Raul Ceretta Nunes

Modeling communication delays in distributed systems using time series

The design of dependable distributed applications is a hard task, mainly because of the indefinable statistic behavior of the communication delays. Despite this feature, in practice, most system monitors make use of timeouts (a maximum waiting time) to ensure some termination properties in their protocols. To have better results, some monitors dynamically predict new timeout values based on observed communication delays to improve the performance and accuracy of the protocols. In the last years, time series theory emerged in the computer science area as a good tool to increase the prediction accuracy. The time series mathematical model is used to describe a sequence of observations of a stochastic process taken periodically in time. This paper shows how to model the round trip communication delay observed by a pull monitor (a periodic requester source), despite its non-periodic answers. As a result, this paper shows that the round trip communication delay pattern can be properly represented as a time series. This time series is an alternative model to explore new timeout predictors in a distributed system.

URL query string anomaly sensor designed with the bidimensional Haar wavelet transform

In this paper, the 2D Haar wavelet transform is the proposed analysis technique for HTTP traffic data. Web attacks are detected by two threshold operations applied to the wavelet coefficients of the 2D transform: one based on their median and the other on the best approximation method. The two proposed algorithms are validated through an extensive number of simulations, including comparisons with well-established techniques, confirming the effectiveness of the designed sensor.

Efficient and robust adaptive consensus services based on oracles

Due to their fundamental role in the design of fault-tolerant distributed systems, consensus protocols have been widely studied. Most of the research in this area has focused on providing ways for circumventing the impossibility of reaching consensus on a purely asynchronous system subject to failures. Of particular interest are the indulgent consensus protocols based upon weak failure detection oracles. Following the first works that were more concerned with the correctness of such protocols, performance issues related to them are now a topic that has gained considerable attention. In particular, a few studies have been conducted to analyze the impact that the quality of service of the underlying failure detection oracle has on the performance of consensus protocols. To achieve better performance, adaptive failure detectors have been proposed. Also, slowness oracles have been proposed to allow consensus protocols to adapt themselves to the changing conditions of the environment, enhancing their performance when there are substantial changes on the load to which the system is exposed. In this paper we further investigate the use of these oracles to design efficient consensus services. In particular, we provide efficient and robust implementations of slowness oracles based on techniques that have been previously used to implement adaptive failure detection oracles. Our experiments on a wide-area distributed system show that by using a slowness oracle that is well matched with a failure detection oracle, one can achieve performance as much as 53.5% better than the alternative that does not use a slowness oracle.

Semi-Autonomous Navigation for Virtual Tactical Simulations in the Military Domain.

Integrated constructive and virtual simulations are becoming popular for tactical training in the military domain. An important aspect concerning the integration of these simulation models in the construction of virtual tactical simulations is the modelling and implementation of different kinds of semi-autonomous agents. A fundamental feature of these agents is the capability of intelligently and realistically modelling task-oriented navigation activities in large virtual terrain simulation environments, while following underlying military doctrine and tactics. This paper reviews important navigation issues that emerge in such simulation systems and prominent Artificial Intelligence (AI) techniques that have been explored to solve them. From this analysis, a hybrid, semi-autonomous navigation framework is proposed aiming to fulfil the needs of virtual tactical training simulations, more specifically, in the military domain. As implemented in a system for the virtual tactical simulation of artillery battery tasks, the framework shows how to overcome the challenges of implementing realistic global and local navigation behaviours for military units and, at the same time, it shows that the semi-autonomous behaviours implemented are of primary importance to allow interaction with users for learning purposes in the simulation exercises.

Energy saving on DTN using trajectory inference model

Delay or Disruption Tolerant Networks (DTN) are characterized by long delays and intermittent connectivity, requiring efficient energy consumption for increasing the mobile nodes lifetime. The movements of nodes modify the network topology, changing the number of connection opportunities between nodes. This paper proposes a new technique for energy saving on DTN by using a trajectory inference model for mobile nodes powered by machine learning techniques. The objective of this work is to reduce the energy consumption of DTN using a mobility prediction method. Experimental results indicate more than 47% of energy saving on data communication applying the trajectory inference model.

Doctrine based multi-resolution HLA distributed simulation

In distributed simulation, the purpose of multi-resolution methods is to allow simulation integration getting consistent views of different resolutions. In these methods, challenges in the treatment of aggregation and disaggregation can be found, such as synchronization of events and objects, and data reliability when occurs a change of resolution. Doctrines are the basis for operations involving different resources (human and material) with different roles to succeed in operation, and multi-resolution in distributed simulation can take advantage of this factor to ensure the reliability of aggregation and disaggregation processes. The aim of this paper is to propose a new strategy for treatment of multi-resolution, which builds converting rules from doctrine dynamic rules. The multi-resolution converter uses dynamic rules to describe aspects of the doctrine in the aggregation and disaggregation processes, increasing the reliability of multi-resolution distributed simulations. This strategy was implemented on a High Level Architecture (HLA) federation with virtual and constructive Commercial Off- The-Shelf (COTS) simulators. The experiments showed the flexibility of this strategy on managing different doctrines.

Signal strength as support to mobility detection on failure detectors

A Failure Detector (FD) is an essential building block to develop reliable applications on Mobile Ad-hoc NETworks (MANETs). To detect faulty nodes correctly the node mobility and disconnections are challenges that must be circumvented by an FD. This paper presents an FD algorithm that detects faulty nodes efficiently in MANETs. This approach explores the signal power intensity on the receiving messages to detect node mobility and improve the failure detector knowledge. The experimental results have shown improvements in the Quality of Service (QoS) when compared with other similar FDs.

A hybrid method to detecting failures in mobile sensor networks using localization algorithms

This paper presents a new approach to detect node failures to support fault tolerant application on mobile sensor networks in an optimized way. Our approach takes advantage of localization algorithm message exchanges to implement a failure detector algorithm, optimizing sent messages, reducing energy consumption and contributing to avoid the nodes scalability problem. We analyze a network performance for the Friedman Failure Detector, Monte Carlo Localization and both working together. The experimental results from simulations show an approximately reduction of 43% in the number of messages sent and are reported in this paper.

THE USE OF TIME SERIES AS A PREDICTION TOOL FOR PROVISIONING IN CLOUD COMPUTING ENVIRONMENTS

Cloud Computing systems needs to ensure the distribution of resources for processing services within acceptable levels of Quality of Service - QoS. One problem that exists in this context is how to use available computational resources avoiding bottlenecks and wastage. This paper aims to determine if there is a statistical method able to predict the amount of resources that should be used for new virtual servers. Thus, we used a time series model named ARIMA (autoregressive moving average) as underlying technique for provisioning of new virtual machines in Cloud Computing environments. The results evidence the feasibility of use of such models in this context.

A Management Model to Prevent Misuse of the Web

The Internet has brought benefits to companies. However, the misuse of this resource can cause losses in employee productivity. This paper proposes a management model to prevent misuse of the Web that provides a cycle of continuous improvement of access control policies based on contextual attributes and a software to minimize the cost of the management of access control polices. A case study in a public university demonstrated the applicability of the model in the management of wireless Internet access.