Vandi Alves

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.

Experimental evaluation of software aging effects in the eucalyptus elastic block storage

The need for reliability, availability and performance has increased in modern applications, which need to handle rapidly growing demands while providing uninterrupted service. Cloud computing systems fundamentally provide access to large pools of data and computational resources. Eucalyptus is a software framework used to implement private clouds and hybrid-style Infrastructure as a Service. It implements the API Amazon Web Service (AWS), allowing interoperability with other AWS-based services. Elastic block storage is a technology which provides flexible allocation of remote storage volumes to the virtual machines running in a cloud computing environment. This work investigates the software aging effects on the Eucalyptus framework, considering workloads composed of intensive requests for attaching remote storage volumes to virtual machines. The results evidenced problems that may be harmful to system dependability and its performance due to RAM memory exhaustion and subsequent use of swap memory, besides high CPU utilization by the virtual machines and subsequent increase in the response time of applications running on the VMs.

An Investigative Approach to Software Aging in Android Applications

This paper proposes an investigative approach to indicators of software aging in applications developed for Android, a Linux-based operating system primarily designed for touch screen mobile devices such as smartphones and tablets. Software aging is a degrading factor in systems, leading to poor performance, failures, and may ultimately result in system downtime. The methodology proposed identifies memory leaking in Android applications. In order to test the approach, case studies were performed with the Monkey tool as workload generator, employing Linux utilities to monitor the environment. Communication between the computer and the smartphone was handled with the ADB tool, a toolkit included in the Android SDK package. Experimental results confirmed both the effectiveness of the procedure and the existence of software aging phenomenon in the Foursquare application running on the Android OS platform.

EucaBomber: Experimental Evaluation of Availability in Eucalyptus Private Clouds

Cloud computing is a computational paradigm with increasing adoption because it offers resources as services in a dynamically scalable way through the Internet. The constant concern in providing cloud computing services in a reliable and uninterrupted manner inspires availability and reliability studies. A feasible method of performing such studies is through automated fault injection, enabling to observe the behavior of the cloud architecture under many conditions. This paper presents a fault injection tool, named EucaBomber, for reliability and availability studies in the Eucalyptus cloud computing platform. EucaBomber allows to define the probability distribution associated to the time between generated events. The efficiency of EucaBomber is verified through testbed scenarios where faults and repairs are injected in a private Eucalyptus cloud. The experimental results are cross-checked with results estimated from a Reliability Block Diagram, using the same input parameters of the experimental testbed. The test scenarios also illustrate how the tool may assist cloud systems administrators and planners to evaluate the systems availability and maintenance policies.

Characterization of Software Aging Effects in Elastic Storage Mechanisms for Private Clouds

Cloud computing systems fundamentally provide access to large pools of data and computational resources. Eucalyptus is a software framework used to implement private and hybrid-style Infrastructure as a Service clouds. It implements the Amazon Web Service (AWS) API, allowing interoperability with other AWS-based services. Elastic block storage (EBS) is a technology which provides flexible allocation of remote storage volumes to the virtual machines running in a cloud computing environment. Eucalyptus interacts with many software components to provide EBS features to the virtual machines: KVM hypervisor and Eucalyptus Node Controller (NC) are among those components. This work investigates the software aging effects in a Eucalyptus environment, considering workloads composed of intensive requests for attaching remote storage volumes to virtual machines. The results evidenced that memory leaks in Node Controller and the high CPU utilization by the KVM process are strongly correlated. The experimental analysis also show how much the aging effects are related to the performance degradation of a virtualized web server running on this infrastructure.

A Tool for Automatic Dependability Test in Eucalyptus Cloud Computing Infrastructures

Cloud Computing is a paradigm that dynamically provides resources as services through the Internet. The constant concern about the trust placed in cloud computing systems inspires dependability studies. A possible way of performing dependability studies, especially regarding reliability and availability, is through fault injection tools, which enable to observe the system’s behavior during the occurrence of fault events. This paper presents a fault injection tool, called EucaBomber, for reliability and availability studies in the Eucalyptus cloud computing platform. The tool supports fault injections in Eucalyptus hardware and software components at runtime, and also upholds reparation of both types of injected faults. The efficiency of EucaBomber is tested through a case study involving two different scenarios where faults and repairs of hardware and software are injected in the Eucalyptus platform simulating the systems events. Such a tool assists the system administrator and planners to evaluate the system’s availability and maintenance policies.

Performance evaluation of sheepdog distributed storage system

Distributed storage systems (DSS) are becoming even more important and complex due to the emergence of paradigms such as cloud computing, and the challenges for dealing with big data. DSS provide a set of services such as publishing, file sharing and high performance utility storage. In addition, there is a growing demand to support these services with high scalability, availability and low cost. Sheepdog is a distributed storage system which aims at providing storage volumes with high availability, using clusters of common machines. This type of storage system may prove useful in the VMS (Video Monitoring Service) market and as remote storage for cloud-based applications. This paper analyzes the scalability of Sheepdog clusters, by measuring the performance with different number of nodes and different replication degrees. The system analyzed here showed better performance for read operations in small cluster sizes than in larger ones. On the other hand, proper scalability was found for the write throughput, since no significant performance degradation was noticed when the number of cluster nodes increased.

Decision making in cloud environments: an approach based on multiple-criteria decision analysis and stochastic models

Cloud computing is a paradigm that provides services through the Internet. The paradigm has been influenced by previously available technologies (for example cluster, peer-to-peer, and grid computing) and has now been adopted by almost all large organizations. Companies such as Google, Amazon, Microsoft and Facebook have made significant investments in cloud computing, and now provide services with high levels of dependability. The efficient and accurate assessment of cloud-based infrastructure is fundamental in guaranteeing both business continuity and uninterrupted public services, as much as is possible. This paper presents an approach for selecting cloud computing infrastructures, in terms of dependability and cost that best suits both company and customer needs. We use stochastic models to calculate dependability-related metrics for different cloud infrastructures. We then use a Multiple-Criteria Decision-Making (MCDM) method to rank the best cloud infrastructures, taking customer service constraints such as reliability, downtime, and cost into consideration. A case study demonstrates the practicability and usefulness of the proposed approach.