Marcos José Santana

Performance evaluation based on system modeling using Statecharts extensions

Abstract This paper presents two extensions for Statecharts: the Stochastic Statecharts, which use the original statecharts notation with a minor modification in the formal semantics and the Queuing Statecharts, which do not follow the pure Statecharts notation, but a join between Statecharts and queuing network representations. Some basic elements of Statecharts are redefined such as events and conditions, besides some concepts referring to the dynamic system behavior. The specification approaches show the basic behavior of a generic queuing system by means of templates and standard events. It is presented the PerformCharts, a new simulation environment based on Statecharts specification, which allows model solution using either Markov chains or the Network Simulator (NS).

Real-time compression of SOAP messages in a SOA environment

This paper discusses how the use of compression techniques aimed at decreasing data transfer times over a communication network can influence the response time of an application that process SOAP messages in the context of a service-oriented architecture. Following an overview of the most known object models and comparing some of their features, the article presents an heuristic that can be used to decide whether a soap message either should or should not be compressed. A simulated experiment shows that the proposed heuristic can help in reducing the service response time in a variety of scenarios.

Using adaptive priority scheduling for service differentiation QoS-aware Web servers

The current best-effort service model used on the Internet treats all requests uniformly, both in the network and at the application level. However, sometimes it is desirable to provide different classes or levels of service in order to satisfy the needs of different users and applications. In this paper, we propose an architecture for the provision of differentiated services at the Web server level. The architecture is verified by means of a simulation model and real Web server traces are used as workload. Two priority-based algorithms are implemented in the architecture aiming at service differentiation. The adaptive algorithm, an innovative solution at the application domain, allows the tuning of the priority level provided and determines how strict the use of priorities would be. The system can then adapt itself to various workloads, an essential feature in a highly dynamic environment such as the Web.

Combining time series prediction models using genetic algorithm to autoscaling Web applications hosted in the cloud infrastructure

In a cloud computing environment, companies have the ability to allocate resources according to demand. However, there is a delay that may take minutes between the request for a new resource and it being ready for using. This causes the reactive techniques, which request a new resource only when the system reaches a certain load threshold, to be not suitable for the resource allocation process. To address this problem, it is necessary to predict requests that arrive at the system in the next period of time to allocate the necessary resources, before the system becomes overloaded. There are several time series forecasting models to calculate the workload predictions based on history of monitoring data. However, it is difficult to know which is the best time series forecasting model to be used in each case. The work becomes even more complicated when the user does not have much historical data to be analyzed. Most related work considers only single methods to evaluate the results of the forecast. Other works propose an approach that selects suitable forecasting methods for a given context. But in this case, it is necessary to have a significant amount of data to train the classifier. Moreover, the best solution may not be a specific model, but rather a combination of models. In this paper we propose an adaptive prediction method using genetic algorithms to combine time series forecasting models. Our method does not require a previous phase of training, because it constantly adapts the extent to which the data are coming. To evaluate our proposal, we use three logs extracted from real Web servers. The results show that our proposal often brings the best result and is generic enough to adapt to various types of time series.

An automatic distributed simulation environment

Developing a sequential simulation program is not an easy task. Developing a distributed simulation program is harder than a sequential one because it is necessary to deal with mapping physical processes into logical processes, communication and synchronization problems and learn another simulation language/library. In the literature, several simulation environments can be found but the great number are for sequential simulation, not using all the advantages of a distributed/parallel platform. This paper presents ASDA, an automatic distributed simulation environment that aims at providing several possibilities to users developing a distributed simulation. The automatic word can be understood in three different ways: the environment automatically generates a distributed simulation program code; the environment can automatically choose one distributed simulation approach; and the environment can automatically convert a sequential simulation program into a distributed simulation program using the MRIP (multiple replication in parallel) approach.

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.

A Performance Evaluation Study for Web Services Attachments

Web Services are a technology based on the Service Oriented Architecture that enables communication between applications through the Internet. Using Web Services, it is possible to send any type of information in any form of encryption. In this context, different techniques have been used to attach binary files in SOAP messages. However, there is no consensus on which technique has the best performance. This paper presents a performance evaluation study with three techniques for Web Service attachments: Pure Binary, MTOM and SwA. A testing environment was configured to verify the influence of the network and the size of files. Also, we present a tool called WSATPerf that supports the execution of the performance evaluation.

PIV and WPIV: Performance Index For Heterogeneous Systems Evaluation

This article presents two new performance indices (PIV - performance index vector and WPIV - weighted performance index vector), to evaluate heterogeneous computing systems, based on a Euclidian metric. Aiming to maximize the use of the machines, the proposed indices are a combination of several usual indices and the results of their evaluation through a simulator show an appropriate behavior for different kinds of applications

Negotiation mechanisms on application level: a new approach to improve quality of service in Web servers

This paper describes a negotiation mechanism inserted in a Web server model with differentiated services. All the results of this article have been obtained by means of simulation using for this a queueing network model representing a Web server with QoS. The results also confirm that this new approach enhances the quality of service provided to clients, mainly in overload situations, being an aid in the process of request admission and dropping

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.