Loading [a11y]/accessibility-menu.js
Facilitating Workload Aware Storage Platform by Using Machine Learning Technics | IEEE Conference Publication | IEEE Xplore
Scheduled Maintenance: On Tuesday, 25 February, IEEE Xplore will undergo scheduled maintenance from 1:00-5:00 PM ET (1800-2200 UTC). During this time, there may be intermittent impact on performance. We apologize for any inconvenience.

Facilitating Workload Aware Storage Platform by Using Machine Learning Technics


Abstract:

In this paper, we present our proof-of-concept of a workload aware storage platform. The POC demonstrates the feasibility of building a machine learning technics facilita...Show More

Abstract:

In this paper, we present our proof-of-concept of a workload aware storage platform. The POC demonstrates the feasibility of building a machine learning technics facilitated middleware for storage management. The middleware is capable of providing optimal assignments of storage workloads to backends as well as continuously on-the-fly optimization thereafter. Experiment indicates that the proposed middleware can efficiently and dynamically adapt the storage backend to satisfy the SLA requirements with minimum impact on the workloads.
Date of Conference: 07-09 August 2017
Date Added to IEEE Xplore: 07 September 2017
ISBN Information:
Conference Location: Shenzhen, China

References

References is not available for this document.