While it is not the case in a continuous environment, we show that the answer is quite different when the environment is discrete. In , , we consider stigmergy in graphs and identifies classes of graphs in which robots can communicate by stigmergy. We provide two algorithms with different tradeoffs. One algorithm achieves faster stigmergy when the density of robots is low enough to let robots move independently. This algorithm works when the graph contains some particular pairwise-disjoint subgraphs. The second algorithm, while slower solves the problem under an extremely high density of robots assuming that the graph admits some large cycle. Both algorithms are described in a general way, for any graph that admits the desired properties and with identified nodes. We show how the latter assumption can be removed in more specific topologies. Indeed, we consider stigmergy in the grid which offers additional orientation information not available in a general graphs, allowing us to relax some of the assumptions. Given an

Consider a set of mobile robots with minimal capabilities placed over distinct nodes of a discrete anonymous ring. Asynchronously, each robot takes a snapshot of the ring, determining which nodes are either occupied by robots or empty. Based on the observed configuration, it decides whether to move to one of its adjacent nodes or not. In the first case, it performs the computed move, eventually. The computation also depends on the required task. In , we solve both the well-known Gathering and Exclusive Searching tasks. In the former problem, all robots must simultaneously occupy the same node, eventually. In the latter problem, the aim is to clear all edges of the graph. An edge is cleared if it is traversed by a robot or if both its endpoints are occupied. We consider the exclusive searching where it must be ensured that two robots never occupy the same node. Moreover, since the robots are oblivious, the clearing is perpetual, i.e., the ring is cleared infinitely often. In the literature, most contributions are restricted to a subset of initial configurations. Here, we design two different algorithms and provide a characterization of the initial configurations that permit the resolution of the problems under minimal assumptions.

Today's Web services – such as Google, Amazon, and Facebook – leverage user data for varied purposes, including personalizing recommendations, targeting advertisements, and adjusting prices. At present, users have little insight into how their data is being used. Hence, they cannot make informed choices about the services they choose.

In Coati, we have recently started a collaboration with EPI ABS (Algorithms Biology Structure) from Sophia Antipolis on minimal connectivity complexes in mass spectrometry based macro-molecular complex reconstruction . This problem turns out to be a minimum color covering problem (minimum number of colors to cover colored edges with connectivity constraints on the subgraphs induced by the colors) of the edges of a graph, and is surprizingly similar to a capacity maximization problem in a multi-interfaces radio network we were studying.

Consider a set of oligomers listing the subunits involved in sub-complexes of a macro-molecular assembly, obtained e.g. using native mass spectrometry or affinity purification. Given these oligomers, connectivity inference (CI) consists of finding the most plausible contacts between these subunits, and minimum connectivity inference (MCI) is the variant consisting of finding a set of contacts of smallest cardinality. MCI problems avoid speculating on the total number of contacts, but yield a subset of all contacts and do not allow exploiting a priori information on the likelihood of individual contacts. In this context, we present in two novel algorithms, ALGO-MILP-W and ALGO-MILP-WB. The former solves the minimum weight connectivity inference (MWCI), an optimization problem whose criterion mixes the number of contacts and their likelihood. The latter uses the former in a bootstrap fashion, to improve the sensitivity and the specificity of solution sets. Experiments on the yeast exosome, for which both a high resolution crystal structure and a large set of oligomers is known, show that our algorithms predict contacts with high specificity and sensitivity, yielding a very significant improvement over previous work. The software accompanying this paper is made available, and should prove of ubiquitous interest whenever connectivity inference from oligomers is faced.

More information on several results presented in this section may be found in PhD thesis of A. K. Maia de Oliveira , and in the Habilitation thesis of N. Nisse .

Graph colouring is a central problem in graph theory and it has a huge number of applications in various scientific domains (telecommunications, scheduling, bio-informatics, ...). We mainly study graph colouring problems that model ressource allocation problems.

