Server-storage virtualization: Integration and load balancing in data centers

TLDR

Such data centers form a key building block for new cloud computing architectures. The study designs an agile data center with integrated server and storage virtualization and proposes the VectorDot load‑balancing algorithm to address hierarchical, multi‑dimensional resource constraints. The authors implement the VectorDot algorithm—based on the Toyoda multi‑dimensional knapsack approach—within an integrated server‑storage virtualization platform and evaluate it on synthetic and real data‑center testbeds using VMware ESX, IBM SAN Volume Controller, and Cisco/Brocade switches. Experiments show the system’s end‑to‑end validity and that VectorDot efficiently eliminates overloads on server, switch, and storage nodes.

Abstract

We describe the design of an agile data center with integrated server and storage virtualization technologies. Such data centers form a key building block for new cloud computing architectures.We also show how to leverage this integrated agility for non-disruptive load balancing in data centers across multiple resource layers - servers, switches, and storage. We propose a novel load balancing algorithm called VectorDot for handling the hierarchical and multi-dimensional resource constraints in such systems. The algorithm, inspired by the successful Toyoda method for multi-dimensional knapsacks, is the first of its kind. We evaluate our system on a range of synthetic and real data center testbeds comprising of VMware ESX servers, IBM SAN Volume Controller, Cisco and Brocade switches. Experiments under varied conditions demonstrate the end-to-end validity of our system and the ability of VectorDot to efficiently remove overloads on server, switch and storage nodes.