Is Blockchain for Internet of Medical Things a Panacea for COVID-19 Pandemic?

The outbreak of the COVID-19 pandemic has deeply influenced the lifestyle of the general public and the healthcare system of the society. As a promising approach to address the emerging challenges caused by the epidemic of infectious diseases like COVID-19, Internet of Medical Things (IoMT) deployed in hospitals, clinics, and healthcare centers can save the diagnosis time and improve the efficiency of medical resources though privacy and security concerns of IoMT stall the wide adoption. In order to tackle the privacy, security, and interoperability issues of IoMT, we propose a framework of blockchain-enabled IoMT by introducing blockchain to incumbent IoMT systems. In this paper, we review the benefits of this architecture and illustrate the opportunities brought by blockchain-enabled IoMT. We also provide use cases of blockchain-enabled IoMT on fighting against the COVID-19 pandemic, including the prevention of infectious diseases, location sharing and contact tracing, and the supply chain of injectable medicines. We also outline future work in this area.Comment: 15 pages, 8 figure

In-network data acquisition and replication in mobile sensor networks

This paper assumes a set of n mobile sensors that move in the Euclidean plane as a swarm. Our objectives are to explore a given geographic region by detecting and aggregating spatio-temporal events of interest and to store these events in the network until the user requests them. Such a setting finds applications in mobile environments where the user (i.e., the sink) is infrequently within communication range from the field deployment. Our framework, coined SenseSwarm, dynamically partitions the sensing devices into perimeter and core nodes. Data acquisition is scheduled at the perimeter, in order to minimize energy consumption, while storage and replication takes place at the core nodes which are physically and logically shielded to threats and obstacles. To efficiently identify the nodes laying on the perimeter of the swarm we devise the Perimeter Algorithm (PA), an efficient distributed algorithm with a low communication complexity. For storage and fault-tolerance we devise the Data Replication Algorithm (DRA), a voting-based replication scheme that enables the exact retrieval of values from the network in cases of failures. We also extend DRA with a spatio-temporal in-network aggregation scheme based on minimum bounding rectangles to form the Hierarchical-DRA (HDRA) algorithm, which enables the approximate retrieval of events from the network. Our trace-driven experimentation shows that our framework can offer significant energy reductions while maintaining high data availability rates. In particular, we found that when failures across all nodes are less than 60%, our framework can recover over 80% of detected values exactly

Mobile computing algorithms and systems for user-aware optimization of enterprise applications

The adoption of mobile devices, particularly smartphones, has grown steadily over the last decade, also permeating the enterprise sector. Enterprises are investing heavily in mobilization to improve employee productivity and perform business workflows, including smartphones and tablets. Enterprise mobility is expected to be more than a $250 billion market in 2019. Strategies to achieve mobilization range from building native apps, using mobile enterprise application platforms (MEAPS), developing with a mobile backend as a service (mBaaS), relying on application virtualization, and employing application refactoring. Enterprises are not yet experiencing the many benefits of mobilization, even though there is great promise. Email and browsing are used heavily, but the practical adoption of enterprise mobility to deliver value beyond these applications is in its infancy and faces barriers. Enterprises deploy few business workflows (<5 percent). Barriers include the heavy task burden in executing workflows on mobile devices, the irrelevance of available mobile features, non-availability of necessary business functions, the high cost of network access, increased security risks associated with smartphones, and increased complexity of mobile application development. This dissertation identifies key barriers to user productivity on smartphones and investigates user-aware solutions that leverage redundancies in user behavior to reduce burden, focusing on the following mobility aspects: (1) Workflow Mobilization: For an employee to successfully perform workflows on a smartphone, a mobile app must be available, and the specific workflow must survive the defeaturization process necessary for mobilization. While typical mobilization strategies offer mobile access to a few heavily-used features, there is a long-tail problem for enterprise application mobilization, in that many application features are left unsupported or are too difficult to access. We propose a do-it-yourself (DIY) platform, Taskr, that allows users at all skill levels to mobilize workflows. Taskr uses remote computing with application refactoring to achieve code-less mobilization of enterprise web applications. It allows for flexible mobile delivery so that users can execute spot tasks through Twitter, email, or a native mobile app. Taskr prototypes from 15 enterprise applications reduce the number of user actions performing workflows by 40 percent compared to the desktop; (2) Content sharing (enterprise email): An enterprise employee spends an inordinate amount of time on email responding to queries and sharing information with co-workers. This problem is further aggravated on smartphones due to smaller screen real estate. We consider automated information suggestions to ease the burden of reply construction on smartphones. The premise is that a significant portion of the information content in a reply is likely present in prior emails. We first motivate this premise by analyzing both public and private email datasets. We then present Dejavu, a system that relies on inverse document frequency (IDF) and keyword matching to provide relevant suggestions for responses. Evaluation of Dejavu over email datasets shows a 22 percent reduction in the user’s typing burden; (3) Collaboration: Even though many business processes within enterprises require employees to work as a team and collaborate, few mobile apps allow two employees to work on an object from two separate devices simultaneously. We present Peek, a mobile-to-mobile remote computing protocol for collaboration that lets users remotely interact with an application in a responsive manner. Unlike traditional desktop remote computing protocols, Peek provides multi-touch support for ease of operation and a flexible frame compression scheme that accounts for the resource constraints of a smartphone. An Android prototype of Peek shows a 62 percent reduction in time to perform touchscreen actions.Ph.D

