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Record W2483223866

Biologically inspired peer-to-peer distributed file system

2006· article· en· W2483223866 on OpenAlexaff
Sergio Camorlinga

Bibliographic record

VenueMspace (University of Manitoba) · 2006
Typearticle
Languageen
FieldComputer Science
TopicDistributed and Parallel Computing Systems
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsComputer scienceWorkaroundPeer-to-peerDistributed computingFile sharingReplication (statistics)World Wide WebThe InternetProgramming language
DOInot available

Abstract

fetched live from OpenAlex

A fundamental problem in the current second generation of Peer-to-Peer algorithms and applications is that they are based on schemes and models that have predetermined, predefined centralized and distributed techniques. The majority of second-generation Peer-to-Peer systems assume stable environments. Workarounds are commonly used to fix them. However, when subject to dynamic contexts, the algorithms and applications are brittle, unscalable, and limited to continue providing services. A Peer-to-Peer Distributed File System, as an application developed on top of a Peer-to-Peer system, inherits second-generation Peer-to-Peer drawbacks, unless special workarounds are provided. The Peer-to-Peer Distributed File System has limitations to manage its distributed file services effectively in decentralized, self-organized, ad-hoc environments. This thesis tackles these problems by first presenting a new computing paradigm called the Emergent Thinker and then applying the Emergent Thinker to design and develop a Biologically Inspired Peer-to-Peer Distributed File System. As a collateral contribution, the thesis provides a paradigm and a methodology that can be used to provide Systems Research a new approach to solve distributed systems problems. The thesis introduces the Emergent Thinker paradigm, an area-wide logical computing entity, named after a philosopher that continuously analyses information and has emergent computed solutions for new and/or existing requests. The Complex Adaptive System (CAS) emergent computation model and the CAS propagation model are proposed as mechanisms to achieve the Emergent Thinker. The Thinker is intended as an alternative approach for new and current design and implementation challenges in systems research. The Biologically Inspired Peer-to-Peer Distributed File System (BPD) implements the Emergent Thinker paradigm. The BPD design and implementation is the major thesis contribution. The biological inspiration comes from the natural and biological models used in the implementation of the CAS that form the basis of its services. The BPD provides file system services in a complex information system environment that is dynamic, self-organized, ad hoc and decentralized. (Abstract shortened by UMI.)

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.

How this classification was reachedexpand

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.812
Threshold uncertainty score0.813

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.013
GPT teacher head0.188
Teacher spread0.175 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2006
Admission routes1
Has abstractyes

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