Fairness-Efficiency Scheduling for Pay-as-you-go shared Caching systems with Long-term Fairness Guarantees

Pay-as-you-go caching systems are now widely used as storage services in cloud computing. However, users’ data caching requirements not only change over time, but also they are affected by workload characteristics, making it difficult to always ensure high efficient use of cache resources. Cache resource sharing is an effective way to improve the efficiency of cache usage. To incentivize users to share caches, it is essential to ensure long-term fairness among multiple users. However, traditional resource allocation strategies canonly guarantee memory less fairness among users,which is not applicable to long-term cache sharing systems. In this paper, we propose a fair allocation policy named FairCache for Pay-as-you-go cache resources. First, FairCache can satisfy four desirable properties of resource allocation: sharing incentive, pay-as-you-usefairness, strategy proofness, and pare to efficiency. Second, FairCache is an efficiency-fairness resource allocation policy based on the efficiency knob θ. The strategy keeps sensitive to the constantly changing cache demands of multiple users within the system by adjusting the efficiency knob θ, thus ensuring long-term multi-user fairness while maximizing the efficiency of cache usage. In addition, FairCache also has an anti-cheating mechanism to avoid possible free-rider problems when multiple users cache access files. Finally, this paper implements the FairCache policy in Alluxio. The experimental results show that FairCache is a lightweight scheduler and that it can maximize the efficiency usage of cache resources while ensuring the long-term for multiple users in the pay-as-you-go Cache systems fairness.