Cost-aware triage improves xapp conflict handling in open ran
Cost-Aware Conflict Triage for xApp Control Conflicts in Open RAN
Networking and Internet Architecture
Summary
In Open Radio Access Networks, different control apps called xApps try to improve the network but can sometimes make conflicting changes that hurt performance. The authors introduce a method that not only detects these conflicts but also decides whether fixing them is worth the cost. Their system groups conflict events, estimates costs and benefits, and then chooses to fix, delay, or ignore the problem. This approach improves overall efficiency compared to always fixing conflicts immediately.
What this means in practice
- •For network operators: Optimize control conflict interventions among xApps to improve RAN performance without unnecessary fixes.
- •For telecom equipment vendors: Develop smarter RAN controllers that selectively mitigate conflicts based on estimated cost-benefit analysis.
Authors
Abdul Wadud, Fatemeh Golpayegani, Nima Afraz
Abstract
Open Radio Access Network (Open RAN) enables multi-vendor deployments where concurrent RAN control applications (xApps) independently optimise mobility, load, coverage, and energy within the Near Real Time RAN Intelligent Controller (Near-RT RIC). When xApps act on overlapping control parameters, their isolated loops produce conflicting decisions that degrade the network Key Performance Indicators (KPIs). Existing conflict-evaluation methods estimate severity but do not answer whether the intervention is cost-justified. This paper proposes a cost-aware conflict triage framework that pairs ECDF-based severity evaluation with an event-level decision layer. The framework groups detected conflict records into episodes, extracts nine features, estimates per-mechanism costs and benefits, and assigns one of three actions: tolerate, defer, or mitigate. Evaluated in a simulator-driven Open RAN setting over 30 Monte Carlo runs with four concurrent xApps, the framework defers 66.8 %, mitigates 19.8 %, and tolerates 13.4 % of detected episodes, achieving a mean net utility of 0.132 per intervention, 3.9x higher than an always-mitigate baseline, by avoiding low- value interventions through cost-aware selectivity.