14,393 research outputs found
Uncovering Bugs in Distributed Storage Systems during Testing (not in Production!)
Testing distributed systems is challenging due to multiple sources of nondeterminism. Conventional testing techniques, such as unit, integration and stress testing, are ineffective in preventing serious but subtle bugs from reaching production. Formal techniques, such as TLA+, can only verify high-level specifications of systems at the level of logic-based models, and fall short of checking the actual executable code. In this paper, we present a new methodology for testing distributed systems. Our approach applies advanced systematic testing techniques to thoroughly check that the executable code adheres to its high-level specifications, which significantly improves coverage of important system behaviors. Our methodology has been applied to three distributed storage systems in the Microsoft Azure cloud computing platform. In the process, numerous bugs were identified, reproduced, confirmed and fixed. These bugs required a subtle combination of concurrency and failures, making them extremely difficult to find with conventional testing techniques. An important advantage of our approach is that a bug is uncovered in a small setting and witnessed by a full system trace, which dramatically increases the productivity of debugging
From the Desktop to the Cloud: Leveraging Hybrid Storage Architectures in Your Repository
4th International Conference on Open RepositoriesThis presentation was part of the session : Conference PresentationsDate: 2009-05-19 01:00 PM – 02:30 PMRepositories collect and manage data holdings using a storage device. Mainly this has been a local file system, but recently attempts have been made at using open storage products and cloud storage solutions, such as Sun's Honeycomb and Amazon S3 respectively. Each of these solutions has their own pros and cons but There are advantages in adopting a hybrid model for repository storage, combining the relative strengths of each one in a policy-determined model. In this paper we present an implementation of a repository storage layer which can dynamically handle and manage a hybrid storage systemJoint Information Systems Committee (JISC
InterCloud: Utility-Oriented Federation of Cloud Computing Environments for Scaling of Application Services
Cloud computing providers have setup several data centers at different
geographical locations over the Internet in order to optimally serve needs of
their customers around the world. However, existing systems do not support
mechanisms and policies for dynamically coordinating load distribution among
different Cloud-based data centers in order to determine optimal location for
hosting application services to achieve reasonable QoS levels. Further, the
Cloud computing providers are unable to predict geographic distribution of
users consuming their services, hence the load coordination must happen
automatically, and distribution of services must change in response to changes
in the load. To counter this problem, we advocate creation of federated Cloud
computing environment (InterCloud) that facilitates just-in-time,
opportunistic, and scalable provisioning of application services, consistently
achieving QoS targets under variable workload, resource and network conditions.
The overall goal is to create a computing environment that supports dynamic
expansion or contraction of capabilities (VMs, services, storage, and database)
for handling sudden variations in service demands.
This paper presents vision, challenges, and architectural elements of
InterCloud for utility-oriented federation of Cloud computing environments. The
proposed InterCloud environment supports scaling of applications across
multiple vendor clouds. We have validated our approach by conducting a set of
rigorous performance evaluation study using the CloudSim toolkit. The results
demonstrate that federated Cloud computing model has immense potential as it
offers significant performance gains as regards to response time and cost
saving under dynamic workload scenarios.Comment: 20 pages, 4 figures, 3 tables, conference pape
The Virginia Tech Computational Grid: A Research Agenda
An important goal of grid computing is to apply the rapidly expanding power of distributed
computing resources to large-scale multidisciplinary scientic problem solving. Developing a usable computational grid for Virginia Tech is desirable from many perspectives. It leverages distinctive strengths of the university, can help meet the research computing needs of users with the highest demands, and will generate many challenging computer science research questions. By deploying a campus-wide grid and demonstrating its effectiveness for real applications, the Grid Computing Research Group hopes to gain valuable experience and contribute to the grid computing community. This report describes the needs and advantages which characterize the Virginia Tech context with respect to grid computing, and summarizes several current research projects which will meet those needs
Resource Management in Message Passing Environments
This paper discusses the need for resource management support for parallel applications running on workstation clusters and communicating by message passing among tasks. Many resource management systems are only able to start a message passing runtime environment and parallel applications, but dynamic reconfiguration fails because of the missing cooperation between the resource manager and the runtime environment. In order to utilize computational resources in message passing environments efficiently, to control execution of parallel applications by rescheduling tasks at runtime, and to minimize their execution time, a resource management system has been developed and preliminary tests results have been carried out. Most of our efforts in this regard have been to design an efficient approach to load measurement and process scheduling and implement the resource management system in a manner such that it can easily be adapted to any message passing framework. Although our first version is based on the PVM system, we also intend to implement an MPI – based resource management system
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