Luis Hideo Vasconcelos Nakamura

Performance Evaluation of Resource Management in Cloud Computing Environments.

Cloud computing is a computational model in which resource providers can offer on-demand services to clients in a transparent way. However, to be able to guarantee quality of service without limiting the number of accepted requests, providers must be able to dynamically manage the available resources so that they can be optimized. This dynamic resource management is not a trivial task, since it involves meeting several challenges related to workload modeling, virtualization, performance modeling, deployment and monitoring of applications on virtualized resources. This paper carries out a performance evaluation of a module for resource management in a cloud environment that includes handling available resources during execution time and ensuring the quality of service defined in the service level agreement. An analysis was conducted of different resource configurations to define which dimension of resource scaling has a real influence on client requests. The results were used to model and implement a simulated cloud system, in which the allocated resource can be changed on-the-fly, with a corresponding change in price. In this way, the proposed module seeks to satisfy both the client by ensuring quality of service, and the provider by ensuring the best use of resources at a fair price.

Providing IaaS resources automatically through prediction and monitoring approaches

A cloud computing infrastructure management is proposed in this paper, which consists of two approaches that facilitate the provisioning of computing resources in a self-adaptive virtualized environment. Resource allocation is employed to predict the future of workload management and to employ a self-adaptive approach by using computational agents to monitor the Virtual Machines (VMs). The paper also includes the Return on Investment (ROI) formula that deals with the relationship between the prices for the Infrastructure-as-a-Service (IaaS) contracted by the customer and the effective use of this service. The experimental results show a significant improvement when self-configuration is used with agent-based computational modeling in contrast with the self-configuration based on prediction for future workload.

A Health Smart Home System to Report Incidents for Disabled People

Health Smart Home (HSH) provides health care services for people with special needs and wish to be independent and remain in their own home. The residence is equipped with automatic devices and a range of sensors to ensure the safety of the patients at home and the supervision of their health status. These Health Smart Homes have been increasingly studied not only by the academic community but also by industry on account of the great potential it has, especially in applications that can help people with some type of physical disability such as visual or hearing impairment. We implemented a system witch monitors rooms and issues a warning whenever it detects a potential hazard. Our proposal relies on low-cost cutting-edge technology.

PEESOS: A Web Tool for Planning and Execution of Experiments in Service Oriented Systems

Performing functionality testing in service-oriented architectures is not a trivial task. The difficulty is especially the large number of components that may be present in a SOA such as brokers, providers, service registries, clients, monitoring tools, data storage tools, etc. Thus, in order to facilitate the process of conducting functional testing and capacity planning in service-oriented systems, we present PEESOS. This first version is a functional prototype that offers facilities to assist researchers and industry to test their new applications, allowing collaborations that can be done between the participants to achieve an appropriate objective when developing a new application. The first results show that it is possible to make a planning environment easier to operate and to readily obtain results for performance evaluation of a target architecture. Since this is a first version of the prototype, it has interface and scalability limitations as well as needing improvements in performance of the logs repository and also in a core engine. We hope that such limitations can be corrected in the near future, including gathering information from the scientific community to make the prototype a useful and accessible tool. PEESOS is on-line and available at http://peesos.wsarch.lasdpc.icmc.usp.br.

A Study Case of Restful Frameworks in Raspberry Pi: A Performance and Energy Overview

This paper analyzes the execution behavior of web services on devices with limited resources. The experiments compare web services in the Axis2 and CXF frameworks analyzing performance and power consumption. To determine which framework is better suited for service provision, a testing environment and a performance and energy evaluation between them are presented. We show that the Raspberry Pi can be useful in service-oriented applications for different types of tasks. Bringing together the best features of small devices and SoC, it is possible to provide diverse, mobile and green applications.

Design and implementation of fault tolerance techniques to improve QoS in SOA

Fault tolerance techniques can improve the trust of users in service oriented architectures as they can ensure data availability. This paper presents an implementation of a novel fault tolerance mechanism in a SOA architecture which simultaneously provides increased availability and better quality of service. In addition to this mechanism, a service selector using reputation ratings of the architecture components is discussed. The selection is based on information from past transactions of the components of the architecture, which allows to identify the best web services able to meet the requests of customers. The mechanisms are tested and a performance evaluation is presented to validate the results.

Combining cell phones and WSNs for preventing accidents in smart-homes with disabled people

Smart homes provide automatic services through a combination of wireless sensor networks (WSNs) and wireless devices that allow monitoring operations in the home. These smart homes have been increasingly studied not only by the academic community but also by industry on account of the great potential they have, especially in applications that can help people with some type of physical disability such as visual or hearing impairment. This kind of application can give them independence and make their lives safer and more comfortable. Thus, in this paper we propose a Health Smart Home system for disabled people that can warn them about possible accidents that can occur in a particular location of their house. In other words, the system anticipates possible accidents that may occur somewhere in the house. We implemented a preliminary prototype that monitors rooms and issues a warning whenever it detects a potential hazard. Our proposal relies on low-cost cutting-edge technology and includes the following: Raspberry Pi boards, motion sensors, cameras and a central server. The server will handle the data that has been captured by sensors and send warnings through smartphones to people with physical impairments.

A semantic approach for efficient and customized management of IaaS resources

This paper presents a semantic approach to custom management of IaaS (Infrastructure as a Service) resources in a cloud computing environment requiring minimal human intervention from both the cloud provider and the user. The proposal differs from other approaches by using autonomic computing and semantic web techniques together to provide a self-configuring and self-optimizing environment that aims to satisfy SLAs (Service Level Agreements). The approach monitors the virtualized resources to guarantee a customized and optimized use based on financial criteria and energy consumption policies.

Different Approaches for QoS-Aware Web Services Composition Focused on E-Commerce Systems

In this paper four different algorithms are proposed to solve the QoS-aware Web Services Composition (QWSC) problem in six different search-space sizes and a realistic deadline (a point not covered in many related works). Differently from some related works, statistical techniques are adopted in this paper in order to ensure more precise results from the algorithms. Two new algorithms are proposed: Greedy Heuristic and Double Hybrid Genetic Algorithm. The results of these algorithms were compared with an Exhaustive Search algorithm that always guarantees the global optima and a heuristic algorithm called Utility Function. The results obtained showed that the design of experiments and the performance evaluation can be used to determine which algorithms has better performance according to the different search-space sizes and the established deadline, it is also possible to determine which genetic operators are better suited for the QWSC problem.

Semantic Web and Ontology Applied to Web Services Discovery with QoS

This paper presents a study on the use of Semantic Web and Ontology created with the OWL (Web Ontology Language) to sort and select Web Services according to its Quality of Service (QoS) attributes. The focus of this paper is to evaluate the performance of this approach in accordance with some adopted parameters. To this end, two algorithms that use Semantic Web resources have been developed in order to make the discovery of appropriate Web Services in the ontology. At the end of this article, the results of a performance evaluation are presented and analyzed.