Contiki-based IEEE 802.15.4 node's throughput and wireless channel utilization analysis
Bibliographic record
Abstract
In this paper, we analyse the impact of the Contiki Operating System (OS), and its Carrier Sense Multiple Access and Collision Avoidance (CSMA-CA) implementation on an IEEE 802.15.4 node's throughput and wireless channel utilization. The analysis is based on Contiki's Rime networking protocol stack, and its target is to determine an upper bound for the stated metrics. We explain that in Contiki with CSMA-CA as a MAC layer protocol, a node's throughput is limited to 8.1 kbps, at maximum, even without power saving features. In order to maximize a node's transmission capability, we modified Contiki's CSMA-CA implementation. A number of simulations are performed, and it is observed that with our modifications node throughput reaches 45 kbps, at maximum. Simulation results for estimating the channel capacity with our modified CSMA-CA MAC layer protocol show that the average per-node delay is low when the offered data load remains below 100 kbps. For an offered load of 100 kbps, the channel drops almost 20% of packets. Going beyond 100 kbps results in large latencies and significant packet loss. Results presented in this paper can serve as basis for the available bandwidth estimation in Wireless Sensor Networks (WSNs), QoS-based routing, and design of congestion control algorithm.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
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 teacher head, 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".