Egomunities, Exploring Socially Cohesive Person-based Communities

In the last few years, there has been a great interest in detecting overlapping communities in complex networks, which is understood as dense groups of nodes featuring a low outbound density. To date, most methods used to compute such communities stem from the field of disjoint community detection by either extending the concept of modularity to an overlapping context or by attempting to decompose the whole set of nodes into several possibly overlapping subsets. In this report we take an orthogonal approach by introducing a metric, the cohesion, rooted in sociological considerations. The cohesion quantifies the community-ness of one given set of nodes, based on the notions of triangles - triplets of connected nodes - and weak ties, instead of the classical view using only edge density. A set of nodes has a high cohesion if it features a high density of triangles and intersects few triangles with the rest of the network. As such, we introduce a numerical characterization of communities: sets of nodes featuring a high cohesion. We then present a new approach to the problem of overlapping communities by introducing the concept of ego-munities, which are subjective communities centered around a given node, specifically inside its neighborhood. We build upon the cohesion to construct a heuristic algorithm which outputs a node's ego-munities by attempting to maximize their cohesion. We illustrate the pertinence of our method with a detailed description of one person's ego-munities among Facebook friends. We finally conclude by describing promising applications of ego-munities such as information inference and interest recommendations, and present a possible extension to cohesion in the case of weighted networks

Biais dans les mesures obtenues par un réseau de capteurs sans fil

International audienceIn the area of complex networks, research has been stimulated by the availability of important data sets obtained through automatic measurement. In this article, we focus on interaction data in a hospital, gathered through the use of a wireless sensor network. We highlight the bias introduced by the measurement system and propose a method to reconstruct the original signal which evidences phenomenon which were not visible on the raw data

Energy aware unicast geographic routing

Abstract — In this paper, we are investigating the optimal radio range minimizing the energy globally consummed by a geographical routing process. Considering a geographical greedy routing protocol and a uniform distribution of nodes in the network area, we analytically evaluate the energy cost of a multi-hop communication. This cost evaluation corresponds to the asymptotic behavior of the routing protocol and turns out to be very accurate compared to the results obtained by simulations. We show that this cost is function of the node intensity and we use this result to deduce the optimal radio range. We evaluate this range with two energy consumption models, the first one considering the energy consumed by transmission operations only and the second one considering both transmission and reception operations. These results can be used in two ways. First, the nodes range can be tuned in advance as a function of the expected node intensity during an off-line planning. Second, we propose an adaptative algorithm where nodes tune their powers according to an on-line evaluation of the local node intensity. I

Triangles to Capture Social Cohesion

Although community detection has drawn tremendous amount of attention across the sciences in the past decades, no formal consensus has been reached on the very nature of what qualifies a community as such. In this article we take an orthogonal approach by introducing a novel point of view to the problem of overlapping communities. Instead of quantifying the quality of a set of communities, we choose to focus on the intrinsic community-ness of one given set of nodes. To do so, we propose a general metric on graphs, the cohesion, based on counting triangles and inspired by well established sociological considerations. The model has been validated through a large-scale online experiment called Fellows in which users were able to compute their social groups on Face- book and rate the quality of the obtained groups. By observing those ratings in relation to the cohesion we assess that the cohesion is a strong indicator of users subjective perception of the community-ness of a set of people.Bien que la problématique de détection de communautés dans les réseaux sociaux ait attiré une attention grandissante à travers les sciences ces dernières années, aucun consensus formel n'a été atteint sur la nature de ce qui définit une communauté. Nous introduisons ici un point de vue novateur au problème de communautés recouvrantes. Au lieu de quantifier la qualité d'un ensemble de communautés, nous nous concentrons sur l'aspect intrinsèquement communautaire d'un ensemble donné de nœuds. Pour ce faire, nous proposons une métrique générique sur les graphes, la cohésion, se fondant sur la notion de triangles et inspirée par des résultats établis en sociologie. Ce modèle a été validé à travers Fellows, une expérience à large échelle sur Facebook dans laquelle les utilisateurs avaient la possibilité de calculer de manière automatique leurs groupes d'amis puis de noter la qualité de ceux ci. En observant ces notes et la cohésion des groupes obtenus, nous concluons que la cohésion est une bonne évaluation de la perception subjective de l'aspect communautaire d'un ensemble de nœuds par un utilisateur

