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Record W63207346

Smart applications on virtual infrastructure

2011· article· en· W63207346 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueConference of the Centre for Advanced Studies on Collaborative Research · 2011
Typearticle
Languageen
FieldComputer Science
TopicCloud Computing and Resource Management
Canadian institutionsUniversity of TorontoYork UniversityIBM (Canada)University of Alberta
Fundersnot available
KeywordsScalabilityComputer scienceArchitectureVirtualizationResource (disambiguation)Computer securityCloud computingOperating systemComputer network
DOInot available

Abstract

fetched live from OpenAlex

Smart Applications on Virtual Infrastructure (SAVI) research is focused on the design of future application platforms built on flexible, versatile and evolvable infrastructure that can readily deploy, maintain, and retire the large-scale, possibly short-lived, distributed applications that are the future of software systems. Future application platforms will support an open applications and content marketplace where a vast number of vendors offer applications, content, and services to other vendors as well as to consumers. This marketplace will be characterized by extremely large scale and very high churn, with new applications being introduced and others retired at very fast rates. Content will also be produced at very high rates and large volumes, and demand for content will change quickly over time. These attributes of the marketplace will place extreme demands on the supporting infrastructure for agility in resource allocation, as well as scalability, reliability, accountability and security. Cost-effectiveness will require that infrastructure be flexible so that it can be readily re-purposed, essentially reprogrammed, to provide new capabilities. The management and control systems must be designed to provide efficient resource usage and high availability at low operations expense. Multiple owners will provide infrastructure and so the architecture for the infrastructure must be open and allow for interconnection and federation. Crucially, the architecture of the infrastructure should support the rapid introduction of applications, the delivery of applications with targeted levels of Quality of Experience, and the rapid retirement of applications and redeployment of their supporting resources. SAVI takes a view of infrastructure in that all resources whether computing, processing, or networking are viewed as being part of shareable resource pools that can be controlled and managed using the same systems. Future users will typically access the application platform through a mobile device that connects to a ubiquitous very-high-bandwidth, integrated wireless/optical access network. The application platform provides connectivity to services that support the application of interest. Many services will be supported by massive-scale distant datacenters located at sites of renewable energy. Other services will require low latency (alarms in grids, safety applications in transportation, monitoring in remote health) or processing of large volumes of local data (e.g., video capture in lecture rooms) provided by converged network and computing resources at the smart edge of the network, such as the premises of service providers. The role of the resource control and management systems is to ensure that applications can be supported by all the elements of the infrastructure in the anticipated future marketplace.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.607
Threshold uncertainty score0.505

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.096
GPT teacher head0.361
Teacher spread0.265 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it