A distributed system design for next generation storage and remote replication

• Main Authors: Maruthachalam, Dhanaraj, Mohanta, Taranisen, Swain, Amulya Ratna, Sethi, Hemendra Kumar
• Format: Conference Proceeding
• Language: English
• Subjects: Arrays; Cache memory; Cloning; distributed design; LDisk; Load management; LUN; NAS; remote replication; SAN; SCSI; storage; Storage area networks; thin-provision; Time factors
• DOI: 10.1109/ICADIWT.2014.6814686

The business continuity is essential for any enterprise application where remote replication enables customers to store the data on a Logical Disk (LDisk) at the local site and replicate the same at remote locations. In case of a disaster at local site, the replicated LDisk (remote copy) at remote site is marked as primary copy and the remote copy is made available without any downtime. The replication to destination is configured either in sync-mode or async-mode. In case of async-mode, the host IOs are first processed by the source array at the local site. A snapshot of the LDisk is triggered periodically and the new snapshot is replicated to the destination array at remote site. In this configuration, one particular node of source array becomes loaded with ongoing host IOs, snapshot, and replication activities. In the scale-out model, a storage array consists of multiple nodes and hence, the replication tasks and responsibilities can be distributed to a different node. We propose a cloning mechanism called DeltaClone, which replicates the incremental changes of LDisk across nodes. The ownership of a LDisk and its DeltaClone are assigned to two different nodes which are called as master node and slave node respectively. When the periodic request is triggered to synchronize the LDisk data with its remote copy, the current DeltaClone is frozen and it is then merged with remote copy. Hence, the replication tasks are carried out at slave node without affecting the performance of the master node and the ongoing host IOs. The slave node is re-elected periodically to ensure the dynamic load-balancing across the nodes. Our distributed design improves the overall storage performance and the simulation results showed that the proposed method outperforms the traditional methods.