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Record W2130633327 · doi:10.1109/services-2.2008.10

A Middleware Solution to Monitoring Composite Web Services-Based Processes

2008· article· en· W2130633327 on OpenAlexaff
Farhana Zulkernine, Patrick Martin, Kirk Wilson

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicService-Oriented Architecture and Web Services
Canadian institutionsQueen's University
Fundersnot available
KeywordsComputer scienceMiddleware (distributed applications)Service-level agreementBusiness processService level objectiveWeb serviceOutsourcingProcess managementService levelService providerService (business)Process (computing)Quality of serviceDatabaseService designWorld Wide WebComputer networkBusinessOperating systemWork in process

Abstract

fetched live from OpenAlex

Web services can be composed to create complex business processes that span multiple organizations. quality of service (QoS) of such a process is guaranteed by a set of service level agreements (SLAs) between the service providers and the service consumers. Monitoring is required at every service provider and at the service consumer end in order to ensure satisfaction of the SLAs. Distributed monitoring of business processes can be complex and costly. We propose a middleware solution, namely the performance monitor (PM) framework, to enable outsourcing of the task of SLA monitoring of both intra and inter-organizational composite Web service processes. We present a prototype implementation of the PM with experimental data to establish the effectiveness of the framework in monitoring and verifying SLAs for a composite process and discuss possible extensions to the framework for more generalized applications.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.001
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.017
GPT teacher head0.232
Teacher spread0.215 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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

Citations11
Published2008
Admission routes1
Has abstractyes

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