Internet of Things for Mental Health: Open Issues in Data Acquisition, Self-Organization, Service Level Agreement, and Identity Management

The increase of mental illness cases around the world can be described as an urgent and serious global health threat. Around 500 million people suffer from mental disorders, among which depression, schizophrenia, and dementia are the most prevalent. Revolutionary technological paradigms such as the Internet of Things (IoT) provide us with new capabilities to detect, assess, and care for patients early. This paper comprehensively survey works done at the intersection between IoT and mental health disorders. We evaluate multiple computational platforms, methods and devices, as well as study results and potential open issues for the effective use of IoT systems in mental health. We particularly elaborate on relevant open challenges in the use of existing IoT solutions for mental health care, which can be relevant given the potential impairments in some mental health patients such as data acquisition issues, lack of self-organization of devices and service level agreement, and security, privacy and consent issues, among others. We aim at opening the conversation for future research in this rather emerging area by outlining possible new paths based on the results and conclusions of this work.Consejo Nacional de Ciencia y Tecnologia (CONACyT)Sonora Institute of Technology (ITSON) via the PROFAPI program PROFAPI_2020_0055Spanish Ministry of Science, Innovation and Universities (MICINN) project "Advanced Computing Architectures and Machine Learning-Based Solutions for Complex Problems in Bioinformatics, Biotechnology and Biomedicine" RTI2018-101674-B-I0

A Collective Adaptive Approach to Decentralised k-Coverage in Multi-robot Systems

We focus on the online multi-object k-coverage problem (OMOkC), where mobile robots are required to sense a mobile target from k diverse points of view, coordinating themselves in a scalable and possibly decentralised way. There is active research on OMOkC, particularly in the design of decentralised algorithms for solving it. We propose a new take on the issue: Rather than classically developing new algorithms, we apply a macro-level paradigm, called aggregate computing, specifically designed to directly program the global behaviour of a whole ensemble of devices at once. To understand the potential of the application of aggregate computing to OMOkC, we extend the Alchemist simulator (supporting aggregate computing natively) with a novel toolchain component supporting the simulation of mobile robots. This way, we build a software engineering toolchain comprising language and simulation tooling for addressing OMOkC. Finally, we exercise our approach and related toolchain by introducing new algorithms for OMOkC; we show that they can be expressed concisely, reuse existing software components and perform better than the current state-of-the-art in terms of coverage over time and number of objects covered overall

Cyber resilience and incident response in smart cities: A systematic literature review

© 2020 The Authors. Published by MDPI. This is an open access article available under a Creative Commons licence. The published version can be accessed at the following link on the publisher’s website: https://doi.org/10.3390/smartcities3030046The world is experiencing a rapid growth of smart cities accelerated by Industry 4.0, including the Internet of Things (IoT), and enhanced by the application of emerging innovative technologies which in turn create highly fragile and complex cyber–physical–natural ecosystems. This paper systematically identifies peer-reviewed literature and explicitly investigates empirical primary studies that address cyber resilience and digital forensic incident response (DFIR) aspects of cyber–physical systems (CPSs) in smart cities. Our findings show that CPSs addressing cyber resilience and support for modern DFIR are a recent paradigm. Most of the primary studies are focused on a subset of the incident response process, the “detection and analysis” phase whilst attempts to address other parts of the DFIR process remain limited. Further analysis shows that research focused on smart healthcare and smart citizen were addressed only by a small number of primary studies. Additionally, our findings identify a lack of available real CPS-generated datasets limiting the experiments to mostly testbed type environments or in some cases authors relied on simulation software. Therefore, contributing this systematic literature review (SLR), we used a search protocol providing an evidence-based summary of the key themes and main focus domains investigating cyber resilience and DFIR addressed by CPS frameworks and systems. This SLR also provides scientific evidence of the gaps in the literature for possible future directions for research within the CPS cybersecurity realm. In total, 600 papers were surveyed from which 52 primary studies were included and analysed.Published onlin

Computation Against a Neighbour: Addressing Large-Scale Distribution and Adaptivity with Functional Programming and Scala

Recent works in contexts like the Internet of Things (IoT) and large-scale Cyber-Physical Systems (CPS) propose the idea of programming distributed systems by focussing on their global behaviour across space and time. In this view, a potentially vast and heterogeneous set of devices is considered as an “aggregate” to be programmed as a whole, while abstracting away the details of individual behaviour and exchange of messages, which are expressed declaratively. One such a paradigm, known as aggregate programming, builds on computational models inspired by field-based coordination. Existing models such as the field calculus capture interaction with neighbours by a so-called “neighbouring field” (a map from neighbours to values). This requires ad-hoc mechanisms to smoothly compose with standard values, thus complicating programming and introducing clutter in aggregate programs, libraries and domain-specific languages (DSLs). To address this key issue we introduce the novel notion of “computation against a neighbour”, whereby the evaluation of certain subexpressions of the aggregate program are affected by recent corresponding evaluations in neighbours. We capture this notion in the neighbours calculus (NC), a new field calculus variant which is shown to smoothly support declarative specification of interaction with neighbours, and correspondingly facilitate the embedding of field computations as internal DSLs in common general-purpose programming languages—as exemplified by a Scala implementation, called ScaFi. This paper formalises NC, thoroughly compares it with respect to the classic field calculus, and shows its expressiveness by means of a case study in edge computing, developed in ScaFi

Gestão de micro-serviços na Cloud e Edge

O aumento do número de dispositivos móveis nos últimos anos tem elevado o número de pedidos realizados aos serviços de backend da cloud, bem como a quantidade de dados produzida. Este facto tem levado à utilização de novas arquiteturas no desenvolvimento dos sistemas e à necessidade de novas estratégias para garantir a qualidade dos serviços. A arquitetura de micro-serviços, na linha de “Service Oriented Architecture and Computing” (SOA/SOC), permite o desenvolvimento independente de pequenos serviços, cada um implementando uma dada funcionalidade, com uma interface bem definida e acessível através da rede. Serviços com funcionalidades mais complexas resultam da comunicação entre os micro-serviços, em que cada um recorre aos serviços de outros. Esta arquitetura permite o deployment independente de cada serviço com configuração individual dos recursos (ex.: CPU, RAM), bem como o seu escalonamento independente (múltiplas instâncias por serviço). O tamanho reduzido de cada serviço permite também o seu deployment em arquiteturas heterogéneas de computação, como a cloud e a edge. A heterogeneidade dos locais de deployment considerados, ou seja, a cloud e a edge, torna complexa a gestão dos micro-serviços, em particular a migração/replicação dos serviços. É necessário decidir quando se processa a migração/replicação de um dado serviço, e para que local, sendo depois também necessário decidir como se processa essa migração/ replicação. Ao existirem vários micro-serviços, em que pode haver dependências entre eles, a sua gestão é mais complexa, bem como a decisão sobre as suas dependências. A solução consiste num protótipo aplicacional com mecanismos automáticos de migração e replicação de micro-serviços na cloud e na edge, que permite uma diminuição no tempo de acesso a esses serviços, resultando num melhor desempenho aplicacional. Estes mecanismos possibilitam o deployment de micro-serviços automaticamente na cloud e edge consoante certas regras e métricas configuráveis (ex.: latência, número de acessos). A avaliação realizada permitiu comprovar que a utilização da cloud e da edge para a execução dos serviços permitiu uma diminuição dos tempos de acessos aos mesmos, em comparação à utilização apenas da cloud