S-CDA: A Smart Cloud Disk Allocation Approach in Cloud Block Storage System

Cloud disk provided to users by cloud providers has been a prevalent form of cloud storage. Assigning disk storage space for cloud disks among available data warehouses remains a challenging task, as the load characteristics of cloud disks are not known at the time of disk creation. Methods considering only subscribed capacity could be prone to result in resource under-utilization and load imbalance among warehouses. We propose a Smart Cloud Disk Allocation (S-CDA) approach, which uses clustering and classifying to predict the load information for new cloud disks, and then realizes multi-dimensional allocation based on Manhattan distance. Experimental results with realistic cloud workloads show that, compared with the existing one-dimensional allocation scheme, S-CDA increases the overall space/MPS/disk bandwidth utilization, while decreasing the load imbalance.