Design of link layer protocols for error recovery in IP/CDMA2000 interconnections
Bibliographic record
Abstract
The behavior of wireless links in third generation wireless data systems based on cdma2000 standard have profound impacts on the performance of transport layer protocols. This is due to greater variations in round trip times(RTTs) experienced by the TCP agents. In this work we present an exhaustive study of the nature and impacts of the variable delays on wireless links caused due to error recovery through link-layer retransmissions. We identify the conditions under which sharp delay vari- ations and residual errors occur in presence of link layer recovery mecha- nisms and how they degrade the system performance and impact the TCP behavior. I. INTRODUCTION TCP and lacks much of the complexities of TCP. Also, these mod- els have been developed for independent (i.i.d.) frame errors only and developing similar models for correlated block errors is a com- plex process and simulations are the only means to address the need for an accurate model. On the other hand, in another approach (5), (4), an extensive model for TCP is used but the link-layer details are simplified by means of introducing delays of desired durations at de- sired intervals. Such an approach is an oversimplification of delay in- troduced due to error recovery through link-layer retransmissions and lacks analysis for a given frame error rate(FER) with specific fading- induced correlation structure. Previous works in this area have thus been marked by oversimplified models at either transport or the link layer. In this study we have developed a simulation tool for cdma2000 data network in widely used ns2(14) simulator. Our model(15) in- volves elaborate implementation of protocols like RLP, PPP and their integration with physical layer frame error models and transport layer protocols like TCP. In the following sections we will cover these pro- tocols and their implementations. Our extension to the simulator helps in an accurate and broader analysis of additional delays induced over wireless links due to link layer error recovery. The main focus of this paper is on an exact analysis of delay vari- ability due to link-layer retransmissions for various values of FERs with varying correlation structure and its impact on performance of upper layer protocols. We note that for modest levels of FERs with little correlation, frame losses are effectively handled by link-layer er- ror recovery mechanisms. We further observe that a smaller level of average FER with high degree of correlation produces similar through- puts as a high value of average FER with little correlation. We further derive conditions under which a high data rate supplemental channel may be assigned to a mobile based on its current FER and its tolerance for delay variability. In the following sections we first begin with de- scription of the network setup we are analyzing and then proceed on to our results at various layers of communication protocol stack.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".