Evaluating QoS in SDN-Based EPC: A Comparative Analysis
Bibliographic record
Abstract
Software Defined Networking (SDN) is an emerging paradigm in networking and of high interest to the mobile network operators due to its potential benefit in improving network performance. The idea of integrating SDN in mobile network architecture, such as in LTE-evolved packet core (EPC), has already been proposed by many researchers. The SDN-based EPC network offers better Quality of Service (QoS) which is critical to the successful delivery of real-time multimedia applications in the mobile operator networks. In this paper, we provide state-of-the-art work to evaluate and analyze the QoS metrics in real-time services. We conduct a comprehensive comparison between the performance of EPC and SDN-based EPC regarding latency, jitter, and packet loss. We inject active probe packets in the networks to collect statistical data about the metrics. Various levels of workload are applied to test the robustness and stability of both EPC and SDN-based EPC designs. Our results show that SDN-based EPC significantly outperforms its legacy counterpart in all three QoS metrics. To the best of our knowledge, our study is the first comparative analysis that evaluates QoS in EPC and SDN-based EPC for real-time applications.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| 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".