Daniel Kunkle and Jiri Schindler.
This paper presents a load-balancing framework for high-performance clustered storage systems that offers a general method for reconfiguring a system facing dynamic workload changes.
The load balancing framework for high-performance clustered storage systems presented in this paper provides a general method for reconfiguring a system facing dynamic workload changes. It simultaneously balances load and minimizes the cost of reconfiguration. It can be used for automatic reconfiguration or to present an administrator with a range of (near) optimal reconfiguration options, allowing a tradeoff between load distribution and reconfiguration cost. The framework supports a wide range of measures for load imbalance and reconfiguration cost, as well as several optimization techniques. The effectiveness of this framework is demonstrated by balancing the workload on a NetApp Data ONTAP GX system, a commercial scale-out clustered NFS server implementation. The evaluation scenario considers consolidating two real world systems, with hundreds of users each: a six-node clustered storage system supporting engineering workloads and a legacy system supporting three email severs.
In Proceedings of the International Conference on High Performance Computing 2008 (HiPC ’08)
- A copy of the paper is attached to this posting.