A well-known channel assignment problem is the following: we are given a graph *span* of the used bandwidth.
We studied a particular, yet quite general, case, called *backbone colouring*, in which there are only two levels of interference. So we are given a graph *the backone*.
Two adjacent vertices in

Various on-line colouring procedures are used. The most widespread ones is the greedy one, which results in a greedy colouring.
Given a graph *greedy colouring* of *b-colouring* of a graph *Grundy number* of *b-chromatic number*. Determining the Grundy number and the b-chromatic number of a graph are NP-hard problems in general. For a fixed

We also studied weighted colouring which models various problems of shared resources allocation.
Given a vertex-weighted graph *weighted chromatic number*. In , , we prove that the Weighted Coloring Problem admits a version of the Hajós' Theorem and so we show a necessary and sufficient condition for the weighted chromatic number of a vertex-weighted graph

Frequently, the proper colouring of the graph must be induced by some other parameters that a vertex can compute locally, for example on looking on the labels assigned to its incident edges or to their orientations.

For a connected graph *code* of a vertex *detectable* if every two adjacent vertices of *detection number*

An *orientation* of a graph *indegree* of *proper* if *proper orientation number* of a graph *subcubic* graphs

Graph theory can be roughly partitioned into two branches: the areas of undirected graphs and directed graphs (digraphs). Even though both areas have numerous important applications, for various reasons, undirected graphs have been studied much more extensively than directed graphs. One of the reasons is that many problems for digraphs are much more difficult than their analogues for undirected graphs.

One of the cornerstones of modern (undirected) graph theory is minor theory of Robertson and Seymour. Unfortunately, we cannot expect an equivalent for directed graphs. Minor theory implies in particular that, for any fixed

The concept of arc-disjoint flows in networks is a very general framework within which many well-known and important problems can be formulated. In particular, the existence of arc-disjoint branching flows, that is, flows which send one unit of flow from a given source

an NP-complete problem to decide whether a network

a polynomial problem to decide whether a network

The algorithm for the later result generalizes the polynomial algorithm, due to Lovász, for deciding whether a given input digraph has two arc-disjoint out-branchings rooted at a given vertex.
Finally we prove that under the so-called Exponential Time Hypothesis (ETH), for every

A * $({k}_{1},{k}_{2})$-outdegree-splitting* of a digraph

Duration: May 2014 - April 2015

Inria teams: Scale, Coati

Abstract: This collaboration aims to assess the benefits that digital technologies can bring in complex travel distribution applications. Indeed, these applications require both high performance algorithms and distributed programming methods to search for the best solutions among billions of combinations, in a very short time thanks to the simultaneous use of several hundreds (if not thousands) of computers. These benefits will be demonstrated in an application to build 'off the shelf' optimized packages, fully customized to best meet the complex demands of the traveler.

"Convention de recherche encadrant une bourse CIFRE" on the topic *Smart Transports: optimisation du trafic dans les villes*.

"Convention de recherche encadrant une bourse CIFRE" on the topic *Graphic Processing Units for Signal Processing* with joint supervision with Aoste project.

Coati is part of the joint laboratory Inria / Alcatel-Lucent Bell-labs France within the ADR Network Science and works on the fast computation of topological properties (hyperbolicity, covering, etc.).

The STINT projet (*STructures INTerdites*) is
leaded by the MC2 group (LIP, ENS-Lyon) and involves the G-SCOP laboratory (Grenoble).

The aim of STINT is to answer the following fondamental question: *given a (possibly infinite) family $\psi $ of graphs, what propoerties does a $\psi $-free graph have?*. To this end, it will firstly establish bounds on some classical graph parameters (e.g., clique number, stability number, chromatic number) for

Réseaux de communications, working group of GDR ASR, CNRS.

Action Graphes, working group of GDR IM, CNRS.

