5 resultados para Memory Management (Computer science)
em Repositório Institucional da Universidade Tecnológica Federal do Paraná (RIUT)
Resumo:
The growing demand for large-scale virtualization environments, such as the ones used in cloud computing, has led to a need for efficient management of computing resources. RAM memory is the one of the most required resources in these environments, and is usually the main factor limiting the number of virtual machines that can run on the physical host. Recently, hypervisors have brought mechanisms for transparent memory sharing between virtual machines in order to reduce the total demand for system memory. These mechanisms “merge” similar pages detected in multiple virtual machines into the same physical memory, using a copy-on-write mechanism in a manner that is transparent to the guest systems. The objective of this study is to present an overview of these mechanisms and also evaluate their performance and effectiveness. The results of two popular hypervisors (VMware and KVM) using different guest operating systems (Linux and Windows) and different workloads (synthetic and real) are presented herein. The results show significant performance differences between hypervisors according to the guest system workloads and execution time.
Resumo:
This work presents a study about a the Baars-Franklin architecture, which defines a model of computational consciousness, and use it in a mobile robot navigation task. The insertion of mobile robots in dynamic environments carries a high complexity in navigation tasks, in order to deal with the constant environment changes, it is essential that the robot can adapt to this dynamism. The approach utilized in this work is to make the execution of these tasks closer to how human beings react to the same conditions by means of a model of computational consci-ousness. The LIDA architecture (Learning Intelligent Distribution Agent) is a cognitive system that seeks tomodel some of the human cognitive aspects, from low-level perceptions to decision making, as well as attention mechanism and episodic memory. In the present work, a computa-tional implementation of the LIDA architecture was evaluated by means of a case study, aiming to evaluate the capabilities of a cognitive approach to navigation of a mobile robot in dynamic and unknown environments, using experiments both with virtual environments (simulation) and a real robot in a realistic environment. This study concluded that it is possible to obtain benefits by using conscious cognitive models in mobile robot navigation tasks, presenting the positive and negative aspects of this approach.
Resumo:
Abstract – Background – The software effort estimation research area aims to improve the accuracy of this estimation in software projects and activities. Aims – This study describes the development and usage of a web application tocollect data generated from the Planning Poker estimation process and the analysis of the collected data to investigate the impact of revising previous estimates when conducting similar estimates in a Planning Poker context. Method – Software activities were estimated by Universidade Tecnológica Federal do Paraná (UTFPR) computer students, using Planning Poker, with and without revising previous similar activities, storing data regarding the decision-making process. And the collected data was used to investigate the impact that revising similar executed activities have in the software effort estimates' accuracy.Obtained Results – The UTFPR computer students were divided into 14 groups. Eight of them showed accuracy increase in more than half of their estimates. Three of them had almost the same accuracy in more than half of their estimates. And only three of them had loss of accuracy in more than half of their estimates. Conclusion – Reviewing the similar executed software activities, when using Planning Poker, led to more accurate software estimates in most cases, and, because of that, can improve the software development process.
Resumo:
Social networks rely on concepts such as collaboration, cooperation, replication, flow, speed, interaction, engagement, and aim the continuous sharing and resharing of information in support of the permanent social interaction. Facebook, the largest social network in the world, reached, in May 2016, the mark of 1.09 billion active users daily, draining 161.7 million hours of users’ attention to the website every day. These users share 4.75 billion units of content daily. The research presented in this dissertation aims to investigate the management of knowledge and collective intelligence, from the introduction of mechanisms that aim to enable users to manage and organize current information in the feeds from Facebook groups in which they participate, turning Facebook into a collective knowledge and information management device that goes far beyond mere interaction and communication among people. The adoption of Design Science Research methodology is intended to instill the "genes" of collective intelligence, as presented in the literature, in the computational artifact being developed, so that intelligence can be managed and used to create even more knowledge and intelligence to and by the group. The main theoretical contribution of this dissertation is to discuss knowledge management and collective intelligence in a complementary and integrated manner, showing how efforts to obtain one also contribute to leveraging the other.
Resumo:
This document presents GEmSysC, an unified cryptographic API for embedded systems. Software layers implementing this API can be built over existing libraries, allowing embedded software to access cryptographic functions in a consistent way that does not depend on the underlying library. The API complies to good practices for API design and good practices for embedded software development and took its inspiration from other cryptographic libraries and standards. The main inspiration for creating GEmSysC was the CMSIS-RTOS standard, which defines an unified API for embedded software in an implementation-independent way, but targets operating systems instead of cryptographic functions. GEmSysC is made of a generic core and attachable modules, one for each cryptographic algorithm. This document contains the specification of the core of GEmSysC and three of its modules: AES, RSA and SHA-256. GEmSysC was built targeting embedded systems, but this does not restrict its use only in such systems – after all, embedded systems are just very limited computing devices. As a proof of concept, two implementations of GEmSysC were made. One of them was built over wolfSSL, which is an open source library for embedded systems. The other was built over OpenSSL, which is open source and a de facto standard. Unlike wolfSSL, OpenSSL does not specifically target embedded systems. The implementation built over wolfSSL was evaluated in a Cortex- M3 processor with no operating system while the implementation built over OpenSSL was evaluated on a personal computer with Windows 10 operating system. This document displays test results showing GEmSysC to be simpler than other libraries in some aspects. These results have shown that both implementations incur in little overhead in computation time compared to the cryptographic libraries themselves. The overhead of the implementation has been measured for each cryptographic algorithm and is between around 0% and 0.17% for the implementation over wolfSSL and between 0.03% and 1.40% for the one over OpenSSL. This document also presents the memory costs for each implementation.