MétaCan
Menu
Back to cohort
Record W4250251176 · doi:10.1002/wcm.465

Introducing reliability and load balancing in mobile IPv6‐based networks

2006· article· en· W4250251176 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

VenueWireless Communications and Mobile Computing · 2006
Typearticle
Languageen
FieldEngineering
TopicIPv6, Mobility, Handover, Networks, Security
Canadian institutionsNortel (Canada)
Fundersnot available
KeywordsComputer scienceMobile IPComputer networkLoad balancing (electrical power)IPv6Node (physics)Distributed computingReliability (semiconductor)WorkloadMobile computingOperating systemThe Internet

Abstract

fetched live from OpenAlex

Abstract Mobile IPv6 is an enabling platform for creating IP mobility in the evolution path towards next generation service offerings. However, Mobile IPv6 does not provide reliability and load balancing in the network. In this paper, we introduce ‘Virtual HA Reliability Protocol.’ It is an extension to Mobile IPv6 that introduces reliability and load balancing in the Mobile IPv6‐based networks. It also provides solutions to the problems caused due to Home Agent failures in Mobile IPv6. These problems are: delayed failure detection, service interruption in the upper layer applications, increased workload on the Mobile Node, message overhead over the air interface, and IPsec Security Associations re‐establishment. We also present the results of several experiments to assess the performance of our solution. The results show that our solution provides transparent Home Agent failure detection and recovery mechanisms. As a result, there is a significant reduction in message exchange over the air interface. Also, our solution provides high service availability in the upper layer applications. Moreover, there is reduced workload on the Mobile Node. Finally, the load balancing mechanism of our solution provides efficient, dynamic, and transparent load balancing among the multiple Home Agents. Thus our solution improves the overall Mobile IPv6 and upper layer applications performance. Copyright © 2006 John Wiley & Sons, Ltd.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.084
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 science0.0000.001
Research integrity0.0000.001
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 head0.005
GPT teacher head0.219
Teacher spread0.214 · 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