Improving Reliability with Dynamic Syndrome Allocation in Intelligent Software Defined Data Centers

被引：2

作者：

Bayram, Ulya ^{[1
]}

Rozier, Eric W. D. ^{[1
]}

Divine, Dwight ^{[2
]}

Zhou, Pin ^{[3
]}

机构：

[1] Univ Cincinnati, Dept EECS, Cincinnati, OH 45221 USA

[2] Univ Illinois, Illinois Nat Hist Survey, Chicago, IL 60680 USA

[3] Datos IO Inc, San Jose, CA USA

来源：

2015 45TH ANNUAL IEEE/IFIP INTERNATIONAL CONFERENCE ON DEPENDABLE SYSTEMS AND NETWORKS | 2015年

关键词：

MEAN SHIFT; ERRORS;

D O I：

10.1109/DSN.2015.46

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

We propose new algorithms for implementing a software-defined data center (SDDC) to improve the dependability of storage systems without the addition of new hardware. We define the construction of a system that can predict its future resource requirements and act on these predictions to allocate overprovisioned resources to improve reliability. We introduce algorithms for implementing a smart SDDC (S2DDC) that characterizes user I/O transactions (writes and deletes), and use these models to predict the level of overprovisioning within a system, overbooking excess resources to improve reliability, while mitigating the impact on quality of service. We compare several implementations of our methods experimentally, and discuss methods for improving the fault-tolerance of our S2DDC, present experimental results showcasing our ability to improve system reliability showing the decrease in expected annual block loss due to disk failures and latent sector errors, and highlight the benefit of dependence based usage models in estimating overprovisioning.

引用

页码：219 / 230

页数：12