Pluginizing QUIC

Coninck, Quentin De; François, Michel; Piraux, Maxime; Rochet, Florentin; Given-Wilson, Thomas; Legay, Axel; Pereira, Olivier; Bonaventure, Olivier

doi:10.1145/3341302.3342078

Cited by 67 publications

(42 citation statements)

References 58 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…They also fear that both the initial implementation and its later maintenance entail a considerable time investment. This is somewhat contradicted by our own experiences: our qlog integration in PQUIC [28] is isolated and made flexible so that additional plugins can easily inject new events ( §3.4).…”

Section: Qlog and Qvis Usage In Practicementioning

confidence: 96%

“…Others mention finding bugs in QUIC's retransmission logic during its complex handshake. While developing PQUIC [28], we ourselves found the network emulation tool "mininet" to queue up an infinite amount of packets when using the default settings (ignoring the max_queue_size parameter). This was visible as a slow start phase and an ever-increasing RTT spanned the entire transfer.…”

Section: Congestion Controlmentioning

confidence: 99%

“…To this end, when developing the Multipath extension in our Pluginized QUIC (PQUIC) implementation [28], we have leveraged qlog's flexibility and substantially extended it. We added custom qlog events for the new multipath-related state and re-scoped existing connection-level events to the path level by adding a "uniflow ID".…”

Section: Multipath Quicmentioning

confidence: 99%

“…Spread over 440 pages in ten documents [86], the protocols are challenging to understand and implement. In 2018, by working on our own implementations [28,57,67], it became evident that the QUIC community would need extensive tooling to help debug and validate their systems. These tools would ideally be re-usable across codebases, in turn requiring a common input data format.…”

mentioning

confidence: 99%

See 3 more Smart Citations

Debugging QUIC and HTTP/3 with qlog and qvis

Marx

Piraux

Quax

et al. 2020

Proceedings of the Applied Networking Research Workshop

Self Cite

View full text Add to dashboard Cite

The QUIC and HTTP/3 protocols are powerful but complex and difficult to debug and analyse. Our previous work proposed the qlog format for structured endpoint logging to aid in taming this complexity. This follow-up study evaluates the real-world implementations, uses and deployments of qlog and our associated qvis tooling in academia and industry. Our survey among 28 QUIC experts shows high community involvement, while Facebook confirms qlog can handle Internet scale. Lessons learned from researching 16 QUIC+HTTP/3 and five TCP+TLS+HTTP/2 implementations demonstrate that qlog and qvis are essential tools for performing root-cause analysis when debugging modern Web protocols. CCS CONCEPTS • Networks → Transport protocols; Protocol testing and verification; Network protocol design.

show abstract

Section: Qlog and Qvis Usage In Practicementioning

confidence: 96%

Section: Congestion Controlmentioning

confidence: 99%

Section: Multipath Quicmentioning

confidence: 99%

mentioning

confidence: 99%

See 2 more Smart Citations

Debugging QUIC and HTTP/3 with qlog and qvis

Marx

Piraux

Quax

et al. 2020

Proceedings of the Applied Networking Research Workshop

Self Cite

View full text Add to dashboard Cite

show abstract

“…They have a propensity to induce allergies and granulomas, particularly bovine collagen whereas human and porcine collagens are better tolerated. These adverse effects are commonly temporary until all collagen has been resorbed, but one patient developed stone-hard granulomas not disappearing with any treatment over more than a decade (De Coninck, 2008). Usually, the granulomas are palisaded around amorphous eosinophilic material representing bovine collagen.…”

Section: Soft Tissue Fillersmentioning

confidence: 99%

Adverse effects of fillers

Haneke

2018

Dermatologic Therapy

View full text Add to dashboard Cite

Filler injections belong to the most frequently performed noninvasive beautifying procedures. When done correctly they are generally well tolerated. However, a number of factors, such as poor filler quality, and particularly host as well as user dependent filler reactions may lead to unwanted effects. These may be early, late, or delayed events with characteristics for each of them. Temporary fillers almost invariably cause temporary side effects whereas those of permanent fillers may last forever. Some fillers are notorious for their poor safety profile; for example, silicone is banned in the European Union and the United States but nevertheless used by many practitioners and beauticians. Many fillers can be identified in histopathologic sections allowing specific measures to be instituted.

show abstract

Science gateway adoption using plug‐in middleware for evidence‐based healthcare data management

Oruche

Milman

Alarcon

et al. 2022

Concurrency and Computation

View full text Add to dashboard Cite

There is a growing need for next-generation science gateways to increase the accessibility of emerging large-scale datasets for data consumers (e.g., clinicians, researchers) who aim to combat COVID-19-related challenges. Such science gateways that enable access to distributed computing resources for large-scale data management need to be made more programmable, extensible, and scalable. In this article, we propose a novel socio-technical approach for developing a next-generation healthcare science gateway, namely, OnTimeEvidence that addresses data consumer challenges surrounding the COVID-19 pandemic related data analytics. OnTimeEvidence implements an intelligent agent, namely, Vidura Advisor that integrates an evidence-based filtering method to transform manual practices and improve scalability of data analytics. It also features a plug-in management middleware that improves the programmability and extensibility of the science gateway capabilities using microservices. Lastly, we present a usability study that shows the important factors from data consumers' perspective to adopt OnTimeEvidence with chatbot-assisted middleware support to increase their productivity and collaborations to access vast publication archives for rapid knowledge discovery tasks. K E Y W O R D Sdiffusion of innovations, intelligent agents, intelligent middleware, microservices, science gateways INTRODUCTIONManaging the emerging collections of large-scale medical datasets such as scientific publications and electronic health records (EHRs) can be a challenging task for medical data consumers (e.g., clinicians, medical researchers) who need to make timely decisions for combating COVID-19-related issues. Data consumers are constantly faced with complex tasks that are labor-intensive and require domain-specific knowledge discovery over medical information for critical decision making. When synthesizing scientific literature for knowledge discovery, data consumers often rely clinical methodologies such as levels of evidence 1,2 to improve information reliability and reduce the quantity of literature by prioritizing scientific rigor (e.g., expert opinions to systematic reviews and meta-analyses). The challenge of manually filtering high-volume of literature based on evidence-based methods presents the need from data consumers to adopt next-generation science gateways to gain access to emerging large-scale datasets and resources for developing timely pandemic-related solutions.Any opinions, findings, and conclusions or recommendations expressed in this publication are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.

show abstract

Pluginizing QUIC

Cited by 67 publications

References 58 publications

Debugging QUIC and HTTP/3 with qlog and qvis

Debugging QUIC and HTTP/3 with qlog and qvis

Adverse effects of fillers

Science gateway adoption using plug‐in middleware for evidence‐based healthcare data management

Contact Info

Product

Resources

About