| Scenario | Recommended RSL | Reasoning | |----------|----------------|------------| | Streaming 4K video (train) | 0.8 | High volatility, need quick roam | | VoIP call (office) | 0.4 | Moderate, avoid mid-call handover | | Sensor node (factory) | 0.1 | Stability over reactivity | | Emergency responder | 0.95 | Always seek best link | | Idle smartphone | 0.2 | Save battery, no urgency | Correspondence: model@adaptive-systems.ai
Roaming Sensitivity Level, Handover Optimization, Context-Aware Computing, Mobility Management, Hysteresis Control. 1. Introduction Roaming—the process of transitioning a connection from one access point or service domain to another—is fundamental to mobile networks, IoT, and autonomous systems. Traditional roaming decisions rely on static thresholds (e.g., RSSI < -75 dBm triggers a scan). However, such rigidity fails in dynamic environments. Two identical signal drops may require opposite responses depending on user context, application sensitivity, or historical network reliability. roaming sensitivity level
Higher SVI → higher RSL → quicker roaming response. CCF ∈ [0,1] represents the penalty of premature roaming (e.g., re-authentication delay, data loss, monetary cost). For a video call, CCF is low (roaming is costly). For background sync, CCF is high (roaming is cheap). RSL is inversely related: ( RSL \propto (1 - CCF) ). 3.3 History-Dependent Hysteresis (HDH) HDH prevents ping-pong effects. Let ( R_past ) be the previous roaming time. Then: | Scenario | Recommended RSL | Reasoning |
[ SVI = \frac1N \sum_k=1^N-1 |Q(t_k+1) - Q(t_k)| ] Traditional roaming decisions rely on static thresholds (e
[ RSL(t) = \alpha \cdot SVI(t) + \beta \cdot (1 - CCF(t)) + \gamma \cdot HDH(t) ]