Sabrina Gaito

Opportunistic forwarding in workplaces

So far, the search for Opportunistic Network (ON) applications has focused on urban/rural scenarios where the combined use of mobility and the store-carry-and-forward paradigm helpfully recovers from network partitions and copes with node sparsity. This paper explores the chance of using ONs in workplaces, where the node distribution is denser, thus contributing to reduce the message delivery latency, and where we still find similar needs for informal and unplanned network platforms to support human social relationships and interactions. Both a survey and trace recording experiments have been used to support the analysis of this mobility setting. The ability of recording very short contact times (i.e. lasting few seconds) allowed to interestingly show the slightly different role the social relationships play in dense scenarios and how the large amount of contacts (both short and long), occurring in densily populated spaces, actually contribute to reduce the message-delivery latency and to increase the delivery probability.

Strangers help friends to communicate in opportunistic networks

Peoples inclination to move and meet while engaging in social relationships generates a wide set of contacts ranging from a few seconds to hours. This paper focuses mainly on the role of short contacts and shows how they are essential to the efficiency, stability and simple computation of the forwarding process, thus making affordable in practice efforts to deploy opportunistic networks on top of human contacts. Starting from a rich dataset of contacts that we collected in a university workplace, the paper offers three main contributions. Firstly, it shows that brief contacts contribute significantly to reducing delivery latency and increasing delivery likelihood. Secondly, the brief contacts enable the construction of a taxonomy of social relationships which has proven to be stable over time and easily computable by each handheld device in a distributed way. Finally, the novel description of sociality can be profitably applied to achieve forwarding requirements that combine efficiency of data delivery with stability and simple computation of the adopted metrics.

FDG-PET imaging in HIV-infected subjects: relation with therapy and immunovirological variables

PurposeTo characterise tissue sites of immune activation and HIV replication we performed FDG-PET in ART-treated and ART-naive HIV-infected individuals. Specific aims were to establish whether HIV-infected patients can be differentiated on the basis of the detection of specific locations of viral replication, even in the presence of an apparently optimal immunovirological response to ART, and whether these FDG-PET findings can be related to immunovirological variables and AIDS history status.Patients and methodsPatients were divided into five groups as follows: subgroup A1 (full responders, n = 8): current ART treatment, CD4+ T lymphocytes >500/mL, viral load <50 copies/mL; subgroup A2 (full responders, n = 5): same criteria as A-1, but with a previous history of AIDS; subgroup A3 (immunological non responders, n = 5): current ART treatment, viral load <50 copies/mL, low CD4+ T lymphocytes (<200/mL); group B (virological non responders, n = 2): current ART treatment, CD4+ T lymphocytes around 500/mL, viral load >50,000 copies/mL; group C (ART-naïve, n = 5): no current or previous ART treatment, increased viral load.ResultsPET images revealed different patterns of FDG uptake. All ART-treated patients with either suppressed (<50 copies/mL; Group A) or high viremia (group B) showed a normal pattern of FDG uptake. On the contrary, the ART-naïve subjects with high viraemia (group C) displayed multiple foci of increased glucose metabolism in the lymph nodes. In the ART-naïve subjects, FDG uptake, apparently related to viraemia level, was observed in the upper torso mainly in the axillary nodes bilaterally in patients with viraemia below 100,000 copies/mL; in those with viraemia higher than 100,000 copies/mL, FDG uptake was also observed in the inguinal lymph nodes.ConclusionsThe emergence, in our study, of a correlation between the percentage of CD8+/CD38+/RO+ T cells (well established markers of progression to AIDS independently of CD4+ T lymphocytes) and positive FDG-PET in ART-naive patients is a novel finding that seems to confer prognostic value on FDG uptake. FDG uptake is strongly associated with response to ART independently of a previous AIDS diagnosis. Notably, no differences were observed between ART-treated subjects classed as immunological responders and those classed as non responders. Data herewith indicate that FDG uptake and immunological variables are unrelated when ART is being administered. This is evidence of the complementarity of immunological and FDG measures. FDG uptake is a sensitive marker of disease state and its relation with CD8+/CD38+/CD45RO+ T cells indicates that it can be considered a marker of disease status. The lack of a correlation between FDG uptake and immunological variables in patients under ART warrants further investigation.