Title: EULER (Experimental UpdateLess Evolutive Routing)

Type: COOPERATION (ICT)

Defi: Future Internet Experimental Facility and Experimentally-driven Research

Instrument: Specific Targeted Research Project (STREP)

Duration: October 2010 - June 2014

Partners: Alcatel-Lucent Bell (leader) (Antwerp, Belgique), iMind (Ghent, Belgium), UCL (Louvain, Belgium), RACTI (Patras, Grece), UPC (Barcelona, Spain), UPMC (ComplexNetworks, Paris 6), Inria (Coati, Gang, Cepage). Coordinator: ALCATEL-LUCENT (Belgium)

STREP EULER (Experimental UpdateLess Evolutive Routing) is part of FIRE (Future Internet Research and Experimentation) objective of FP7. It aims at finding new paradigms to design, develop, and validate experimentally a distributed and dynamic routing scheme suitable for the future Internet and its evolution. Coati is the leader of WP3 on Topology Modelling and Routing scheme experimental analysis.

Discrete Optimization group : Lehrstuhl II für Mathematik, RWTH Aachen (Germany)

Robust optimization in backbone networks for energy efficient designs, and chance-constrained programming in backhaul networks subject to link capacity variations.

Title : Algorithms Design and Games for Location, Placement and Infrastructure Leasing (AlGaLoP)

Duration: June 2013- September 2014

Coati and DIT University of Athens (responsible Vassilis Zissimopoulos)

Title: Algorithm for large and Dynamic Networks

Inria principal investigator: Nicolas Nisse

International Partner (Institution - Laboratory - Researcher):

Universidad Adolfo Ibañez, Santiago, Chile

Facultad de Ingeniería y Ciencias

Karol Suchan

Duration: 2013 - 2015

The main goal of this Associate Team is to study the structure of networks (modeled by graphs) to design both efficient distributed algorithms and reliable network topologies suitable to applications. We are interested both in large-scale (Facebook, Internet, etc.) and in smaller networks (e.g., WDM) that handle heavy traffic. More precisely, we aim at designing new techniques of distributed and localized computing to test structural properties of networks and to compute structures (e.g., decompositions) to be used in applications. Concerning the applications, we will first focus on routing and subgraph packing problems.

There are two main objectives:

Find efficient localized algorithms to test certain graph properties or to prove that no such algorithms exist. We will formalize several distributed computing models and analyze which properties can and which cannot be tested in them.

Define graph properties ‚ computable or approximable in distributed systems ‚ such as structures/decompositions/representations. The driving idea is to combine several well studied graph properties in order to obtain more specific structures which we hope to be more easily computable.

To verify the practical efficiency of our results, the designed algorithms will be implemented and compared to existing ones. For this purpose, a particular effort will be put to design and implement algorithms to generate graphs that satisfy properties of interest, in order to use them to test the algorithms.

The originality of the proposal is to combine powerful tools of graphs theory (e.g., FPT complexity) and of combinatorial optimization (Mixed Integer Programming) with distributed computing. One challenge here is to balance between the degree of locality of desired algorithms and the relevance of properties that may be computed.

Action ECOS-SUD: ALgorithmes Distribués pour le calcul de la structure des réseaux, with Chile, 2013-2015.

GAIATO : Graphs And Algorithms Applied To Telecommunications, International Cooperation FUNCAP/FAPs/Inria/INS2i-CNRS, no. INC-0083-00047.01.00/13, with Federal University of Ceara, Brasil, 2014-2016.

