{"ID":2842191,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2511.10146","arxiv_id":"2511.10146","title":"Dynamic Edge Server Selection in Time-Varying Environments: A Reliability-Aware Predictive Approach","abstract":"Latency-sensitive embedded applications increasingly rely on edge computing, yet dynamic network congestion in multi-server architectures challenges proper edge server selection. This paper proposes a lightweight server-selection method for edge applications that fuses latency prediction with adaptive reliability and hysteresis-based handover. Using passive measurements (arrival rate, utilization, payload size) and an exponentially modulated rational delay model, the proposed Moderate Handover (MO-HAN) method computes a score that balances predicted latency and reliability to ensure handovers occur only when the expected gain is meaningful and maintain reduced end-to-end latency. Results show that MO-HAN consistently outperforms static and fair-distribution baselines by lowering mean and tail latencies, while reducing handovers by nearly 50% compared to pure opportunistic selection. These gains arise without intrusive instrumentation or heavy learning infrastructure, making MO-HAN practical for resource-constrained embedded devices.","short_abstract":"Latency-sensitive embedded applications increasingly rely on edge computing, yet dynamic network congestion in multi-server architectures challenges proper edge server selection. This paper proposes a lightweight server-selection method for edge applications that fuses latency prediction with adaptive reliability and h...","url_abs":"https://arxiv.org/abs/2511.10146","url_pdf":"https://arxiv.org/pdf/2511.10146v1","authors":"[\"Jaime Sebastian Burbano\",\"Arnova Abdullah\",\"Eldiyar Zhantileuov\",\"Mohan Liyanage\",\"Rolf Schuster\"]","published":"2025-11-13T10:00:11Z","proceeding":"cs.DC","tasks":"[\"cs.DC\",\"cs.NI\"]","methods":"[]","has_code":false}