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tSIP: A Lightweight SIP-Based Messaging Protocol for Resource-Constrained Embedded Devices

2023· article· en· W4387486086 on OpenAlexaff
Haytham Khalil, Khalid Elgazzar

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicEmbedded Systems Design Techniques
Canadian institutionsOntario Tech University
Fundersnot available
KeywordsComputer scienceProtocol (science)Session Initiation ProtocolComputer networkEmbedded systemOperating systemServer

Abstract

fetched live from OpenAlex

Phone of Things (PoT) is a term recently coined in the Internet of Things (IoT) field. PoT extends the available connectivity options of IoT systems to include the ubiquitous phone network’s assets and infrastructure, leveraging them as a part of the IoT architecture. In this context, this paper proposes a constrained version of the Session Initiation Protocol (SIP), the dominant protocol used in VoIP communications. The proposed protocol, called tSIP, is a small-footprint messaging format that provides decentralized peer-to-peer communication between tSIP-enabled IoT devices. tSIP messages can also be mapped to the original SIP messages with the help of a proxy. tSIP promotes PoT and provides a standardized lightweight communication protocol between low-resource embedded IoT devices and the existing Unified Communications (UC) solution within the premises, allowing IoT devices to function as typical SIP endpoints in the VoIP ecosystem and facilitating their control and monitoring. The paper reviews the proposed tSIP messaging protocol regarding its architecture, encoding, and performance evaluation on embedded devices. The paper also gives use case scenarios for the proposed tSIP and discusses where its development will go in the future.

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 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)0.002
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: Not applicable · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.510
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0020.000
Research integrity0.0000.000
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 head0.046
GPT teacher head0.337
Teacher spread0.291 · 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 teacher head, not a consensus.

Study designNot applicable
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
Published2023
Admission routes1
Has abstractyes

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