MétaCan
Menu
Back to cohort
Record W2135544156

Modified application centric load balancing algorithm for satellite-based grids

2005· article· en· W2135544156 on OpenAlexaff
Brajendra K. Singh, Haresh S. Bhatt, A. K. Aggarwal

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicDistributed and Parallel Computing Systems
Canadian institutionsUniversity of Windsor
Fundersnot available
KeywordsComputer scienceLoad balancing (electrical power)Distributed computingGridGrid computingAlgorithmQuality of serviceSatelliteDistributed algorithmComputer networkEngineering
DOInot available

Abstract

fetched live from OpenAlex

Abstract:- A load balancing algorithm for a heterogeneous distributed computing environment attempts to improve the response time of a parallel or distributed application by ensuring optimum utilization of available resources. When the compute-resources are geographically dispersed, as is the case for grids, these resources may be connected through low speed satellite networks. Hence network delay for data transfer may become a significant factor in the load balancing strategy. In this paper, we have enhanced the application centric load balancing strategy to take network delay into consideration in satellite-based grid computing. The modified algorithm uses a static scheme for allocation of computer and network resources. This can satisfy the QoS requirements of applications on the grid. We have extensively analyzed and tested the performance of our algorithm. Key-Words:- Network delay, workload simulator, centralized static load balancing, satellite based grid

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)0.000
metaresearch head score (Gemma)0.001
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: Simulation or modeling
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.003
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.012
GPT teacher head0.240
Teacher spread0.228 · 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
GenreMethods

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

Citations1
Published2005
Admission routes1
Has abstractyes

Explore more

Same topicDistributed and Parallel Computing SystemsFrench-language works237,207