Existing cloud computing platforms offer virtually unlimited compute resources (virtual machines, bandwidth, storage, etc.) that can be used on demand. Such on-demand model offers significant elasticity to the customers in terms when and where they use the resources. The existing pricing model, however, is pay-as-you-go which in turn can lead to unpredictable costs to the cloud customers. This talk will discuss two adaptive approaches for resource control under a fixed budget: Distributed Rate Limiting (DRL) and Temporal Rate Limiting (TRL). DRL is a fully decentralized mechanism for resource control over a distributed cloud service, that splits the available budget among the participating nodes subject to the load each node experiences. TRL in contrast, splits the budget over a time period, to optimize the performance of the customer with demand pattern that varies in time.
Talk followed by a Q&A Session.
The conference will be conducted in English