Rivalino Matias

The fundamentals of software aging

Since the notion of software aging was introduced thirteen years ago, the interest in this phenomenon has been increasing from both academia and industry. The majority of the research efforts in studying software aging have focused on understanding its effects theoretically and empirically. However, conceptual aspects related to the foundation of this phenomenon have not been covered in the literature. This paper discusses foundational aspects of the software aging phenomenon, introducing new concepts and interconnecting them with the current body of knowledge, in order to compose a base taxonomy for the software aging research. Three real case studies are presented with the purpose of exemplifying many of the concepts discussed.

Accelerated Degradation Tests Applied to Software Aging Experiments

In the past ten years, the software aging phenomenon has been systematically researched, and recognized by both academic, and industry communities as an important obstacle to achieving dependable software systems. One of its main effects is the depletion of operating system resources, causing system performance degradation or crash/hang failures in running applications. When conducting experimental studies to evaluate the operational reliability of systems suffering from software aging, long periods of runtime are required to observe system failures. Focusing on this problem, we present a systematic approach to accelerate the software aging manifestation to reduce the experimentation time, and to estimate the lifetime distribution of the investigated system. First, we introduce the concept of ¿aging factor¿ that offers a fine control of the aging effects at the experimental level. The aging factors are estimated via sensitivity analyses based on the statistical design of experiments. Aging factors are then used together with the method of accelerated degradation test to estimate the lifetime distribution of the system under test at various stress levels. This approach requires us to estimate a relationship model between stress levels and aging degradation. Such models are called stress-accelerated aging relationships. Finally, the estimated relationship models enable us to estimate the lifetime distribution under use condition. The proposed approach is used in estimating the lifetime distribution of a web server with software aging symptoms. The main result is the reduction of the experimental time by a factor close to 685 in comparison with experiments executed without the use of our technique.

Experimental evaluation of software aging effects on the eucalyptus cloud computing infrastructure

The need for reliability and availability has increased in modern applications, which need to handle rapidly growing demands while providing uninterrupted service. This work investigates the memory leak and memory fragmentation aging effects on the Eucalyptus cloud-computing framework, which considers workloads composed of intensive requests addressing different virtual machines. We experimentally show the existence of the investigated aging effects in the cloud environment under study. Also, a software rejuvenation strategy to mitigate the observed aging effects is proposed and its benefits are evaluated.

Software aging issues on the eucalyptus cloud computing infrastructure

Demands on software reliability and availability have increased due to the nature of present day applications. Cloud computing systems fundamentally provide access to large pools of data and computational resources through a variety of interfaces similarly to existing grid and HPC resource management and programming systems. This work investigates the software aging effects on the Eucalyptus cloud computing infrastructure considering workloads composed of provisioning different types of virtual machines.

Using Accelerated Life Tests to Estimate Time to Software Aging Failure

Software aging is a phenomenon defined as the continuing degradation of software systems during runtime, being particularly noticeable in long-running applications. Aging-related failures are very difficult to observe, because the accumulation of aging effects usually requires a long-term execution. Thus, collecting a statistically significant sample of times to aging-related failures so as to estimate the system’s lifetime distribution is a very hard task. This is an important problem that prevents many experimental and analytical studies, mainly those focused on modeling of software aging aspects, of using representative parameter values. In this paper we propose and evaluate the use of quantitative accelerated life tests (QALT) to reduce the time to obtain the lifetime distribution of systems that fail due to software aging. Since QALT was developed for hardware failures, in this paper, we adapt it to software aging experiments. We test the proposed approach experimentally, estimating the lifetime distribution of a real web server system. The accuracy of the estimated distribution is evaluated by comparing its reliability estimates with a sample of failure times observed from the real system under test. The mean time to failure calculated from the real sample falls inside the 90% confidence interval constructed from the estimated lifetime distribution, demonstrating the high accuracy of the estimated model. The proposed approach reduces the time required to obtain the failure times by a factor of seven, for the real system investigated.

