Paper Info
Title
SDRP: Safe, Efficient, and SLO-Aware Workload Consolidation Through Secure and Dynamic Resource Partitioning
Abstract
Workload consolidation is a widely-used technique to improve the resource utilization of services computing systems by consolidating latency-critical (LC) and batch workloads on the same physical server. The resource manager for workload consolidation dynamically allocates hardware resources (e.g., cores, caches) to the workloads to maximize the resource utilization while satisfying the service-level objective (SLO) of the LC workloads. Since security-critical hardware resources are dynamically allocated across consolidated workloads, information leakages can be created among workloads through microarchitectural side-channel (SC) attacks. Despite extensive prior works, it is yet to investigate efficient system software support for achieving high resource utilization without compromising the SLO and security of consolidated workloads. To bridge this gap, we propose SDRP, secure and dynamic resource partitioning for safe, efficient, and SLO-aware workload consolidation. As with the state-of-the-art techniques, SDRP dynamically allocates hardware resources to enhance the resource utilization and provide the SLO guarantees. In contrast to the state-of-the-art techniques, SDRP dynamically sanitizes security-critical hardware resources to robustly defeat microarchitectural SC attacks. Our quantitative evaluation demonstrates that SDRP achieves high resource sanitization quality, introduces low performance overheads, delivers high resource utilization with the SLO and security guarantees, and defeats the last-level cache (LLC)-based SC attack.
Year
DOI
Venue
2022
10.1109/TSC.2020.3024552
IEEE Transactions on Services Computing
Keywords
DocType
Volume
Resource partitioning,server consolidation,security,efficiency,service-level objective
Journal
15
Issue
ISSN
Citations 
4
1939-1374
1
PageRank 
References 
Authors
0.35
9
2
Name
Order
Citations
PageRank
Myeonggyun Han193.85
Woongki Baek240225.85