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In this study, we propose a mechanism for identifying early signals of trending rumor events (i.e. controversial emerging topics) in streaming social media. The pattern, combining features of both user's attitude and information diffusion, is applied in the sliding windows of social media data streams. By capturing and analyzing frequent patterns within early windows, we found signal patterns appearing...
The emergence of the Internet of Things in Smart Cities questions how the future citizens will perceive their predominant living and working environments and what quality of living they can experience within it, for instance the level of everyday stress. However, perception and experienced stress levels are challenging metrics to measure and are even more challenging to correlate with an underlying...
The continuously growing wealth of data has radically changed the data science landscape. At the same time, Big Data tools have known important progress in terms of optimising performance and scalability. However, applying them into practical deployment settings is still a challenging task that is highly dependent on the particularities of the data. In this paper, we present our experiences with implementing...
The unprecedented data explosion has drastically changed the data science landscape. At the same time, Big Data analytics have reshaped the design and implementation of the applications that analyse the data. In this paper, we explore the use of Big Data tools for extracting value from Twitter data. We acquire a large set of Twitter data (10TB in size) and process it by relying on Spark DataFrame...
The introduction of ubiquitous systems, wearable computing and 'Internet of Things' technologies in our digital society results in a large-scale data generation. Environmental, home, and mobile sensors are only a few examples of the significant capabilities to collect massive data in real-time from a plethora of heterogeneous social environments. These capabilities provide us with a unique opportunity...
GEPETO (for GEoPrivacy-Enhancing Toolkit) is a flexible software that can be used to visualize, sanitize, perform inference attacks and measure the utility of a particular geolocated dataset. The main objective of GEPETO is to enable a data curator (e.g., a company, a governmental agency or a data protection authority) to design, tune, experiment and evaluate various sanitization algorithms and inference...
The Paxos-MIC protocol allows to solve a sequence of consensus instances in an unreliable asynchronous system. It follows the basic principles of Paxos and uses two optimizations of this protocol: a safe one, So that is always activated and a risky one, Ro. The paper focuses on the interest of Ro that has been introduced by Lamport in the Fast Paxos protocol. We study the optimization Ro in favorable...
The Consensus problem is a central paradigm of fault-tolerant distributed computing. In a purely asynchronous system, Consensus is impossible to solve in deterministic manner. However, by enriching the system with some synchrony assumptions, several solutions have been proposed in order to circumvent the impossibility result, among which the Paxos approach introduced by Lamport. The repeated use of...
We present a protocol designed to solve several consecutive consensus instances in an asynchronous distributed system prone to crash failures and message omissions. The protocol follows the Paxos approach and integrates two different optimizations to reduce the latency of learning a decision value. This protocol is adaptive as it tries to obtain the best performance gain depending on the current context...
Mobile devices are now equipped with multiple sensors and networking capabilities. They can gather information about their surrounding environment and interact both with nearby nodes, using a dynamic and self-configurable ad-hoc network, and with distant nodes via the Internet. While the concept of mobile agent is appropriate to explore the ad-hoc network and autonomously discover service providers,...
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