Software Rejuvenation in Eucalyptus Cloud Computing Infrastructure: A Method Based on Time Series Forecasting and Multiple Thresholds

The need for reliability and availability has increased in modern applications, in order to handle rapidly growing demands while providing uninterrupted service. Cloud computing systems fundamentally provide access to large pools of data and computational resources through a variety of interfaces similarly to existing grid and HPC resource management and programming systems. This work proposes an approach that uses time series to schedule rejuvenation, so as to reduce the downtime by predicting the proper moment to perform the rejuvenation.We show the results of our approach through experiments using the Eucalyptus cloud computing framework.

Software aging in the eucalyptus cloud computing infrastructure: Characterization and rejuvenation

The need for high reliability, availability and performance has significantly increased in modern applications, that handle rapidly growing demands while providing uninterruptible services. Cloud computing systems fundamentally provide access to large pools of data and computational resources. Eucalyptus is a software framework largely used to implement private clouds and hybrid-style Infrastructure as a Service. It implements the Amazon Web Service (AWS) API, allowing interoperability with other AWS-based services. This article investigates the software aging effects in the Eucalyptus framework, considering workloads composed of intensive requests for remote storage attachment and virtual machine instantiations. We found problems that may be harmful to system dependability and performance, specifically regarding to RAM memory and swap space exhaustion, besides highly excessive CPU utilization by the virtual machines. We also present an approach that applies time series analysis to schedule rejuvenation, so as to reduce the downtime by predicting the proper moment to perform the rejuvenation. We experimentally evaluate our approach using an Eucalyptus test bed. The results show that our approach achieves higher availability, when compared to a threshold-triggered rejuvenation method based on continuous monitoring of resources utilization.

The mechanics of memory-related software aging

Software aging is a phenomenon defined as the continuing degradation of software systems during runtime, being particularly noticeable in long-running applications. Memory-related aging effects are one of the most important problems in this research field. Therefore understanding their causes and how they work is a major requirement in designing dependable software systems. In this paper we go deep into how memory management works inside application process, focusing on two memory problems that cause software aging: fragmenting and leakage. We explain the mechanics of memory-related software aging effects dissecting a real and widely adopted memory allocator. Along with the theoretical explanation, we present an experimental study that illustrates how memory fragmenting and leakage occur and how they accumulate over time in order to cause system aging-related failures.

Measuring software aging effects through OS kernel instrumentation

Software aging is a phenomenon defined as the continuing degradation of software systems during runtime, being particularly noticeable in long-running applications. Measuring aging effects is a very important step towards identifying the most significant causes of software aging, so rejuvenation mechanisms can be applied effectively. The literature has already discussed aging monitoring from a userspace perspective. In this paper we present an innovative study where we explore OS kernel instrumentation techniques to measure software aging effects. Kernel instrumentations are available in practically all modern operating systems and we show how this powerful mechanism can be used to monitor either application-specific or system-wide aging indicators. In addition to the theoretical study, we present numerical results obtained from controlled experiments.

On the effectiveness of Mann-Kendall test for detection of software aging

Software aging (i.e. progressive performance degradation of long-running software systems) is difficult to detect due to the long latency until it manifests during program execution. Fast and accurate detection of aging is important for eliminating the underlying defects already during software development and testing. Also in a deployment scenario, aging detection is needed to plan mitigation methods like software rejuvenation. The goal of this paper is to evaluate whether the Mann-Kendall test is an effective approach for detecting software aging from traces of computer system metrics. This technique tests for existence of monotonic trends in time series, and studies of software aging often consider existence of trends in certain metrics as indication of software aging. Through an experimental study we show that the Mann-Kendall test is highly vulnerable to creating false positives in context of aging detection. By increasing the amount of data considered in the test, the false positive rate can be reduced; however, time to detect aging increases considerably. Our findings indicate that aging detection using the Mann-Kendall test alone is in general unreliable, or may require long measurement times.