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Process migration

2000· review· en· 469 citations· W2294047952 on OpenAlex· 10.1145/367701.367728

Why is this work in the frame?

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

Canadian affiliationAn author listed a Canadian institution. This is the only route the usual frame has.

Full frame distilled prediction

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.

Candidate categories
Meta-epidemiology (narrow)
Consensus categories
none
Domain
Candidate signal: noneConsensus signal: none
Study design
Candidate signal: Other designConsensus signal: none
Genre
Candidate signal: ReviewConsensus signal: Review
Teacher disagreement score
0.996
Threshold uncertainty score
1.000
Validation status
machine_predicted_unvalidated · codex-gemma-dda1882f352a

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0040.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

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

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.

Opus teacher head0.056
GPT teacher head0.347
Teacher spread
0.291 · how far apart the two teachers sit on this one work
Validation status
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Abstract

Process migration is the act of transferring a process between two machines. It enables dynamic load distribution, fault resilience, eased system administration, and data access locality. Despite these goals and ongoing research efforts, migration has not achieved widespread use. With the increasing deployment of distributed systems in general, and distributed operating systems in particular, process migration is again receiving more attention in both research and product development. As high-performance facilities shift from supercomputers to networks of workstations, and with the ever-increasing role of the World Wide Web, we expect migration to play a more important role and eventually to be widely adopted. This survey reviews the field of process migration by summarizing the key concepts and giving an overview of the most important implementations. Design and implementation issues of process migration are analyzed in general, and then revisited for each of the case studies described: MOSIX, Sprite, Mach, and Load Sharing Facility. The benefits and drawbacks of process migration depend on the details of implementation and, therefore, this paper focuses on practical matters. This survey will help in understanding the potentials of process migration and why it has not caught on.

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.

The record

Venue
ACM Computing Surveys
Topic
Distributed systems and fault tolerance
Field
Computer Science
Canadian institutions
University of Toronto
Funders
not available
Keywords
Computer scienceProcess migrationImplementationProcess (computing)Software deploymentLocalityData migrationWorkstationDistributed computingProcess managementSoftware engineeringOperating system
Has abstract in OpenAlex
yes