Navegando por Autor "Paiva, Gustavo Silva"
Agora exibindo 1 - 2 de 2
Resultados por página
Opções de Ordenação
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 CastroThe 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.Item Improved heuristic algorithms for the job sequencing and tool switching problem.(2017) Paiva, Gustavo Silva; Carvalho, Marco Antonio Moreira deIn flexible manufacturing systems, a single machine can be configured with different tools for process- ing different jobs, each requiring a specific set of tools. There is a limit to the maximum number of tools that can be loaded simultaneously in the machine; between the processing of two different jobs, it may be necessary to switch these tools, causing interruptions in the production line. The Job Sequenc- ing and Tool Switching Problem (SSP) aims to determine a job sequence and the tool-loading order for a flexible machine, in order to minimize the number of tool switches. These two tasks can be separated into Sequencing , an N P -hard problem, and Tooling , which is a Pproblem if the job sequence is given. This paper proposes a methodology that uses graph representations, heuristic methods, and local search methods to solve the sequencing problem. These contributions are combined in an Iterated Local Search scheme, which is then combined with a classical tooling method, in order to solve the SSP. Comprehen- sive computational experiments show that the resulting method is competitive and can establish new best solutions for literature instances, while outperforming the current state-of-the-art method.