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Record W2949886190 · doi:10.22215/etd/2014-11043

Utility-Based Packet Scheduling and Resource Allocation Algorithms with Heterogeneous Traffic for Wireless OFDMA Networks

2014· dissertation· en· W2949886190 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

Venuenot available
Typedissertation
Languageen
FieldEngineering
TopicAdvanced Wireless Network Optimization
Canadian institutionsCarleton UniversityUniversity of Toronto
FundersMinistero dello Sviluppo Economico
KeywordsComputer scienceNetwork packetScheduling (production processes)Quality of serviceComputer networkAlgorithmWireless networkDistributed computingWirelessReal-time computingMathematical optimization

Abstract

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The focus of this dissertation is on studying various packet scheduling and resource block (RB) allocation algorithms, for a variety of flow requirements, heterogeneous traffic, and architecture, in wireless OFDMA networks.In the second chapter, we investigate packet scheduling and RB allocation algorithms for realtime (RT) and non-realtime (NRT) packet-switched flows. We start by specifying different quality-of-service (QoS)-requirements for RT \& NRT flows and present different packet scheduling and RB allocation algorithms (including known cores and novel cores) based on the bit-rate driven utilities and the delay driven disutilities. We, then, summarize the machinery for attaining different fairness and QoS-requirements in a pair of classification tables (including a novel intuitive decomposition).When considering RT and NRT flows together, the commonly-used approach is the one based on performing two sequential algorithms of RT and NRT flows. This approach cannot exploit the potent existent multiuser diversity, in wireless OFDMA networks. In the third chapter, we propose a novel unified disutility minimization, in a common pool of RBs. Since the packet scheduling and RB allocation algorithms have taken place for RT and NRT flows from a common pool of RBs (without static priority separation), the overall spectral efficiency is increased. The novel formulations are used to devise computationally-efficient packet scheduling and RB allocation algorithm that surpass baseline algorithms. We also develop a novel general model for input-output bit-rate behaviour in packet scheduling and RB allocation of the heterogeneous traffic. This model sheds light on identifying different input load regions and understanding of the system in a simple intuitive manner.When it comes to providing very high bit-rate coverage, wireless networks require cost-effective radio access network (RAN) devices, such as multiuser enabled amplify-and-forward (AF) relays, with proper fair packet scheduling and RB allocation algorithms. These relays are cost-effective, simpler to implement, and introduce less delay in comparison to other relay based routers. In the fourth chapter, we develop novel fair packet scheduling and RB allocation algorithms in this kind of OFDMA based AF relays.Finally, we discuss a number of interesting research topics, as future directions, in the last chapter.

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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 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: none
Teacher disagreement score0.822
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
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 head0.007
GPT teacher head0.216
Teacher spread0.209 · 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

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Citations1
Published2014
Admission routes1
Has abstractyes

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