IMDEA Networks Institute Digital Repository
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Analyzing gender inequality through large-scale Facebook advertising data
No full textOnline social media are information resources that can have a transformative power in society. While the Web was envisioned as an equalizing force that allows everyone to access information, the digital divide prevents large amounts of people from being present online. Online social media, in particular, are prone to gender inequality, an important issue given the link between social media use and employment. Understanding gender inequality in social media is a challenging task due to the necessity of data sources that can provide large-scale measurements across multiple countries. Here, we show how the Facebook Gender Divide (FGD), a metric based on aggregated statistics of more than 1.4 billion users in 217 countries, explains various aspects of worldwide gender inequality. Our analysis shows that the FGD encodes gender equality indices in education, health, and economic opportunity. We find gender differences in network externalities that suggest that using social media has an added value for women. Furthermore, we find that low values of the FGD are associated with increases in economic gender equality. Our results suggest that online social networks, while suffering evident gender imbalance, may lower the barriers that women have to access to informational resources and help to narrow the economic gender gap.pu
Deadline-constrained content upload from multihomed devices: Formulations and algorithms
Get PDFThis work originates from the practical requirements of video surveillance in public transport systems, where security cameras store video onboard, and a central operator occasionally needs to access portions of the recordings. When this happens, the selected video portions must be uploaded within a given deadline, using (multiple) wireless interfaces, with different costs (which correspond to, e.g., tariffs). We study this video upload problem as a scheduling problem with deadline, where our goal is to choose which interfaces to use and when, so as to minimize the cost of the upload while meeting the given deadline. Our study gives rise to adaptive schedulers that require only a very coarse knowledge of the wireless interfaces bandwidth.
In this paper, we first assume an oracle has the perfect knowledge about the available bandwidth of wireless interfaces at each time, and we formulate an optimization problem to minimize the upload cost within the given deadline. Second, we propose greedy oracle-based heuristics that perform very close to optimal, and that can provide a simple baseline for performance. Third, we formulate a stochastic optimization problem, assuming only the knowledge of the distribution of available bandwidth, and, fourth, we propose adaptive schedulers, that we simulate and also implement and test in a real testbed.
Simulation results demonstrate that the proposed adaptive solutions can effectively leverage the fundamental trade-off between upload cost and completion time, despite unpredictable variations in the available bandwidth of wireless interfaces. Experiments with real mobile nodes provided by the MONROE platform confirm the findings.pu
CARES: Computation-aware Scheduling in Virtualized Radio Access Networks
Get PDFIn a virtualized Radio Access Network (RAN), baseband processing is performed by software running in cloud- computing platforms. However, current protocol stacks were not designed to run in this kind of environments: the high variability on the computational resources consumed by RAN functions may lead to eventual computational outages (where frames are not decoded on time), severely degrading the resulting performance. In this paper, we address this issue by re-designing two key functions of the protocol stack: (i) scheduling, to select the transmission of those frames that do not incur in computational outages, and (ii) modulation and coding scheme (MCS) selection, to downgrade the selected MCS in case no sufficient computational resources are available. We formulate the resulting problem as a joint optimization and compute the (asymptotically) optimal solution to this problem. We further show that this solution involves solving an NP-hard problem, and propose an algorithm to obtain an approximate solution that is computationally efficient while providing bounded performance over the optimal. We thoroughly evaluate the proposed approach via simulation, showing that it can provide savings as high as 80% of the computational resources while paying a small price in performance.pu
Panel: Social implications of future technologies
No full textPanel Moderator: Juan Mulet (Director, Fundación España Digital, Spain)
Panel Members: Elisa Martín Garijo, (Technology Director, IBM Spain, Portugal, Greece and Israel; Member IBM’s Technology Academy), Arturo Azcorra (Director of IMDEA Networks Institute; Professor at Univ. Carlos III of Madrid), Juan Diez-Nicolás (President-Founder of ASEP - Análisis Sociológicos, Económicos y Políticos, S.A.; Member of the Spanish Royal Academy of Moral & Political Sciences), Juan José Moreno Navarro (Representative of the Madrid Assembly; Professor at Universidad Politécnica de Madrid)FALSEpu
Formalizing and Implementing Distributed Ledger Objects
