On fair scheduling in heterogeneous link aggregated services

Abstract

Provisioning quality of service (QoS) across an aggregate of transmission entities (e.g., link aggregation) or processing elements (e.g. network processors) is a challenging problem. The difficulty lies in simultaneously satisfying fairness to flows (with different bandwidth requirements) and ensuring minimized intra-flow reordering. This problem is crucial to many applications (that utilize parallel communication or processing paths) like multi-path load distribution, multi-path storage I/O, web service, data processing by network processors in the datapath of routers, transcoding multimedia flow traffic content over the Internet to name a few. We present two algorithms for multi-link systems that aim at reducing undesired reordering, ensure fair sharing of flows and optimal utilization of the links. Our algorithms are based on a new approach of dynamically partitioning flows among links. We perform simulations on real Internet traces to validate our algorithmic approach.