MFAP: Fair Allocation between fully backlogged and non-fully backlogged applications

Yan Sui, Chun Yang, Dong Tong, Xianhua Liu, Xu Cheng
2016 2016 IEEE 34th International Conference on Computer Design (ICCD)  
In this paper, we consider the problem of ensuring fairness in systems serving a mixture of fully backlogged applications, which continuously demand resources, and nonfully backlogged applications. We introduce a fairness metric, called interference fairness, the basic idea underlying which is that the interference caused by application A for another application B should be equal to that caused by B for A. To effectively and efficiently guarantee this fairness metric, we propose Mutual Fair
more » ... ose Mutual Fair Allocation Policy (MFAP), a simple and powerful resource sharing policy, and show how it guarantees interference fairness between any pair of applications. We also show that MFAP, unlike other viable policies, satisfies several highly desirable properties, including some from game theory, as well as common sense intuitions. As a use case, we implemented MFAP on a disk scheduling framework. The experimental results based on synthetic and real workloads show how our implementation achieved interference fairness and improved non-fully backlogged applications performance.
doi:10.1109/iccd.2016.7753343 dblp:conf/iccd/SuiYTLC16 fatcat:jivgndd2hngqbn7tcsd3yjpxjq