Capacity and interference modeling of CSMA/CA networks using SSI point processes

International audienceThe relative location of simultaneous transmitters, i.e. the set of nodes transmitting a frame at a given time, has a crucial impact on the performance of multi hop wireless networks. Two fundamental aspects of wireless network performances are related to these locations: capacity and interference. Indeed, as interference results from the summation of signals stemmed by concurrent transmitters, it directly depends on the transmitters' location. On the other hand, the network capacity is proportional to the number of simultaneous transmitters. In this paper, we investigate original point processes that can be used to model the location of transmitters that comply with the CSMA/CA policies, i.e. the Medium Access Control protocol used in 802.15.4 and 802.11 families of wireless technologies. We first propose the use of the Simple Sequential Inhibition point process to model CSMA/CA networks where clear channel assessment depends on the strongest emitter only. We then extend this point process to model a busy medium detection based on the strength of all concurrent signals. We finally compare the network capacity obtained through realistic simulations to a theoretical capacity estimated using the intensity of the SSI point process. It turns out that the proposed model is validated by the simulations

Demonstration of worldsens: a fast prototyping and performance evaluation of wireless sensor network applications & protocols

International audienceWe present Worldsens, a complete environment for fast prototyping of wireless sensor protocols and applications. Our environment proposes a full simulation platform with both embedded software instruction and radio packet accuracy. We propose a demonstration including a full software design, simulation, performance estimation and deployment on a set of nodes within the same design environment. Through these first experimentations, we show that accurate sensor network simulation is feasible and that complex application design and deployment is affordable

A wireless sensor network to measure the health care workers exposure to tuberculosis

International audienceIn parallel to the advances in modern medicine, health sciences and public health policy, epidemic models aided by computer simulations and information technologies offer an important alternative for the understanding of transmission dynamics and epidemic patterns. In this paper, we focus on the first steps that may lead towards the design of epidemic models, i.e. the measure and analysis of interactions within a closed socio-professional context. More precisely, this project was motivated by the study of the Health Care Workers (HCWs) exposure to tuberculosis in their work environment. Despite the progresses in treatment and prevention, tuberculosis remains a disease in expansion and represents the third cause of death by infectious pathologies in the world. In the health care context, if the transmission is globally controlled, the HCWs exposure remains obscure. Individual factors associated to the contamination of HCWs in their work environment are not precisely known. Our study focus on the evaluation of the intensity and the frequency of contacts between tuberculosis infected patients and HCWs. To gather this information, classical methods consist in performing audits, consulting medical and administrative files or using self-reports of conversations and trusting HCW souvenirs. All these methods are time-consuming, subject to memory failures and interpretations. As an alternate method, we have chosen to dedicate a Wireless Sensor Network (WSN) to gather these interactions inside a Service of Infectious and Tropical Diseases (Bichat-Claude Bernard Hospital, Paris) and a Service of Pneumology (La Piti ´ e Salp ´ etri ` ere Hospital, Paris). Within the two services, each room has been equipped with a sensor node and each HCW carries an autonomous sensor during his presence in the service. An important characteristic of this measurement campaign is that it was performed in a closed environment, over a closed population and during a large continuous period of time. That is, the presence of all HCWs of the units was monitored in all patient rooms, 24/7 during a three months period. In addition to the experimental measure system description, this paper main contributions are the analysis and characterization of this huge and unique data set describing a complex dynamic interaction network, and the impact study of the measurement process bias on the network dynamic. The analyze of large dynamic in situ interaction networks provides an opportunity to study dynamical processes occurring on dynamical networks, such as spreading or epidemical processes, taking into account the dynamics both on and of the network structure

Worldsens: development and prototyping tools for application specific wireless sensors networks

International audienceIn this paper we present Worldsens, an integrated environment for development and rapid prototyping of wireless sensor network applications. Our environment relies on software simulation to help the designer during the whole development process. The refinement is done starting from the high level design choices down to the target code implementation, debug and performance analysis. In the early stages of the design, high level parameters, like for example the node sleep and activity periods, can be tuned using WS-Net, an event driven wireless network simulator. WSNet uses models for applications, protocols and radio medium communication with a parameterized accuracy. The second step of the sensor network application design takes place after the hardware implementation choices. This second step relies on the WSim cycle accurate hardware platform simulator. WSim is used to debug the application using the real target binary code. Precise performance evaluation, including real-time analysis at the interrupt level, are made possible at this low simulation level. WSim can be connected to WSNet, in place of the application and protocol models used during the high level simulation to achieve a full distributed application simulation. WSNet and WSNet+WSim allow a continuous refinement from high level estimations down to low level real-time validation. We illustrate the complete application design process using a real life demonstrator that implements a hello protocol for dynamic neighborhood discovery in a wireless sensor network environment