Scalable and responsive real time event processing using cloud computing

PhD ThesisCloud computing provides the potential for scalability and adaptability in a cost e ective manner. However, when it comes to achieving scalability for real time applications response time cannot be high. Many applications require good performance and low response time, which need to be matched with the dynamic resource allocation. The real time processing requirements can also be characterized by unpredictable rates of incoming data streams and dynamic outbursts of data. This raises the issue of processing the data streams across multiple cloud computing nodes. This research analyzes possible methodologies to process the real time data in which applications can be structured as multiple event processing networks and be partitioned over the set of available cloud nodes. The approach is based on queuing theory principles to encompass the cloud computing. The transformation of the raw data into useful outputs occurs in various stages of processing networks which are distributed across the multiple computing nodes in a cloud. A set of valid options is created to understand the response time requirements for each application. Under a given valid set of conditions to meet the response time criteria, multiple instances of event processing networks are distributed in the cloud nodes. A generic methodology to scale-up and scale-down the event processing networks in accordance to the response time criteria is de ned. The real time applications that support sophisticated decision support mechanisms need to comply with response time criteria consisting of interdependent data ow paradigms making it harder to improve the performance. Consideration is given for ways to reduce the latency,improve response time and throughput of the real time applications by distributing the event processing networks in multiple computing nodes

Functional Programming for Embedded Systems

Embedded Systems application development has traditionally been carried out in low-level machine-oriented programming languages like C or Assembler that can result in unsafe, error-prone and difficult-to-maintain code. Functional programming with features such as higher-order functions, algebraic data types, polymorphism, strong static typing and automatic memory management appears to be an ideal candidate to address the issues with low-level languages plaguing embedded systems. However, embedded systems usually run on heavily memory-constrained devices with memory in the order of hundreds of kilobytes and applications running on such devices embody the general characteristics of being (i) I/O- bound, (ii) concurrent and (iii) timing-aware. Popular functional language compilers and runtimes either do not fare well with such scarce memory resources or do not provide high-level abstractions that address all the three listed characteristics. This work attempts to address this gap by investigating and proposing high-level abstractions specialised for I/O-bound, concurrent and timing-aware embedded-systems programs. We implement the proposed abstractions on eagerly-evaluated, statically-typed functional languages running natively on microcontrollers. Our contributions are divided into two parts - Part 1 presents a functional reactive programming language - Hailstorm - that tracks side effects like I/O in its type system using a feature called resource types. Hailstorm’s programming model is illustrated on the GRiSP microcontroller board.Part 2 comprises two papers that describe the design and implementation of Synchron, a runtime API that provides a uniform message-passing framework for the handling of software messages as well as hardware interrupts. Additionally, the Synchron API supports a novel timing operator to capture the notion of time, common in embedded applications. The Synchron API is implemented as a virtual machine - SynchronVM - that is run on the NRF52 and STM32 microcontroller boards. We present programming examples that illustrate the concurrency, I/O and timing capabilities of the VM and provide various benchmarks on the response time, memory and power usage of SynchronVM

Systematic Approaches for Telemedicine and Data Coordination for COVID-19 in Baja California, Mexico

Conference proceedings info: ICICT 2023: 2023 The 6th International Conference on Information and Computer Technologies Raleigh, HI, United States, March 24-26, 2023 Pages 529-542We provide a model for systematic implementation of telemedicine within a large evaluation center for COVID-19 in the area of Baja California, Mexico. Our model is based on human-centric design factors and cross disciplinary collaborations for scalable data-driven enablement of smartphone, cellular, and video Teleconsul-tation technologies to link hospitals, clinics, and emergency medical services for point-of-care assessments of COVID testing, and for subsequent treatment and quar-antine decisions. A multidisciplinary team was rapidly created, in cooperation with different institutions, including: the Autonomous University of Baja California, the Ministry of Health, the Command, Communication and Computer Control Center of the Ministry of the State of Baja California (C4), Colleges of Medicine, and the College of Psychologists. Our objective is to provide information to the public and to evaluate COVID-19 in real time and to track, regional, municipal, and state-wide data in real time that informs supply chains and resource allocation with the anticipation of a surge in COVID-19 cases. RESUMEN Proporcionamos un modelo para la implementación sistemática de la telemedicina dentro de un gran centro de evaluación de COVID-19 en el área de Baja California, México. Nuestro modelo se basa en factores de diseño centrados en el ser humano y colaboraciones interdisciplinarias para la habilitación escalable basada en datos de tecnologías de teleconsulta de teléfonos inteligentes, celulares y video para vincular hospitales, clínicas y servicios médicos de emergencia para evaluaciones de COVID en el punto de atención. pruebas, y para el tratamiento posterior y decisiones de cuarentena. Rápidamente se creó un equipo multidisciplinario, en cooperación con diferentes instituciones, entre ellas: la Universidad Autónoma de Baja California, la Secretaría de Salud, el Centro de Comando, Comunicaciones y Control Informático. de la Secretaría del Estado de Baja California (C4), Facultades de Medicina y Colegio de Psicólogos. Nuestro objetivo es proporcionar información al público y evaluar COVID-19 en tiempo real y rastrear datos regionales, municipales y estatales en tiempo real que informan las cadenas de suministro y la asignación de recursos con la anticipación de un aumento de COVID-19. 19 casos.ICICT 2023: 2023 The 6th International Conference on Information and Computer Technologieshttps://doi.org/10.1007/978-981-99-3236-

LIPIcs, Volume 251, ITCS 2023, Complete Volume

LIPIcs, Volume 251, ITCS 2023, Complete Volum