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Record W1967628564 · doi:10.1145/1008213.1008224

NC State scientists develop breakthrough internet protocol

2004· article· en· W1967628564 on OpenAlexaboutno aff
Injong Rhee

Bibliographic record

VenueComputers in entertainment · 2004
Typearticle
Languageen
FieldComputer Science
TopicDistributed and Parallel Computing Systems
Canadian institutionsnot available
Fundersnot available
KeywordsThursdayThe InternetComputer scienceProtocol (science)TelecommunicationsState (computer science)Library scienceWorld Wide Web

Abstract

fetched live from OpenAlex

Dear Editor-in-Chief, Researchers in North Carolina State University's Department of Computer Science have developed a new data transfer protocol for the Internet. The protocol is named BIC-TCP, which stands for Binary Increase Congestion Transmission Control Protocol. In a recent comparative study run by the Stanford Linear Accelerator Center (SLAC), BIC consistently topped the rankings in a set of experiments that determined its stability, scalability and fairness in comparison with other protocols. The study tested six other protocols developed by researchers from schools around the world, including the California Institute of Technology and the University College of London. Dr. Injong Rhee, associate professor of computer science, said BIC can operate, given appropriate medium, at speeds approaching 10 gigabits per second (Gbps) which is roughly 6,000 times that of DSL and 150,000 times that of current modems. While this might eventually translate into music downloads in the blink of an eye, the potential value of such a protocol is a real eye-opener. Rhee and NC State colleagues Dr. Khaled Harfoush, assistant professor of computer science, and Lisong Xu, postdoctoral student, presented a paper on their findings in Hong Kong at Infocom 2004, the 23rd meeting of the Institution of Electrical and Electronics Engineers Communications Society, on Thursday, March 11. Many national and international computing labs are now involved in large-scale scientific studies of nuclear and high-energy physics, astronomy, geology and meteorology. Typically, Rhee said, "Data are collected at a remote location and need to be shipped to labs where scientists can perform analyses and create high-performance visualizations of the data." Visualizations might include satellite images or climate models used in weather predictions. Receiving the data and sharing the results can lead to massive congestion of current networks, even on the newest wide-area high-speed networks such as ESNet (Energy Sciences Network), which was created by the U.S. Department of Energy specifically for these types of scientific collaborations. The problem, Rhee said, is the inherent limitations of regular TCP. "The current form of TCP was originally designed in the 1980s when Internet speeds were much slower and bandwidths much smaller," he said. "Now we are trying to apply it to networks that have several orders of magnitude more available bandwidth." Essentially, we're using an eyedropper to fill a water main. BIC, on the other hand, would open the floodgate. Along with postdoctoral student Xu, Rhee has been working on developing BIC for the past year, although Rhee said he has been researching network congestion solutions for at least a decade. The key to BIC's speed is that it uses a binary search approach -- a fairly common way to search databases -- that allows for rapid detection of maximum network capacities with minimal loss of information. "While it may take classical TCP two hours to reach the full capacity use of a 10 Gbps pipe with 100-millisecond round trip time, BIC needs only a few seconds," Rhee said. The greatest challenge for the new protocol, he added, was to fill the pipe fast without starving out other protocols. "It's a tough balance," he said. By allowing the rapid transfer of increasingly large packets of information over long distances, the new protocol could boost the efficacy of cutting-edge applications ranging from telemedicine and real-time environmental monitoring to business operations and multi-user gaming. At NC State, researchers could more readily visualize, monitor and control real-time simulations and experiments conducted at remote computing clusters. BIC might even help avoid a national disaster: The recent blackout that affected large areas of the eastern United States and Canada underscored the need to spread data-rich backup systems across hundreds of thousands of miles. With network speeds doubling roughly annually, Rhee said the performance demonstrated by the new protocol could become commonly available in high-speed networks in the next few years. Sincerely, Injong Rhee rhee@csc.ncsu.edu

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.012
metaresearch head score (Gemma)0.022
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.041
Threshold uncertainty score0.137

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0120.022
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.002
Science and technology studies0.0030.001
Scholarly communication0.0050.008
Open science0.0030.005
Research integrity0.0040.008
Insufficient payload (model declined to judge)0.0410.044

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 head0.013
GPT teacher head0.264
Teacher spread0.251 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

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

Citations0
Published2004
Admission routes1
Has abstractyes

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