Xavier Défago

Date: until Jan 31 2014

Institution: JAIST, Japan

Michele Flammini

Date: Jun 30 - Jul 13 2014

Institution: Univ. L'aquila, Italy

Brigitte Jaumard

Date: Dec 15-21, 2014

Institution: Concordia Univ., Montréal, Canada

Mejdi Kaddour

Date: Oct 13-19 2014

Institution: Univ. Oran, Algeria

Takako Kodate

Date: Mars 21 - Apr 3 2014

Institution: Tokyo Woman's Christian Univ., Suginami-ku, Tokyo, Japan

Arie M. C. A. Koster

Date: Jun 10-13, 2014

Institution: RWTH Aachen Univ., Germany

Gianpiero Monaco

Date: Jul 9-17, 2014

Institution: Univ. L'aquila, Italy

Gabriele Muciaccia

Date: Jan 10-16, 2014

Institution: Royal Holloway, University of London, UK

Jean-Sébastien Sereni

Date: Fev 2-7, 2014

Institution: LORIA, Nancy, France

Julio-Cesar Silva Araújo

Date: Jun 23 - Jul 25 2014

Institution: Univ. Federal do Ceara, Fortaleza, Brazil

Karol Suchan

Date: Sep 7-28 2014

Institution: Univ. Adolfo Ibanez, Santiago, Chile

Joseph Yu

Date: Mar 1 - Apr 18, 2014

Institution: Abbotsford and SFU, Vancouver, Canada

Vassilis Zissimopoulos

Date: Jul 4-12 2014

Institution: NKUA, Athens, Greece

Marthe Bonamy

Date: Jan 27 - Fev 7, 2014

Institution: LIRMM, Montpellier, France

Akram Kout

Date: Sep 1 - Oct 25, 2014

Institution: Univ. Mentouri, Constantine, Algeria,

Esteban H. Roman Catafau

Date: May 8 - Jul 23 2014

Institution: Univ. Adolfo Ibanez, Santiago, Chile

Claudio Carvallho

Date: Dec 2013-Feb 2014

Institution: Federal University of Ceara, Brasil

Supervisor: Frédéric Havet

Renan Dantas

Date: Dec 2013-Feb 2014

Institution: Federal University of Ceara, Brasil

Supervisor: Frédéric Havet

Doldan Juan

Date: Apr 2014 - Aug 2014

Institution: Universidad de Buenos Aires (Argentina)

Supervisor: Nicolas Nisse

Jean-Claude Bermond

Department of Informatics and Telecommunications of the National and Kapodistrian University of Athens, Greece, May 31 -June 14, 2014

David Coudert

Research Unit 1 (RU1) of the Computer Technology Institute and Press "Diophantus" (CTI), Patras, Greece, March 12-16, 2014

Department of Informatics and Telecommunications of the National and Kapodistrian University of Athens, Greece, March 16-22, 2014

Univ. Adolfo Ibañez, Santiago, Chile, November 17-30, 2014

Frédéric Giroire

LIAFA, Paris, France, March 19, 2014

PARGO, Federal University of Ceará, Fortaleza, Brazil, June 9-20, 2014

Frédéric Havet

LIP, ENS Lyon, France, December 15-17, 2014

Nicolas Nisse

JAIST, Kanazawa, Japan, July 22 - August 8, 2014

Univ. Adolfo Ibañez, Santiago, Chile, November 17 - December 12, 2014

Jean-Claude Bermond :

Mediterranean Days 2014, March 12-14 (http://

Frédéric Giroire :

ResCom'14 : school of the *pôle ResCom of GDR ASR of CNRS* on "Network Science", Furiani, Corsica, May 12-16, 2014

Workshop "Energy Aware Networks" of the labex UCN@Sophia (http://

Nicolas Nisse :

GRASTA’14 : 6th Workshop on GRAph Searching, Theory and Applications , Cargèse, Corsica, France, March 31th-April 4th, 2014

Christelle Caillouet :

ResCom'14 : school of the *pôle ResCom of GDR ASR of CNRS* on "Network Science", Furiani, Corsica, May 12-16, 2014

Frédéric Havet :

Bondy is 70 : Paris, France, November 17, 2014;

David Coudert :

Co-chair of ResCom'14, school of the *pôle ResCom of GDR ASR of CNRS* on "Network Science", Furiani, Corsica, May 12-16, 2014

David Coudert :

ROADEF'14 : 15ème congrès annuel de la Société française de recherche opérationnelle et d’aide à la décision, Bordeaux, France

ONDM'14 : 18th International Conference on Optical Networking Design and Modeling, Stockholm, Sweden, May 19-22, 2014

