Total Cost of Ownership and Risk Analysis of Collaborative Implementation Models for Integrated Fiber-Wireless Smart Grid Communications Infrastructures
Bibliographic record
Abstract
Most previous total cost of ownership (TCO) studies give insight into the overall costs of various communications network architectures under the assumption of the traditional vertical integration model. However, it is necessary to take a closer look at the possibilities and gains achieved through collaboration. In this work, we develop a flexible, generic yet comprehensive TCO framework for the rollout of integrated fiber-wireless (FiWi) smart grid communications infrastructures. Further, we propose a novel collaborative implementation model for a shared infrastructure for both broadband access and smart grid communications. In addition, we take into account that buildings currently shift from a product to a service (i.e, renewable power supply) and exploit the idea that housing companies may collaborate by offering surplus renewable energy to communications network providers across interconnected smart microgrids. We study the impact of our implementation model on TCO and compare it with the vertical integration model. We also conduct a sensitivity analysis for the key cost parameters and analyze the risks related to solar power intermittency and random fiber cuts in terms of power service penalty, fiber cut related costs, and TCO.
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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 | 0.008 | 0.020 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 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 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".