On the bursty evolution of online social networks

The high level of dynamics in todays online social networks (OSNs) creates new challenges for their infrastructures and providers. In particular, dynamics involving edge creation has direct implications on strategies for resource allocation, data partitioning and replication. Understanding network dynamics in the context of physical time is a critical first step towards a predictive approach towards infrastructure management in OSNs. Despite increasing efforts to study social network dynamics, current analyses mainly focus on change over time of static metrics computed on snapshots of social graphs. The limited prior work models network dynamics with respect to a logical clock. In this paper, we present results of analyzing a large timestamped dataset describing the initial growth and evolution of a large social network in China. We analyze and model the burstiness of link creation process, using the second derivative, i.e. the acceleration of the degree. This allows us to detect bursts, and to characterize the social activity of a OSN user as one of four phases: acceleration at the beginning of an activity burst, where link creation rate is increasing; deceleration when burst is ending and link creation process is slowing; cruising, when node activity is in a steady state, and complete inactivity.

Extracting human mobility patterns from GPS-based traces

In this paper we analyze few GPS-based traces to infer human mobility patterns. We propose a clustering method to extract the main points of interest, called geo-locations, from GPS data. Starting from geo-locations we propose a definition of community, the geo-community, which captures the relation between a spatial description of human movements and the social context where users live. A statistical analysis of the principal characteristics of human walks provide the fitting distributions of distances covered by people inside a geo-location and among geo-locations and pause time. Finally we analyze factors influencing people when choosing successive location in their movement.

Bus switched networks: An ad hoc mobile platform enabling urban-wide communications

In this paper we propose to leverage the public transportation system of any given city to obtain a scalable and efficient urban backbone by deploying an opportunistic network on buses. The paper proves that Bus Switched Networks (BSNs) are feasible for deployment in real cities and that they can meet the application level requirements for a large class of applications by ensuring high delivery ratio and acceptable delays under different conditions of packet load. We envision a multi-platform metropolitan network backhaul where BSNs play a relevant role and focus on a novel and lightweight probabilistic routing protocol. We prove that the protocol is highly effective in satisfying the loose QoS required by urban-wide delay-tolerant information services and perfectly scales to urban level. The protocol performance evaluation derives from an benchmark analysis of the protocol on three cities which have been selected to explore geo and structural diversity. Finally, the paper presents URBeS, an analysis platform that, given a specific city served by public transportation, produces bus mobility traces and traffic analysis for any given routing protocol.

Fine-Grained Tracking of Human Mobility in Dense Scenarios

This paper envisions an urban scenario where people carry radio devices that can be dynamically networked, by exploiting human contact opportunities, to create unplanned, improvised and localized wireless connectivity, which has been recently called pocket switched networks (PSN).The paper focuses on the radio device (pocket mobility trace recorder, or PMTR) we have on purposely designed and developed to improve this understanding by enabling the gathering of rich and detailed mobility data sets from experiments in real mobility settings. The main contribution of the paper is twofold: we firstly describe the architecture of the radio devices and, secondly, we provide some evidence of the impact short contacts have on forwarding in dense settings.

A two-level social mobility model for trace generation

We propose a synthetic trace generator that, although based on a simple mobility model, generates traces with statistical properties (like inter-contact time and contact duration) resembling those of well-known real traces. The proposed model is based on a waypoint scheme, with some modifications: the introduction of two categories of nodes, steady and nomadic, with different mobility rates; the grouping of nodes in communities sharing the same location preferences, and the definition of a micro-mobility model inside each location. The statistical properties of the traces generated with this model are compared to those obtained from publicly available real traces.

Brief announcement: revisiting the power-law degree distribution for social graph analysis

The study of complex networks led to the belief that the connectivity of network nodes generally follows a Power-law distribution. In this work, we show that modeling large-scale online social networks using a Power-law distribution produces significant fitting errors. We propose the use of a more accurate node degree distribution model based on the Pareto-Lognormal distribution. Using large datasets gathered from Facebook, we show that the Power-law curve produces a significant over-estimation of the number of high degree nodes, leading researchers to erroneous designs for a number of social applications and systems, including shortest-path prediction, community detection, and influence maximization. We provide a formal proof of the error reduction using the Pareto-Lognormal distribution, which we envision will have strong implications on the correctness of social systems and applications.

How many places do you visit a day

People mobility enormously augmented in the last decades. However, despite the increased possibilities of fast reaching far places, the places that a person commonly visits remain limited in number. The number of visited places of each person is regulated by some laws that are statistically similar among individuals. In our previous work, we firstly argued that a person visit most frequently always few places, and we confirmed that by some initial experiments. Here, in addition to further validating this result, we build a more sophisticate view of the places visited by the people. Namely, on top of our previous work, which identifies the class of Mostly Visited Points of Interest, we define two next classes: the Occasionally and the Exceptionally Visited Points of Interest classes. We argue and validate on real data, that also the occasional places are very limited in number, while the exceptional ones can grow at will, and by the analysis of the classes of visited points we can distinguish the type of users mobility. This paper firstly demonstrates this property in large experimental scenario, and put the basis for new understanding of people places in several areas as localization, social interactions and human mobility modelling.