An energy-efficiency assessment of Content Centric Networking (CCN)
Why this work is in the frame
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Bibliographic record
Abstract
Content-Centric Networking (CCN) is a recently proposed networking architecture that can potentially lead to reduced bandwidth usage and better scalability and security as compared to the current IP-based architecture. In this paper, we conduct an energy consumption analysis of content-centric networking and IP-based networking for a video streaming scenario. We consider two types of energy consumption: the energy required to manufacture the network devices and the energy required for operation. We perform simulations of content-centric networking over a general-tree topology to assess the traffic rate reductions achieved by CCN's insertion of caches at routers. Although CCN network devices have a higher intrinsic energy consumption compared to the IP-based devices because of the presence of additional memory, by exploiting their caching capabilities it is possible to reduce the overall energy consumption of the network. We consider both the incorporation of an online rate adaptation mechanism as well as a static network provisioning approach and observe that these approaches can lead to an energy consumption reduction of 10–20 percent.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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 it