Adaptive Budget- and Risk-Aware Index Scheduling of Background Data Exchange in Mobile Systems

A. M. Panyushkin, R. A. Slesarev

Abstract


ABRIS, an adaptive budget- and risk-aware index scheduler with a per-slot session cost, is proposed for background data exchange in mobile systems. The study addresses the need to reconcile task deadlines with channel variability, radio energy consumption, and metered-traffic limits. Its novelty lies in jointly using two virtual resource queues, a local scenario-based CVaR indicator, a task index, and a nonnegative transmission-activation threshold. The method is derived from a drift-plus-penalty bound. Index sorting is proved exact for divisible transfers, while an additive gap is bounded for quantized transfers. The implementation matched dynamic programming on 2,000 discrete instances. Across 64 paired seven-day simulations, the difference relative to an OPERA-type controller was −6,847 ± 181 J, −2,890 ± 78 MB, and −0.0245 ± 0.0282 percentage points of missed deadlines. Relative to a static policy, the differences were +126 ± 71 J, +47 ± 27 MB, and −0.0395 ± 0.0321 percentage points. Under network stress, the local indicator reduced misses by 0.0403 ± 0.0207 percentage points at a cost of 35 ± 9 J. The theoretical guarantee concerns the surrogate cost, whereas the numerical conclusions concern the specified computational model. The method is intended for lightweight on-device scheduling after hardware-specific calibration.


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