IEEE ICC'14 : IEEE International Conference on Communications, Sydney, Australia, June 10-14, 2014

IEEE Globecom'14 : IEEE Global Communications Conference, Austin, TX, USA, December 8-12, 2014

Frédéric Havet :

WG'14 : 40th International Workshop on Graph-Theoretic Concepts in Computer Science, Orléans, France, June 25-27, 2014;

ICGT'14 : 9th International Colloquium on Graph Theory and combinatorics, Grenoble, France, June 30-July 4, 2014;

BGW'14 : Bordeaux Graph Workshop, Bordeaux, France, November 19-22 2014;

Nicolas Nisse :

16es Rencontres Francophones sur les Aspects Algorithmiques des Télécommunications (AlgoTel 2014), Ile de Ré, France, 3-6 June, 2014.

Jean-Claude Bermond :

Combinatorics Probability and Computing

Computer Science Reviews

Discrete Applied Mathematics

Discrete Mathematics

Discrete Mathematics, Algorithms and Applications

Journal of Graph Theory

Journal of Interconnection Networks (Advisory Board)

Mathématiques et Sciences Humaines

Networks (Wiley)

Parallel Processing Letters

SIAM book series on Discrete Mathematics, Transactions on Network Optimization and Control, Discrete Mathematics, Algorithms and Applications

David Coudert :

Discrete Applied Mathematics (Elsevier)

Networks (Wiley)

Frédéric Havet :

Discrete Mathematics and Theoretical Computer Science

David Coudert :

Pôle ResCom du GDR ASR du CNRS (since 2005)

Rencontres francophones sur les aspects algorithmiques des télécommunications (AlgoTel)

Frédéric Havet :

GT Graphes du GDR IM du CNRS

Ecole de Printemps de Théorie des Graphes

Journée Combinatoire et Algorithmes du Littoral Méditerranéen

ICDCN : 15th International Conference on Distributed Computing and Networks, January 4-7 2014, Coimbatore, India. Attended by Nicolas Nisse.

ROADEF : 15ème congrès annuel de la Société française de recherche opérationnelle et d’aide à la décision, Bordeaux, France, February 26-28. Attended by David Coudert and Alvinice Kodjo (speaker);

STACS : 31st Symposium on Theoretical Aspects of Computer Science, March 5-8 2014, Lyon, France. Attended by Nicolas Nisse.

GRASTA : 6th Workshop on GRAph Searching, Theory and Applications, March 31th-April 4th, 2014, Cargèse, Corsica, France. Attended by David Coudert (speaker), Nicolas Nisse (speaker and organiser), and Stéphane Pérennes.

Nice Workshop on Random Graphs : May 14-15, 2014, Nice, France. Attended by Nicolas Nisse.

ResCom : school of the *pôle ResCom of GDR ASR of CNRS* on "Network Science", Furiani, Corsica, May 12-16, 2014. Attended by David Coudert (Lecturer)

AlgoTel : 16es Rencontres Francophones sur les Aspects Algorithmiques des Télécommunications (AlgoTel 2014), 3-6 June, 2014, Ile de Ré, France. Attended by Fatima Zahra Moataz (speaker), David Coudert, Nicolas Nisse, T. K. Phan (speaker);

WG : 40th International Workshop on Graph-Theoretic Concepts in Computer Science, Orléans, France (June 25-27, 2014). Attended by Frédéric Havet;

SEA : Symposium on Experimental Algorithms, Copenhagen, Denmark, June 29 - July 1st, 2014. Attended by David Coudert (speaker).

ICGT : 9th International colloquium on graph theory and combinatorics, June 30-July 4, 2014, Grenoble, France. Attended by Frédéric Havet and Nicolas Nisse.

MAC : Moving and Computing. Research Meeting on Distributed Computing by Mobile Robots, July 26th 2014, Hida Takayama, Japan. Attended by Nicolas Nisse.

