Kenneth Nagin

The reservoir model and architecture for open federated cloud computing

The emerging cloud-computing paradigm is rapidly gaining momentum as an alternative to traditional IT (information technology). However, contemporary cloud-computing offerings are primarily targeted for Web 2.0-style applications. Only recently have they begun to address the requirements of enterprise solutions, such as support for infrastructure service-level agreements. To address the challenges and deficiencies in the current state of the art, we propose a modular, extensible cloud architecture with intrinsic support for business service management and the federation of clouds. The goal is to facilitate an open, service-based online economy in which resources and services are transparently provisioned and managed across clouds on an ondemand basis at competitive costs with high-quality service. The Reservoir project is motivated by the vision of implementing an architecture that would enable providers of cloud infrastructure to dynamically partner with each other to create a seemingly infinite pool of IT resources while fully preserving their individual autonomy in making technological and business management decisions. To this end, Reservoir could leverage and extend the advantages of virtualization and embed autonomous management in the infrastructure. At the same time, the Reservoir approach aims to achieve a very ambitious goal: creating a foundation for next-generation enterprise-grade cloud computing.

Reservoir - When One Cloud Is Not Enough

As cloud computing becomes more predominant, the problem of scalability has become critical for cloud computing providers. The cloud paradigm is attractive because it offers a dramatic reduction in capital and operation expenses for consumers.

The AGEDIS tools for model based testing

We describe the tools and interfaces created by the AGEDIS project, a European Commission sponsored project for the creation of a methodology and tools for automated model driven test generation and execution for distributed systems. The project includes an integrated environment for modeling, test generation, test execution, and other test related activities. The tools support a model based testing methodology that features a large degree of automation and also includes a feedback loop integrating coverage and defect analysis tools with the test generator and execution framework. Prototypes of the tools have been tried in industrial settings providing important feedback for the creation of the next generation of tools in this area.

Projected state machine coverage for software testing

Our research deals with test generation for software based on finite state machine (FSM) models of the program specification. We describe a set of coverage criteria and testing constraints for use in the automatic generation of test suites. We also describe the algorithms used to generate test suites based on these coverage criteria, and the implementation of these algorithms as an extension of the Murϕ model checker[4]. The coverage criteria are simple but powerful in that they generate test suites of high quality and moderate volume, without requiring the user to have a sophisticated grasp of the test generation technology. The testing constraints are used to combat the endemic problem of state explosion, typically encountered in FSM techniques. We illustrate our techniques on several well-known problems from the literature and describe two industrial trials, to demonstrate the validity of our claims.

Inter-cloud mobility of virtual machines

Cloud computing is increasingly gaining inroads among a variety of organizational users. As clouds are introduced for use by enterprises, service providers, and governmental and educational entities, new challenges related to the interconnection between such clouds emerge. Cloud administrators seek to maintain acceptable levels of autonomy and control over their cloud infrastructure, while ensuring the integrity of the cloud services. At the same time, they are expected to enable cross-cloud services, including mobility of workloads between clouds. We present the design and implementation of a technology that enables live mobility of virtual machines between clouds, while enforcing the cloud insularity requirements of autonomy, privacy, and security. We also provide an empirical evaluation of our solution, demonstrating its viability and compliance with requirements.

PDS Cloud: Long Term Digital Preservation in the Cloud

The emergence of the cloud and advanced object-based storage services provides opportunities to support novel models for long term preservation of digital assets. Among the benefits of this approach is leveraging the clouds inherent scalability and redundancy to dynamically adapt to evolving needs of digital preservation. PDS Cloud is an OAIS-based preservation-aware storage service employing multiple heterogeneous cloud providers. It materializes the logical concept of a preservation information-object into physical cloud storage objects. Preserved information can be interpreted by deploying virtual appliances in the compute cloud provisioned with cloud storage data objects together with their designated rendering software. PDS Cloud has a hierarchical data model supporting independent tenants whose assets are organized in multiple aggregations based on content and value. Continuous changes to data objects, life-cycle activities, virtual appliances and cloud providers are applied in a manner transparent to the client. PDS Cloud is being developed as an infrastructure component of the European Union ENSURE project, where it is used for preservation of medical and financial data.

Storlet Engine for Executing Biomedical Processes Within the Storage System

The increase in large biomedical data objects stored in long term archives that continuously need to be processed and analyzed requires new storage paradigms. We propose expanding the storage system from only storing biomedical data to directly producing value from the data by executing computational modules - storlets - close to where the data is stored. This paper describes the Storlet Engine, an engine to support computations in secure sandboxes within the storage system. We describe its architecture and security model as well as the programming model for storlets. We experimented with several data sets and storlets including de-identification storlet to de-identify sensitive medical records, image transformation storlet to transform images to sustainable formats, and various medical imaging analytics storlets to study pathology images. We also provide a performance study of the Storlet Engine prototype for OpenStack Swift object storage.