Fair-queuing schedulers provide clients with bandwidth or latency guarantees provided they are well-behaved i.e. the requested service is always within strict predefined limits. Violation of the service bounds results in nullification of the performance guarantees of the misbehaving client. In this paper we relax this notion of good behavior and present a generalized service model that takes the current system load into consideration. Consequently clients may opportunistically consume more than their contracted service without losing future performance guarantees, if doing so will not penalize well-behaved clients. We present a new algorithm RFQ (Redemptive Fair Queuing) along with a generalized traffic model called the Deficit Token Bucket (DTB). RFQ incorporates the notion of redemption, whereby a misbehaving client may be rejuvenated and regain its performance guarantees. We characterize the conditions for rejuvenating a client, and prove that RFQ meets its performance guarantee...
Ajay Gulati, Peter J. Varman