Functional requirements document for the Earth Observing System Data and Information System (EOSDIS) Scientific Computing Facilities (SCF) of the NASA/MSFC Earth Science and Applications Division, 1992

Five scientists at MSFC/ESAD have EOS SCF investigator status. Each SCF has unique tasks which require the establishment of a computing facility dedicated to accomplishing those tasks. A SCF Working Group was established at ESAD with the charter of defining the computing requirements of the individual SCFs and recommending options for meeting these requirements. The primary goal of the working group was to determine which computing needs can be satisfied using either shared resources or separate but compatible resources, and which needs require unique individual resources. The requirements investigated included CPU-intensive vector and scalar processing, visualization, data storage, connectivity, and I/O peripherals. A review of computer industry directions and a market survey of computing hardware provided information regarding important industry standards and candidate computing platforms. It was determined that the total SCF computing requirements might be most effectively met using a hierarchy consisting of shared and individual resources. This hierarchy is composed of five major system types: (1) a supercomputer class vector processor; (2) a high-end scalar multiprocessor workstation; (3) a file server; (4) a few medium- to high-end visualization workstations; and (5) several low- to medium-range personal graphics workstations. Specific recommendations for meeting the needs of each of these types are presented

A unified platform for experimental and computational biology

PhD ThesisIn natural sciences, the correct engineering of a system’s chemical, biological and physical properties may allow it to sustain life. Bioengineering cells is probably one of the most complex challenges of biological research; yet, the little we do know about the nature of life is sufficient to guide scientific research, and to explore the elements beyond the apparent simple proliferation of living cells. Although Mendel first characterised the concept of genetic heredity over 150 years ago, we only recently became able to perform tailored genetic modification of living organisms. The development of digital technologies, in particular, has positively influenced the quality and reproducibility of experimental results emerging from biological assays. However, the use of any equipment may require the need for a specific expertise in order to perform a given experimental procedure. Therefore, multidisciplinary research can bring benefits to all fields of science by helping the development of analytical methods that cross the boundaries of individual disciplines. This emerges as a systematic view of scientific problems, and relies on the adequation and integration of results from different research areas. Nevertheless, there is a complex interface between hard sciences that often creates a gap between experimental and theoretical models. In this thesis, we explored synthetic biology approaches and created a unified platform to fill this gap. We propose the first barcoding platform (Bac2code) that allows the identification and the tracking of bacterial strains. In order to facilitate communication between researchers, we developed a barcode system in DNA that physically links bacteria to their genetic description. We designed DNA barcodes as bioorthogonal elements, elaborated a universal cloning strategy to integrate these sequences in Gram-negative and Gram-positive bacteria, and demonstrated their stability over time. Through a generic protocol, any barcoded strain can later be identified via a single sequencing read. With the engineering of a synthetic circuit library, we built a biorepository of genetic constructs for our barcoding platform. These biological devices were optimised based on the closest achievable interface between experimental biology and viii computational results. Following their characterisation, and in the context of intercellular communication, we studied the behaviour of small cohorts of bioengineered cells at the microscale in microfluidics. We pushed the biological and physical boundaries of engineering techniques to the maximum, in order to observe physiological changes between bacteria separated by distances down to 20µm. However, we also showed that we reached a technological barrier, where even the use of nanoscale features was found insufficient to maintain cells isolated under high cellular density. Yet, microfluidics remains a remarkable technology, and we propose the expansion of barcoding methods to automated systems, which would allow serial barcode integration and documentation retrieval at any one time. Here, we developed and tested a barcoding method to ensure the cohesion of experimental and computational biology resources. We demonstrated its use by the in vitro assembly and the in vivo or in silico characterisation of a series of genetic circuits via different techniques. The research output of this thesis is realised as a step forward in interdisciplinary studies, and is now being adapted to reach a larger community of users as a startup companyEngineering and Physical Sciences Research Council and Newcastle University’s School of Computing Science

Creation and maintenance of visual incremental maps and hierarchical localization.

