End-to-End Delay Bounds for Traffic Aggregates under Guaranteed-Rate Scheduling Algorithms

This paper evaluates, via both analysis and simulation, the end-to-end (e2e) delay performance of aggregate scheduling with guaranteed-rate (GR) algorithms. Deterministic e2e delay bounds for a single aggregation are derived under the assumption that all incoming flows at an aggregator conform to the token bucket model. Each aggregator can use any of three types of GR scheduling algorithms: stand-alone GR, twolevel hierarchical GR, and rate-controlled two-level hierarchical GR. We also derive an e2e delay bound for the case of multiple aggregations when the rate-controlled two-level hierarchical GR is used at aggregators. By using the GR scheduling algorithms to handle traffic aggregates, we show not only the existence of delay bounds, but also the fact that under certain conditions (e.g., when the aggregate traverses a long path after the aggregation point) the bounds are even tighter than that of per-flow scheduling. We then compare the analytic delay bounds numerically, and conduct in-depth simulation to (i) confirm the analytic results, and (ii) compare the e2e delays of aggregate and per-flow scheduling. The simulation results have shown that aggregate scheduling is very robust and can take advantage of statistical multiplexing gains. It performs better than per-flow scheduling in most simulation scenarios we considered