IWOCA : 25th International Workshop on Combinatorial Algorithms, Duluth, Minnesota, USA (October 15-17, 2014). Attended by Benjamin Momège (speaker);

BGW : Bordeaux Graph Workshop, Bordeaux, France, November 19-22 2014. Attended by Frédéric Havet;

Globecom : IEEE Global Communications Conference, Austin, United States (December 8-12, 2014). Attended by Frédéric Giroire (speaker)

STINT : Kick off meeting of ANR STINT, Lyon, February 17-18, 2014. Attended by Jean-Claude Bermond, Frédéric Havet and Stéphane Pérennes;

FIA : Future Internet Assembly, Athens, Greece, March 18-20, 2014. Attended by David Coudert;

EULER : Plenary meeting of FP7 STREP EULER, Paris, France (March 27-28, 2014). Attended by David Coudert;

JSInria : Journées Scientifiques Inria, Lille, France, June 25-27, 2014. Attended by David Coudert (speaker);

EULER : Final review meeting of FP7 STREP EULER project, Brussels, Belgium (August 29, 2014). Attended by David Coudert;

STINT : workshop of ANR STINT, Vercors, France, September 24-26 2014. Attended by Frédéric Havet

Seminar Orange/Inria : Common seminar Orange/Inria, Paris, France, October 28, 2014 Attended by Joanna Moulierac;

Inria-Industrie : Rencontre Inria Industrie "Télécoms du futur", November, 13 2014. Attended by Joanna Moulierac.

Jean-Claude Bermond :

Expert for DRTT, and various projects outside France (Canada, italie, ...)

David Coudert :

Expert for the Future and Emerging Technologies Open Scheme (FET-Open) European program, and the ANR

Frédéric Giroire :

Elected member of I3S laboratory committee since 2012

Frédéric Havet :

Responsible of Pôle ComRed of I3S laboratory;

Expert for the ANR and its Czech analogues;

Nicolas Nisse :

Expert for the ANR

Michel Syska :

Expert for DRTT PACA

**Licence**

Alvinice Kodjo, *Informatique Pratique*, 40h ETD, Level L1, UNS;

Alvinice Kodjo, *Réseaux (Couches supérieures)*, 15h ETD, Level L3, UNS;

Fatima Zahra Moataz, *Programmation avec Python*, 12h ETD, Level L1, Université Nice-Sophia Antipolis;

Fatima Zahra Moataz, *Systèmes Informatiques*, 24h ETD, Level L1, Université Nice-Sophia Antipolis;

Christelle Molle-Caillouet, *IT Tools*, 53h ETD, Level L1, IUT Nice Côte d’Azur, UNS;

Christelle Molle-Caillouet, *Database and advanced information system*, 36h ETD, Level L2, IUT Nice Côte d’Azur, UNS;

Christelle Molle-Caillouet, *Operations Research*, 81h ETD, Level L2, IUT Nice Côte d’Azur, UNS;

Christelle Molle-Caillouet, *Delivery Optimization*, 30h ETD, Level L3, IUT Nice Côte d’Azur, UNS;

Benjamin Momège, *Mathématiques Discrètes*, 75h ETD, Level L3, Polytech'Nice Sophia, UNS;

Joanna Moulierac, *Algorithms and Programming*, 100h ETD, Level L1, IUT Nice Côte d’Azur, UNS;

Joanna Moulierac, *Networks, basics and Advanced Networks*, 150h ETD, Level L1 and L2, IUT Nice Côte d’Azur, UNS;

Michel Syska, *Introduction to Operating Systems*, 40h ETD, Level L1, IUT Nice Côte d’Azur, UNS;

Michel Syska, *Operating Systems : Advanced Programming*, 60h ETD, Level L1, IUT Nice Côte d’Azur, UNS;

Michel Syska, *Bash Scripting*, 40h ETD, Level L2, IUT Nice Côte d’Azur, UNS;

Michel Syska, *Introduction to Algorithms*, 30h ETD, Level L3, IUT Nice Côte d’Azur, UNS;

