Managing Heterogeneous Datacenters with Tokens

Abstract

Ensuring fairness in a system with scarce, preferred resources requires time sharing. We consider a heterogeneous system with a few "big" and many "small" processors. We allocate heterogeneous processors using a novel token mechanism, which frames the allocation problem as a repeated game. At each round, users request big processors and spend a token if their request is granted. We analyze the game and optimize users' strategies to produce an equilibrium. In equilibrium, allocations balance performance and fairness. Our mechanism outperforms classical, fair mechanisms by 1.7×, on average, in performance gains, and is competitive with a performance maximizing mechanism. CCS Concepts: • Software and its engineering → Power management; • Information systems → Data centers; • Social and professional topics → Pricing and resource allocation; • Theory of computation → Algorithmic mechanism design; • Computing methodologies → Modeling methodologies;

Token Bucket-based Throughput Constraining in Cross-layer Schedulers

“…Other schedulers, such as, MDU [7] and MDV [8] have a more elaborate utility function and are more difficult to characterize. The authors of [26] also employ a token system, but assume that users lie about their demands to strategically maximize their utility. In [27] constraints are applied to network slices of traffic aggregates in a 5G context, using an additive approach.…”