Simple receding horizon approach to scheduling mobile wireless clients with uncertainty

A key challenge in planning is how to schedule under uncertainty. We consider scheduling communications to dispersed wireless clients sharing a hub over a period of time in a dynamic environment. Scheduling under uncertainty research has produced either complex or unsatisfactory solutions for this problem. This paper develops a simple receding horizon linear program to allocate times for client specific traffic in order to realistically maximize client throughput. Given future uncertainty it considers clients´ (estimated) future rates and loads and aggregates them utilizing various permutations. For the scenario we present, the simplest receding horizon approach using only two time intervals can perform within 3.4 percentage points of the optimal whereas a greedy approach can only achieve within 13 percentage points of the optimal. The aggregation over many periods minimizes the variations due to uncertainty and greatly simplifies the problem while providing good performance. This result can be extended to many other scheduling with uncertainty type scenarios.