Fair Resource Allocation with Source-Side Throttling and FCFS Destination-Side Servicing
This project demonstrates a proof-of-concept approach for addressing performance isolation, QoS, and device capacity constraints in multi-tenant cloud environments using a unified linear programming model.
Abstract
Performance isolation remains challenging in multi-tenant cloud storage. In private clouds like VMware vSAN, virtual disks striped over shared devices cause congestion, especially during bursts.
We propose a lightweight, non-intrusive resource allocation mechanism that eliminates reliance on single bottleneck controllers or specialized device features.
Our design schedules per-VM I/Os using hypervisor throttling, preserving FCFS servicing at devices. A unified linear programming formula runs in a feedback loop to solve optimal IOPS rates per virtual disk, maximizing throughput under QoS and device capacity constraints.
Simulations show effective I/O throttling, burst traffic isolation at the source, reduced destination congestion, and significantly lower end-to-end latency.
Available at GitHub.