Performance Analysis of Floating Static Routes for Redundancy in Multi‑Router Networks
Bibliographic record
Abstract
This manuscript details the design, implementation, and quantitative performance analysis of a multi-router network utilizing static routing with floating static routes for redundancy, executed within the Cisco Packet Tracer 8.22 simulation environment. The study extends beyond basic configuration to empirically investigate the failover efficacy and convergence behavior of backup paths in response to link failures. The primary objective was to quantitatively measure the impact of floating static routes on network recovery time and reliability in a controlled, full-mesh topology connecting four distinct sites. A methodical, five-phase methodology was employed, encompassing device setup, primary and backup path configuration, comprehensive baseline verification, and controlled failure testing. Key performance metrics, including Round-Trip Time (RTT), packet loss, and crucially, network convergence time, were systematically collected. The results demonstrate successful automated failover, with an average network convergence time of approximately 2.2 seconds following a primary link failure, accompanied by minimal transient packet loss (4-6%). Baseline performance showed predictable latency proportional to hop count. The discussion contextualizes these findings within existing networking principles, confirming floating static routes as a functional, deterministic redundancy suitable for small-scale, stable network environments where administrative simplicity and control are prioritized. However, the analysis also critically acknowledges significant limitations, including the inherent constraints of the simulation environment, the scalability challenges of manual configuration, and the relatively slow convergence compared to dynamic routing protocols. The study concludes that while effective for specific use cases, the operational overhead of static routing limits its applicability in larger or dynamic networks. This work provides a validated, practical framework for understanding static routing redundancy and offers concrete performance data that can inform basic network design decisions. It also establishes a foundation for instructive comparative studies with dynamic routing protocols in educational contexts.
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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 | 0.006 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".