Over the last few years, the presence of the mobile robotics has considerably increased in a wide variety of environments. It is common to find robots that carry out repetitive and specific applications and also, they can be used for working at dangerous environments and to perform precise tasks. These robots can be found in a variety of social environments, such as industry, household, educational and health scenarios. For that reason, they need a specific and continuous research and improvement work. Specifically, autonomous mobile robots require a very precise technology to perform tasks without human assistance. To perform tasks autonomously, the robots must be able to navigate in an unknown environment. For that reason, the autonomous mobile robots must be able to address the mapping and localization tasks: they must create a model of the environment and estimate their position and orientation. This PhD thesis proposes and analyses different methods to carry out the map creation and the localization tasks in indoor environments. To address these tasks only visual information is used, specifically, omnidirectional images, with a 360º field of view. Throughout the chapters of this document solutions for autonomous navigation tasks are proposed, they are solved using transformations in the images captured by a vision system mounted on the robot. Firstly, the thesis focuses on the study of the global appearance descriptors in the localization task. The global appearance descriptors are algorithms that transform an image globally, into a unique vector. In these works, a deep comparative study is performed. In the experiments different global appearance descriptors are used along with omnidirectional images and the results are compared. The main goal is to obtain an optimized algorithm to estimate the robot position and orientation in real indoor environments. The experiments take place with real conditions, so some visual changes in the scenes can occur, such as camera defects, furniture or people movements and changes in the lighting conditions. The computational cost is also studied; the idea is that the robot has to localize the robot in an accurate mode, but also, it has to be fast enought. Additionally, a second application, whose goal is to carry out an incremental mapping in indoor environments, is presented. This application uses the best global appearance descriptors used in the localization task, but this time they are constructed with the purpose of solving the mapping problem using an incremental clustering technique. The application clusters a batch of images that are visually similar; every group of images or cluster is expected to identify a zone of the environment. The shape and size of the cluster can vary while the robot is visiting the different rooms. Nowadays. different algorithms can be used to obtain the clusters, but all these solutions usually work properly when they work ‘offline’, starting from the whole set of data to cluster. The main idea of this study is to obtain the map incrementally while the robot explores the new environment. Carrying out the mapping incrementally while the robot is still visiting the area is very interesting since having the map separated into nodes with relationships of similitude between them can be used subsequently for the hierarchical localization tasks, and also, to recognize environments already visited in the model. Finally, this PhD thesis includes an analysis of deep learning techniques for localization tasks. Particularly, siamese networks have been studied. Siamese networks are based on classic convolutional networks, but they permit evaluating two images simultaneously. These networks output a similarity value between the input images, and that information can be used for the localization tasks. Throughout this work the technique is presented, the possible architectures are analysed and the results after the experiments are shown and compared. Using the siamese networks, the localization in real operation conditions and environments is solved, focusing on improving the performance against illumination changes on the scene. During the experiments the room retrieval problem, the hierarchical localization and the absolute localization have been solved.Durante los últimos años, la presencia de la robótica móvil ha aumentado substancialmente en una gran variedad de entornos y escenarios. Es habitual encontrar el uso de robots para llevar a cabo aplicaciones repetitivas y específicas, así como tareas en entornos peligrosos o con resultados que deben ser muy precisos. Dichos robots se pueden encontrar tanto en ámbitos industriales como en familiares, educativos y de salud; por ello, requieren un trabajo específico y continuo de investigación y mejora. En concreto, los robots móviles autónomos requieren de una tecnología precisa para desarrollar tareas sin ayuda del ser humano. Para realizar tareas de manera autónoma, los robots deben ser capaces de navegar por un entorno ‘a priori’ desconocido. Por tanto, los robots móviles autónomos deben ser capaces de realizar la tarea de creación de mapas, creando un modelo del entorno y la tarea de localización, esto es estimar su posición y orientación. La presente tesis plantea un diseño y análisis de diferentes métodos para realizar las tareas de creación de mapas y localización en entornos de interior. Para estas tareas se emplea únicamente información visual, en concreto, imágenes omnidireccionales, con un campo de visión de 360º. En los capítulos de este trabajo se plantean soluciones a las tareas de navegación autónoma del robot mediante transformaciones en las imágenes que este es capaz de captar. En cuanto a los trabajos realizados, en primer lugar, se presenta un estudio de descriptores de apariencia global en tareas de localización. Los descriptores de apariencia global son transformaciones capaces de obtener un único vector que describa globalmente una imagen. En este trabajo se realiza un estudio exhaustivo de diferentes métodos de apariencia global adaptando su uso a imágenes omnidireccionales. Se trata de obtener un algoritmo optimizado para estimar la posición y orientación del robot en entornos reales de oficina, donde puede surgir cambios visuales en el entorno como movimientos de cámara, de mobiliario o de iluminación en la escena. También se evalúa el tiempo empleado para realizar esta estimación, ya que el trabajo de un robot debe ser preciso, pero también factible en cuanto a tiempos de computación. Además, se presenta una segunda aplicación donde el estudio se centra en la creación de mapas de entornos de interior de manera incremental. Esta aplicación hace uso de los descriptores de apariencia global estudiados para la tarea de localización, pero en este caso se utilizan para la construcción de mapas utilizando la técnica de ‘clustering’ incremental. En esta aplicación, conjuntos de imágenes visualmente similares se agrupan en un único grupo. La forma y cantidad de grupos es variable conforme el robot avanza en el entorno. Actualmente, existen diferentes algoritmos para obtener la separación de un entorno en nodos, pero las soluciones efectivas se realizan de manera ‘off-line’, es decir, a posteriori una vez se tienen todas las imágenes captadas. El trabajo presentado permite realizar esta tarea de manera incremental mientras el robot explora el nuevo entorno. Realizar esta tarea mientras se visita el resto del entorno puede ser muy interesante ya que tener el mapa separado por nodos con relaciones de proximidad entre ellos se puede ir utilizando para tareas de localización jerárquica. Además, es posible reconocer entornos ya visitados o similares a nodos pasados. Por último, la tesis también incluye el estudio de técnicas de aprendizaje profundo (‘deep learning’) para tareas de localización. En concreto, se estudia el uso de las redes siamesas, una técnica poco explorada en robótica móvil, que está basada en las clásicas redes convolucionales, pero en la que dos imágenes son evaluadas al mismo tiempo. Estas redes dan un valor de similitud entre el par de imágenes de entrada, lo que permite realizar tareas de localización visual. En este trabajo se expone esta técnica, se presentan las estructuras que pueden tener estas redes y los resultados tras la experimentación. Se evalúa la tarea de localización en entornos heterogéneos en los que el principal problema viene dado por cambios en la iluminación de la escena. Con las redes siamesas se trata de resolver el problema de estimación de estancia, el problema de localización jerárquica y el de localización absoluta

