AI & Machine Learning for Systems Management & Design Research Projects

Dynamic Backup

Dynamic Backup

Dynamic Backup Scheduler

This research focuses on cloud-scale backup systems where a single provider is offering services to a very large number clients, on the order of hundreds of thousands. The customers sign a Service Level Agreement (SLA) with the provider to define Service Level Objectives (SLOs) that specify the type of service expected for a given cost. Based on the SLOs and the budget, the intelligent system we are building constructs an optimized policy to satisfy the SLOs, including the backup frequency, the priority assignment for associated data flow operations, the selection of the restore scheme, resource allocations, and so on. Figure 7 is the basic backup environment used in the research.

Every client in the global backup system is self-interested, meaning that it is only concerned with its own benefits or losses. Consequently, designing an efficient and effective scheduler to perform scheduling and resource allocation for all of the various data flow operations requested by a vast number of clients is extremely challenging. The overall goal of this project is to design an efficient algorithm to manage the backup system so that it can meet the SLOs of every client at the lowest cost.