OS streaming deployment

Clerc, David; Garcés-Erice, Luis; Rooney, Seán

doi:10.1109/pccc.2010.5682313

Cited by 9 publications

(5 citation statements)

References 2 publications

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“…The caching device also writes d locally modified sectors to the diskCache in the local disk. An example implementation by the authors of a caching device is described in [4]. OpenRemoteDisk: The target is created when the client calls OpenRemoteDisk.…”

Section: Methodsmentioning

confidence: 99%

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Guaranteeing consistency between large replicated writable disk images

Rooney

Garcés-Erice

2013

Proceedings of the 9th International Conference on Network and Service Management (CNSM 2013)

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Abstract-We describe a distributed protocol that guarantees the consistency of multiple replicas of a given disk image represented by a large file. The image replicas are used as read/write caches for the primary disk image located at a server. The protocol allows stale caches to be incrementally invalidated minimizing the amount of data that must be copied and recopied from the server. We prove that the protocol ensures the consistency of the disk from the point of view of any client using it, and we describe an implementation within an existing streaming framework.

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Section: Methodsmentioning

confidence: 99%

“…Caching the contents of the remote image disk on the local storage of the machine on which the OS executes offers benefits in terms of performance and scalability [4]. The cache is persistent, allowing the OS to be restarted with a minimal need for interaction with the storage cluster.…”

Section: Introductionmentioning

confidence: 99%

Guaranteeing consistency between large replicated writable disk images

Rooney

Garcés-Erice

2013

Proceedings of the 9th International Conference on Network and Service Management (CNSM 2013)

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“…The driver is fully described in [4]. The COR driver is implemented as a module within the device-mapper infrastructure of the Linux kernel.…”

Section: Copy-on-read Block Device Drivermentioning

confidence: 99%

“…The bootloader provisions the hypervisor image securely from a trusted server onto the device's storage. The provisioning is performed lazily, as described in [4], such that blocks are only copied across the network the first time they are accessed. The images of the user's virtual machines are made available through the same mechanism.…”

Section: Introductionmentioning

confidence: 99%

Secure lazy provisioning of virtual desktops to a portable storage device

Garcés-Erice

Rooney

2012

Proceedings of the 6th International Workshop on Virtualization Technologies in Distributed Computing Date

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It is the software and data stored on a 'personal computer' that makes it personal. These contents can be conveniently stored as a disk image on a server and made available on the users' personal storage as and when required through lazy provisioning. We describe a desktop virtualization system that allows users to securely execute virtual machines on untrusted physical machines. This system is enabled through a portable personal device which contains a bootloader in tamper-proof storage. The hypervisor and the virtual machines are securely provisioning from a trusted server. Blocks are cached on the local storage of the portable device after their first access through a copy-on-read driver. We show that a desktop OS can be started promptly using the system and that the subsequent user experience is close to that for a conventional machine.

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“…However, the OS is costly in terms of time and bandwidth. Another study has attempted to enhance deployment performance by applying a streaming server between the OS and the disk [16]. The authors have implemented this architecture in Windows and Linux.…”

Section: Introductionmentioning

confidence: 99%

Multicast Deployment of Cloud Operating Systems

Lee

Teng

et al. 2012

2012 IEEE 12th International Conference on Computer and Information Technology

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With cloud computing's paradigm shift for IT industries, the concept of thin clients has become popular again. There are usually numerous nodes with various functions in a cloud computing system. It is important to deploy different cloud operating systems (cloud OSs) onto different nodes. The conventional method of using unicast deployment to distribute a massive cloud OS onto thousands of nodes is time consuming and bandwidth-intensive. In this work, we propose a multicast deployment approach to significantly improve deployment efficiency. Furthermore, our multicast deployment approach can leverage existing configurations of the unicast counterpart. Therefore, customized deployment for different groups of nodes can be achieved. To evaluate the feasibility of the proposed approach in practical applications, our deployment approach is implemented using CentOS and Ubuntu on many nodes. Empirical studies show that the required time for the entire distribution process is significantly reduced, from starting delivery until the OS is ready. Moreover, network bandwidth consumption is also significantly reduced compared with the conventional unicast deployment. Consequently, system administrators must spend less effort on monitoring and maintenance.

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OS streaming deployment

Cited by 9 publications

References 2 publications

Guaranteeing consistency between large replicated writable disk images

Guaranteeing consistency between large replicated writable disk images

Secure lazy provisioning of virtual desktops to a portable storage device

Multicast Deployment of Cloud Operating Systems

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