Browsing by Author "Silva, Lucas Henrique Moreira"

Now showing 1 - 2 of 2
  • No Thumbnail Available
    Item
    A general-purpose distributed computing Java middleware.
    (2019) Almeida, André Luís Barroso de; Cimino, Leonardo de Souza; Resende, José Estevão Eugênio de; Silva, Lucas Henrique Moreira; Rocha, Samuel Queiroz Souza; Gregorio, Guilherme Aparecido; Paiva, Gustavo Silva; Silva, Saul Emanuel Delabrida; Santos, Haroldo Gambini; Carvalho, Marco Antonio Moreira de; Aquino, André Luiz Lins de; Lima, Joubert de Castro
    The middleware solutions for General‐Purpose Distributed Computing (GPDC) have distinct requirements, such as task scheduling, processing/storage fault tolerance, code portability for parallel or distributed environments, simple deployment (including over grid or multi‐cluster environments), collaborative development, low code refactoring, native support for distributed data structures, asynchronous task execution, and support for distributed global variables. These solutions do not integrate these requirements into a single deployment with a unique API exposing most of these requirements to users. The consequence is the utilization of several solutions with their particularities, thus requiring different user skills. Besides that, the users have to solve the integration and all heterogeneity issues. To reduce this integration gap, in this paper, we present Java Cá&Lá (JCL), a distributed‐shared‐memory and task‐oriented lightweight middleware for the Java community that separates business logic from distribution issues during the development process and incorporates several requirements that were presented separately in the GPDC middleware literature over the last few decades. JCL allows building distributed or parallel applications with only a few portable API calls, thus reducing the integration problems. Finally, it also runs on different platforms, including small single‐board computers. This work compares and contrasts JCL with other Java middleware systems and reports experimental evaluations of JCL applications in several distinct scenarios.
  • No Thumbnail Available
    Item
    A middleware solution for integrating and exploring IoTand HPC capabilities.
    (2019) Cimino, Leonardo de Souza; Resende, José Estevão Eugênio de; Silva, Lucas Henrique Moreira; Rocha, Samuel Queiroz Souza; Correia, Matheus de Oliveira; Monteiro, Guilherme Souza; Fernandes, Gabriel Natã de Souza; Moreira, Renan da Silva; Silva, Junior Guilherme da; Santos, Matheus Inácio Batista; Aquino, André Luiz Lins de; Almeida, André Luís Barroso de; Lima, Joubert de Castro
    Even with the considerable advances in the development of middleware solutions, there is still a substantial gap in Internet of Things (IoT) and high‐performance computing (HPC) integration. It is not possible to expose services such as processing, storage, sensing, security, context awareness, and actuating in a unified manner with the existing middleware solutions. The consequence is the utilization of several solutions with their particularities, thus requiring different skills. Besides that, the users have to solve the integration and all heterogeneity issues. To reduce the gap between IoT and HPC technologies, we present the JavaCá&Lá (JCL), a middleware used to help the implementation of distributed user‐applications classified as IoT‐HPC. This ubiquity is possible because JCL incorporates (1) a single application programming interface to program different device categories; (2) the support for different programming models; (3) the interoperability of sensing, processing, storage, and actuating services; (4) the integration with MQTT technology; and (5) security, context awareness, and actions services introduced through JCL application programming interface. Experimental evaluations demonstrated that JCL scales when doing the IoT‐HPC services. Additionally, we identify that customized JCL deployments become an alternative when Java‐Android and vice‐versa code conversion is necessary. The MQTT brokers usually are faster than JCL HashMap sensing storage, but they do not perform distributed, so they cannot handle a huge amount of sensing data. Finally, a short example for monitoring moving objects exemplifies JCL facilities for IoT‐HPC development.