Distributed computational model for shared processing on Cyber-Physical System environments

Cyber-Physical Systems typically consist of a combination of mobile devices, embedded systems and computers to monitor, sense, and actuate with the surrounding real world. These computing elements are usually wireless, interconnected to share data and interact with each other, with the server part and also with cloud computing services. In such a heterogeneous environment, new applications arise to meet ever-increasing needs and these are an important challenge to the processing capabilities of devices. For example, automatic driving systems, manufacturing environments, smart city management, etc. To meet the requirements of said application contexts, the system can create computing processes to distribute the workload over the network and/or a cloud computing server. Multiple options arise in relation to what network nodes should support the execution of the processes. This paper focuses on this problem by introducing a distributed computational model to dynamically share these tasks among the computing nodes and considering the inherent variability of the context in these environments. Our novel approach promotes the integration of the computing resources, with externally supplied cloud services, to fulfill modern application requirements. A prototype implementation for the proposed model has been built and an application example has been designed to validate the proposal in a real working environment

Uma proposta para o uso de progressive web apps em ambientes de computação móvel em nuvens

The increased use of mobile applications is directly associated with the constant development of Mobile Computing (CM), such as smartphones, tablets and notebooks. However, the use of applications on these devices turns out to be a problem for their processing limitations, RAM, storage, network connection and especially battery. To mitigate these limitations, an area known as Mobile Cloud Computing (MCC) has presented some alternatives. One of these is Computing Offloading, which consists of sending all or part of the execution of processes or tasks from the mobile device to a remote computing resource with higher processing power. However, the efficiency of this discharge from running in MCC environment can be directly related to the type of application used by the mobile device. Therefore, the objective of this work is to propose a methodology for the use of Progressive Web Applications or Progressive Web Apps (PWA) to offload tasks in Mobile Cloud Computing. Based on the proposed methodology, two case studies involving face detection and Fibonacci sequence calculation were developed. These case studies were evaluated by performing different workloads using the PWA application on different mobile devices and offloading in Docker containers using the 3G, 4G and WiFi networks. The results of the evaluation were obtained from the task execution time metric, noting that in some cases local execution of these tasks is better than cloud execution; while in others, cloud is a better processing option. The developed PWA application was further analyzed using the LightHouse PWA inspection tool, obtaining a maximum score of 100 for the application performance.O aumento no uso de aplicações móveis está diretamente associado ao desenvolvimento constante da Computação Móvel (CM), a exemplo dos smartphones, tablets e notebooks. No entanto, o uso de aplicações nesses dispositivos acaba sendo um problema para suas limitações de processamento, memória RAM, armazenamento, conexão de rede e, principalmente, bateria. Para mitigar essas limitações, uma área conhecida como Computação Móvel em Nuvem ou Mobile Cloud Computing – MCC tem apresentado algumas alternativas. Uma delas está na descarga computacional ou Computing Offloading, que consiste em fazer o envio completo ou parcial da execução de processos ou tarefas do dispositivo móvel para um recurso computacional remoto com maior poder de processamento. No entanto, a eficiência dessa descarga da execução em ambiente MCC pode ter relação direta com o tipo de aplicação utilizada pelo dispositivo móvel. Diante disso, o objetivo deste trabalho consiste em propor uma metodologia para o uso de Aplicações Web Progressivas ou Progressive Web Apps (PWA) para fazer o offloading de tarefas na Computação Móvel em Nuvem. A partir da metodologia proposta, foram desenvolvidos dois estudos de caso, envolvendo a detecção de faces e o cálculo da sequência Fibonacci. A avaliação desses estudos de caso foi feita através da execução de diferentes cargas de trabalho, usando a aplicação PWA em diferentes dispositivos móveis e através do offloading em containers Docker, utilizando as redes 3G, 4G e WiFi. Os resultados da avaliação foram obtidos a partir da métrica de tempo de execução das tarefas, observando-se que, em alguns casos, a execução local dessas tarefas é melhor que a execução na nuvem; enquanto em outros, a nuvem é uma melhor opção de processamento. A aplicação PWA desenvolvida ainda foi analisada utilizando a ferramenta de inspeção de PWA LightHouse, obtendo a nota máxima de 100 para o quesito performance da aplicação