Search

Today, the number of interconnected devices and the amount of personal information gathered by them increases tremendously resulting in the need for development tools to harness its potential. New devices are continually being introduced in the daily life of people, and they are already producing an unprecedented amount of data related to people's well-being. However, taking advantage of such information to create innovative Internet of Bodies solutions heavily relies on manually gathering the needed information from several sources on services and the devices involved. In this paper, we present a novel Human Data Model - a new tool to combine personal information from several sources, perform computations over that information, and proactively schedule computer-human interactions. Developers that use the proposed model would obtain an opportunity to create the Internet of Bodies solutions using high-level abstractions of the users' personal information and taking advantage of the distributed approach of the model. acceptedVersion

The explosive growth of the mobile application market in recent years has led to a large concomitant mobile software industry whose components are, in many cases, startups and small-size software providers. The success of these applications and the firms behind them depends on a subtle balance between different dimensions mainly affected by their architectural design, such as user satisfaction, resource consumption, operating costs, and timing. The present communication describes a framework with a specific set of practices for identifying the boundaries of different architectural designs —in this article we apply it to estimate both the smartphone’s resource consumption and the operating costs in the cloud— and thus help in the architectural decision-making process. This will enable mobile software developers to predict at early stages which architectural design best suits their business model in accordance with the number of users and the expected use of the application and even provide an advance alert of when architectural choices will need to be reviewed, obviating the need for costly architectural re-design in further phases Ministerio de Ciencia, Innovación y Universidades RTI2018-094591-B-I00 Ministerio de Ciencia, Innovación y Universidades PGC2018-094905-B-I00 Junta de Andalucía APOLO (US-1264651) Ministerio de Ciencia e Innovación HORATIO (RTI2018-101204–B–C21) Ministerio de Ciencia, Innovación y Universidades RED2018-102654-T Interreg V-A España-Portugal (POCTEP) 0499-4IE-PLUS-4-E Junta de Andalucía UMA18-FEDERJA-180 Junta de Extremadura GR18112 Junta de Extremadura IB18030

Sensor/Actuator devices are currently being massively adopted, often as nodes of larger sensor networks. These sensor networks are typically dedicated to context acquisition (e.g., get temperature) as well as providing acting services (e.g., open the blinds). However, regarding their own data storage, data is usually sent to Fog/Cloud servers. Fog/Cloud storage solutions provide several advantages over sensor network storage solutions, but also some drawbacks. For instance, in Cloud environments, privacy and legal issues may appear, while in Fog, additional costly hardware must be purchased and maintained, at least a server with redundant storage or many servers when distributed data storage is required. Nowadays, sensor nodes count in thousands around us, and they have significantly increased their storage and computational capabilities over the past few years. Therefore, traditional Fog/Cloud storage solutions could be combined or even replaced by Mist/Edge storage solutions for many use cases. A principal contribution of this paper is a novel data distribution and replication storage solution for wireless sensor networks, the first to consider sensor node heterogeneity to find the optimal storage replication according to node capabilities. The solution has been carefully planned and implemented to run even in very low-end microcontrollers, that lives in many of our surrounding smart devices. Other contributions include data comparing Mist/Edge and Amazon S3 regular storage, showing that there remains plenty of room for research into Mist/Edge storage, as well as into the industry itself.

In business and system requirements analysis, the characteristics of the elements identified are perfectly documented with specific notations and in specific artifacts. However, since these notations are focused on each specific type of element, the interdependencies between elements of different kinds are usually left implicit. These relationships are particularly important during system design in order to evaluate the impact of each requirement and to select the architectural pattern that better satisfies them. To identify and make them explicit, the architect has to analyze all the artifacts generated in depth. Any misinterpretation of these relationships may lead to patterns being selected that can hinder rather than facilitate the satisfaction of the business goals and the system requirements. This paper presents a set of profiles allowing designers to explicitly model these interdependencies in BPMN 2 and UML 2 Use Case diagrams. In addition, ATL transformations are defined to automatically derive these relationships from the business specification to the requirements models, facilitating their analysis by the architect, and thus reducing the risk of misinterpretation.