Multipath Transmission for Wireless Internet Access--From an End-to-End Transport Layer Perspective
Bibliographic record
Abstract
With the growing demand of Internet services, network operators have put significant efforts to improve network error resilience and efficiency. Since there exist different wired/wireless technologies for Internet access such as digital subscriber line (DSL), Ethernet, and worldwide interoperability for microwave access (WiMax), a mobile host can use multiple access networks simultaneously with multipath transmission. Taking the advantage of heterogeneous environment, multipath transmission through the Internet can improve service reliability and network flexibility. Ensuring a reliable end-to-end connection-oriented communication with satisfactory quality of service (QoS) and maintaining congestion control and flow control are the main responsibilities of the Transmission Control Protocol (TCP), the dominant transport layer protocol in the Internet. In this paper, we survey the state-of-the-art of multipath transmission techniques for QoS provisioning in wireless Internet access, focusing on the end-to-end transport layer protocols. The main challenges for the design of multipath TCP are reviewed, and the existing transport layer congestion control schemes are categorized. Multipath TCP and stream control transmission protocol (SCTP)-based transport layer protocols are discussed, and their limitations and/or impractical assumptions are addressed. Open research issues on the development of an effective, efficient, and practical multipath TCP protocol are summarized.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".