It's about THYME: On the design and implementation of a time-aware reactive storage system for pervasive edge computing environments

This work was partially supported by Fundacao para a Ciencia e a Tecnologia (FCT-MCTES) through project DeDuCe (PTDC/CCI-COM/32166/2017), NOVA LINCS UIDB/04516/2020, and grant SFRH/BD/99486/2014; and by the European Union through project LightKone (grant agreement n. 732505).Nowadays, smart mobile devices generate huge amounts of data in all sorts of gatherings. Much of that data has localized and ephemeral interest, but can be of great use if shared among co-located devices. However, mobile devices often experience poor connectivity, leading to availability issues if application storage and logic are fully delegated to a remote cloud infrastructure. In turn, the edge computing paradigm pushes computations and storage beyond the data center, closer to end-user devices where data is generated and consumed, enabling the execution of certain components of edge-enabled systems directly and cooperatively on edge devices. In this article, we address the challenge of supporting reliable and efficient data storage and dissemination among co-located wireless mobile devices without resorting to centralized services or network infrastructures. We propose THYME, a novel time-aware reactive data storage system for pervasive edge computing environments, that exploits synergies between the storage substrate and the publish/subscribe paradigm. We present the design of THYME and elaborate a three-fold evaluation, through an analytical study, and both simulation and real world experimentations, characterizing the scenarios best suited for its use. The evaluation shows that THYME allows the notification and retrieval of relevant data with low overhead and latency, and also with low energy consumption, proving to be a practical solution in a variety of situations.publishersversionpublishe