An extended framework of privacy-preserving computation with flexible access control

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Assignment of sensing tasks to IoT devices: Exploitation of a Social Network of Objects

The Social Internet of Things (SIoT) is a novel communication paradigm according to which the objects connected to the Internet create a dynamic social network that is mostly used to implement the following processes: route information and service requests, disseminate data, and evaluate the trust level of each member of the network. In this paper, the SIoT paradigm is applied to a scenario where geolocated sensing tasks are assigned to fixed and mobile devices, providing the following major contributions. The SIoT model is adopted to find the objects that can contribute to the application by crawling the social network through the nodes profile and trust level. A new algorithm to address the resource management issue is proposed so that sensing tasks are fairly assigned to the objects in the SIoT. To this, an energy consumption profile is created per device and task, and shared among nodes of the same category through the SIoT. The resulting solution is also implemented in the SIoT-based Lysis platform. Emulations have been performed, which showed an extension of the time needed to completely deplete the battery of the first device of more than 40% with respect to alternative approaches

Distributed Wikis: A Survey

International audienceSUMMARY "Distributed Wiki" is a generic term covering various systems, including "peer-to-peer wiki," "mobile wiki," "offline wiki," "federated wiki" and others. Distributed wikis distribute their pages among the sites of autonomous participants to address various motivations, including high availability of data, new collaboration models and different viewpoint of subjects. Although existing systems share some common basic concepts, it is often difficult to understand the specificity of each one, the underlying complexities or the best context in which to use it. In this paper, we define, classify and characterize distributed wikis. We identify three classes of distributed wiki systems, each using a different collaboration model and distribution scheme for its pages: highly available wikis, decentralized social wikis and federated wikis. We classify existing distributed wikis according to these classes. We detail their underlying complexities and social and technical motivations. We also highlight some directions for research and opportunities for new systems with original social and technical motivations

A Partition-based Mobile Crowd Sensing-enabled Task Allocation for Solar Insecticidal Lamp Internet of Things Maintenance

Solar Insecticidal Lamps Internet of Things (SIL-IoT) is a new green prevention and control technology for pest management. In the implementation of SIL-IoT to large-scale regions, two practical issues remain to be solved, i.e., i) scheduling the cleaning tasks of SILs periodically; and ii) minimizing the insecticidal efficiency reduction over time. As smartphones are widely available among farmers across the globe, Mobile Crowd Sensing (MCS) for agricultural data collection becomes a cost-effective and efficient solution by integrating participatory sensing based on a large group of individuals. This paper proposes an MCS-enabled framework to address the SIL Maintenance Problem (SILMP) and perform system analysis by considering both the partition structure of farmland and the insecticidal efficiency of SILs. In addition, considering the farmland’s practical natural geographical features, we propose dividing the regions of interest into numerous subareas, where each subarea can be considered a separate partition. Finally, we formulate the SILMP framework as two sub-problems, i.e., path planning and task selection, and propose two different methods to tackle each problem based on the concept of greedy algorithm. Simulation results show that our proposed methods have improved performance in the trade-off between task cost and insecticidal efficiency and outperform the three selected baseline algorithms

Big data y privacidad. Estudio bibliométrico

Revisión bibliográfica sobre la Privacidad de los datos personales en la actividad relacionada con el concepto “Big Data”.Universidad de Sevilla. Máster Universitario en Estudios Avanzados en Dirección de Empresa

Optimal Deployment of Solar Insecticidal Lamps over Constrained Locations in Mixed-Crop Farmlands

Solar Insecticidal Lamps (SILs) play a vital role in green prevention and control of pests. By embedding SILs in Wireless Sensor Networks (WSNs), we establish a novel agricultural Internet of Things (IoT), referred to as the SILIoTs. In practice, the deployment of SIL nodes is determined by the geographical characteristics of an actual farmland, the constraints on the locations of SIL nodes, and the radio-wave propagation in complex agricultural environment. In this paper, we mainly focus on the constrained SIL Deployment Problem (cSILDP) in a mixed-crop farmland, where the locations used to deploy SIL nodes are a limited set of candidates located on the ridges. We formulate the cSILDP in this scenario as a Connected Set Cover (CSC) problem, and propose a Hole Aware Node Deployment Method (HANDM) based on the greedy algorithm to solve the constrained optimization problem. The HANDM is a two-phase method. In the first phase, a novel deployment strategy is utilised to guarantee only a single coverage hole in each iteration, based on which a set of suboptimal locations is found for the deployment of SIL nodes. In the second phase, according to the operations of deletion and fusion, the optimal locations are obtained to meet the requirements on complete coverage and connectivity. Experimental results show that our proposed method achieves better performance than the peer algorithms, specifically in terms of deployment cost

Motivational and Affective Aspects in Technology Enhanced Learning (MATEL) : Proceedings of the MATEL Workshop 2013-2014

The main purpose and focus of the MATEL workshop series on Motivational and Affective Aspects in Technology Enhanced Learning has been to stimulate interdisci-plinary exchange and joint research activities on understanding and addressing motiva-tional factors and emotions in learning solutions. There is hardly any opposition to the importance of these factors for the success of these solutions. However, there was al-ways a major lack in systematic support and scientific rigor in the interdisciplinary field so that it was characterized through anecdotal evidence and hard-to-generalize results. In 2013 and 2014, From Art to Engineering has become the major motto of the MATEL workshop series. In this report, we bundle the 2013 and 2014 contributions that show steps on this journey