Get PDFDespite the hype about blockchains and distributed ledgers, no formal abstraction of these objects has been proposed. To face this issue, in this paper we provide a proper formulation of a distributed ledger object. In brief, we define a ledger object as a sequence of records, and we provide the operations and the properties that such an object should support. Implementation of a ledger object on top of multiple (possibly geographically dispersed) computing devices gives rise to the distributed ledger object. In contrast to the centralized object, distribution allows operations to be applied concurrently on the ledger, introducing challenges on the consistency of the ledger in each participant. We provide the definitions of three well known consistency guarantees in terms of the operations supported by the ledger object: (1) atomic consistency (linearizability), (2) sequential consistency, and (3) eventual consistency. We then provide implementations of distributed ledgers on asynchronous message passing crash-prone systems using an Atomic Broadcast service, and show that they provide eventual, sequential or atomic consistency semantics. We conclude with a variation of the ledger – the validated ledger – which requires that each record in the ledger satisfies a particular validation rule.TRUEpu
Multi-domain VNF Mapping
Get PDF5G technologies are taking benefit of the Network Function Virtualization to achieve more flexible deployments. This new paradigm allows the resource sharing between operators in federated environments thanks to the decomposition of services into virtual network functions connected together composing a “service function chain”. This work proposes algorithms to solve the placement of such chains in federated multi-domain scenarios satisfying imposed restrictions in terms of resource sharing. Algorithms run on top of an implemented simulator for federated scenarios where multiple operators are involved. Two of our proposed solutions reach O(N ) running times in certain scenarios. Our results also show that we achieve acceptance ratios very similar to those obtained using a tabu meta-heuristic implementation.TRUEpu
Selecting the top-quality item through crowd scoring
Get PDFWe investigate crowdsourcing algorithms for finding the top-quality item within a large collection of objects with unknown intrinsic quality values. This is an important problem with many relevant applications, for example in networked recommendation systems. The core of the algorithms is that objects are distributed to crowd workers, who return a noisy and biased evaluation. All received evaluations are then combined, to identify the top-quality object. We first present a simple probabilistic model for the system under investigation. Then, we devise and study a class of efficient adaptive algorithms to assign in an effective way objects to workers. We compare the performance of several algorithms, which correspond to different choices of the design parameters/metrics. In the simulations we show that some of the algorithms achieve near optimal performance for a suitable setting of the system parameters.pu
Unsupervised Scalable Statistical Method for Identifying Influential Users in Online Social Networks
Get PDFBillions of users interact intensively every day via Online Social Networks (OSNs) such as Facebook, Twitter, or Google+. This makes OSNs an invaluable source of information, and channel of actuation, for sectors like advertising, marketing, or politics. To get the most of OSNs, analysts need to identify influential users that can be leveraged for promoting products, distributing messages, or improving the image of companies. In this report we propose a new unsupervised method, Massive Unsupervised Outlier Detection (MUOD), based on outliers detection, for providing support in the identification of influential users. MUOD is scalable, and can hence be used in large OSNs. Moreover, it labels the outliers as of shape, magnitude, or amplitude, depending of their features. This allows classifying the outlier users in multiple different classes, which are likely to include different types of influential users. Applying MUOD to a subset of roughly 400 million Google+ users, it has allowed identifying and discriminating automatically sets of outlier users, which present features associated to different definitions of influential users, like capacity to attract engagement, capacity to attract a large number of followers, or high infection capacity.pu
The Cloud that Runs the Mobile Internet: A Measurement Study of Mobile Cloud Services
Get PDFMobile applications outsource their cloud infrastructure
deployment and content delivery to cloud computing services and content delivery networks. Studying how these services, which we collectively denote Cloud Service Providers (CSPs), perform over Mobile Network Operators (MNOs) is crucial to understanding some of the performance limitations of today’s mobile apps. To that end, we perform the first empirical study of the complex dynamics between applications, MNOs and CSPs. First, we use real mobile app traffic traces that we gathered through a global crowdsourcing campaign to identify the most prevalent CSPs supporting today’s mobile Internet. Then, we investigate how well these services interconnect with major European MNOs at a topological level, and measure their performance over European MNO networks through a monthlong measurement campaign on the MONROE mobile broadband testbed. We discover that the top 6 most prevalent CSPs are used by 85% of apps, and observe significant differences in their performance across different MNOs due to the nature of their services, peering relationships with MNOs, and deployment strategies. We also find that CSP performance in MNOs is affected by inflated path length, roaming, and presence of middleboxes, but not influenced by the choice of DNS resolver.TRUEpu