Michel Syska, *Linux Systems Administration*, 40h ETD, Level L3, IUT Nice Côte d’Azur, UNS;

**Master**

David Coudert, *Algorithms for Telecoms*, 32h ETD, stream UbiNet of Master 2 IFI and Master RIF, UNS;

Frédéric Giroire, *Algorithmics of Telecommunications*, 18h ETD, stream UbiNet of Master 2 IFI and Master RIF, UNS;

Frédéric Giroire, *Green Networks*, 15h ETD, stream UbiNet of Master 2 IFI, UNS;

Frédéric Giroire, *Introduction to probability and statistics*, 15h ETD, International Master 1, UNS;

Frédéric Havet, *Optimisation combinatoire*, 24 ETD, Master 1 and 2, UNS, France;

**School**

David Coudert, *the notion of hyperbolicity in graphs*, 2h ETD, Summer school ResCom;

Collaboration Inria-Lycée International de Valbonne

Nicolas Nisse : co-responsible of the Computer Science course of MPSI;

IUT Nice Côte d'Azur

Joanna Moulierac, Directrice d'études of Semestre 2 décalé at IUT Nice Côte d'Azur, Computer Science Department since september 2013;

Michel Syska, responsible of the Computer Science Department of IUT form September 2011 till September 2014. He has organized the national meeting of the 46 CS departements, Nice, October 16-17.

Stream Ubinet, Master 2 IFI (http://

Jean-Claude Bermond, member of the scientific committee;

Frédéric Giroire, responsible of the Internships, since October 2011;

International Master 1 (http://

Jean-Claude Bermond, member of the scientific committee of the international track of the M1

Nicolas Nisse, "Algorithmic complexity: Between Structure and Knowledge How Pursuit-evasion Games help" , Université Nice Sophia Antipolis, May 23, 2014

Alvinice Kodjo, "Design and Optimization of Wireless Backhaul Networks" , Université Nice Sophia Antipolis, December 18, 2014. Supervisor: David Coudert

Aurélien Lancin, "Étude de réseaux complexes et de leurs propriétés pour l’optimisation de modèles de routage" , Université Nice Sophia Antipolis, December 9, 2014. Supervisor: David Coudert

Bi Li, "Tree Decompositions and Routing Problems" , Université Nice Sophia Antipolis, November 12, 2014. Supervisors: David Coudert and Nicolas Nisse Computer Science, date de soutenance, encadrant(s)

Ana Karolinna Maia De Oliveira, "Subdivisions of Digraphs" , Université Nice Sophia Antipolis, November 5, 2014. Supervisor: Frédéric Havet

Truong Khoa Phan, "Design and Management of Networks with Low Power Consumption" , Université Nice Sophia Antipolis, September 25, 2014. Supervisors: David Coudert and Joanna Moulierac

Guillaume Ducoffe, "Metric properties of large graphs", since September 2014. Supervisor: David Coudert

Nicolas Huin, "Energy-Efficient Software Defined Networks", since October 2014. Supervisor: Frédéric Giroire and Dino Lopez (I3S)

Fatima Zahra Moataz, "Design and optimization of networks subject to failure and link capacity variations", since October 2012. Supervisor: David Coudert

Sebastien Felix, "Smart transports : optimisation du trafic dans les villes", since January 2011. Supervisors: Jean-Claude Bermond and Jérôme Galtier

Paul Bertot (IUT Nice Côte d'Azur, France), "distributed computing of the diameter of large graphs", November-February (3 months). Supervisor: Michel Syska;

Eneina Gjata (Master 2 IFI, parcours ubinet, University Nice-Sophia Antipolis, France), "Analysis of protocols for Data Redundancy Elimination", March-August 2014 (6 months). Supervisor: Joanna Moulierac

Nicolas Huin (Master 2 RIF, University Nice-Sophia Antipolis, France), "Study of a Distributed Live Video Streaming System", March-August 2014 (6 months). Supervisor: Frédéric Giroire

Flavian Jacquot (IUT Nice Côte d'Azur, France), "distributed computing frameworks for large graphs", November-March (4 months). Supervisor: Luc Hogie;

William Lochet (ENS, Lyon, France), pre-doctoral internship on "Subdivision of oriented cycles in digraphs", October-December 2014 (3 months). Supervisor: Frédéric Havet

Alexandros Panagiotidis (International Master 1, University Nice-Sophia Antipolis, France), "Connectivity Inference in Structural Proteomics", May-August 2014 (4 months). Supervisors: David Coudert, Christelle Caillouet

Thomas Wattrelot (Master 1 MAM, Polytech'Nice, UNS), "Comparison of algorithms for the traveling salesman problem", July-August 2014 (2 months). Supervisor: David Coudert

David Coudert :

Member of the HdR jury of Nicolas Nisse, Univ. Nice Sophia Antipolis, May 23, 2014

Member of the PhD jury of François Clad, Univ. Strasbourg, September 22, 2014

Member of the PhD jury of Truong Khoa Phan, Univ. Nice Sophia Antipolis, September 25, 2014

Member of the PhD jury of Bi Li, Univ. Nice Sophia Antipolis, November 12th, 2014

Referee and member of the PhD jury of Massinissa Merabet, Univ. Montpellier, December 5, 2014

Member of the PhD jury of Aurélien Lancin, Univ. Nice Sophia Antipolis, December 9, 2014

Referee and member of the PhD jury of Stéphane Raux, Univ. Paris Diderot, December 12, 2014

Member of the PhD jury of Alvinice Kodjo, Univ. Nice Sophia Antipolis, December 18, 2014

Frédéric Giroire :

Member of the PhD jury of Alain Julé, Université de Cergy-Pontoise, March 7, 2014

Frédéric Havet :

Referee and member of the PhD jury of Julien Bensmail, University of Bordeaux, June 10, 2014

Referee and member of the PhD jury of Remi Watrigant, University Montpellier 2, October 2, 2014

Member of the PhD jury of Ana Karolinna Maia De Oliveira, Univ. Nice Sophia Antipolis, November 5, 2014

Referee and member of the PhD jury of Maxime Cochefert, University of Metz, December 18, 2014

Joanna Moulierac :

Member of the PhD jury of Truong Khoa Phan, Univ. Nice Sophia Antipolis, September 25, 2014

Nicolas Nisse :

Member of the PhD jury of Bi Li, Univ. Nice Sophia Antipolis, November 12, 2014

Jean-Claude Bermond :

Member of the Ph.D. committee of the University of Marseille

Responsible of the Attractivity for Inria Sophia Antipolis - Méditerranée and more generally for the Campus Sophia Tech

David Coudert :

Member of doctoral committee (CSD) of Inria Sophia Antipolis - Méditerranée, since 2009

Nicolas Nisse :

Member of a comité de sélection of 27me section, Univ. Aix-Marseille

Frédéric Havet :

President of a *comité de sélection* of 27eme section of UNS;

Member of a *comité de sélection* of 27eme section of Aix-Marseille Université;

Joanna Moulierac

Member of the *comité de sélection 27e section* of Univ. Nice Sophia Antipolis

Fête de la Science

Frédéric Giroire presented the stand "Mathémagie" (Magie et Mathématiques) at Rians, France, October 13-18, 2014;

Frédéric Havet organized the "Village des Sciences de Rians", October 13-18 (900 attendants) and created several stands and trained some people to conduct them;

Frédéric Havet presented the stand "Pavages: art, preuves et jeux" at Rians, France, October 13-18, 2014.

Institut Esope - Maison des Sciences de Rians

Frédéric Havet is vice-president of the association Esope 21 whose aim is scientific and literary popularization. He organized many local events and conducted various discovery workshops in elementary and secondary schools. In total , in spoke in front of about 30 classes on various topics (Mathematics, Computer Science, Astronomy, Ornithology, Job in research, etc.).