2018 article
Joint Virtual Machine Placement and Path Selection in a Virtualized Datacenter Environment
ICDCN'18: PROCEEDINGS OF THE 19TH INTERNATIONAL CONFERENCE ON DISTRIBUTED COMPUTING AND NETWORKING.
author keywords: Datacenter; Service Level Agreement; CPU Time; Uplink Bandwidth; Virtual Machine Placement; Path Selection
TL;DR:
This work designs a modified greedy approach that uses virtual machine placement and path selection to solve the joint resource allocation problem and designs a rigorous simulation setup to derive a definitive set of guidelines for the datacenter designer implementing the proposed SLA.
(via Semantic Scholar)
UN Sustainable Development Goal Categories
9. Industry, Innovation and Infrastructure
(Web of Science)
Source: Web Of Science
Added: February 4, 2019
Today's multi-tenant shared datacenter environments guarantee compute resources over a best-effort intra-datacenter network. Bursty traffic in such a network implies higher delays and losses for tenants. This may result in unpredictable network performance, potentially hurting the tenant's overall application performance. Motivated by these concerns, in this work we propose a Service Level Agreement (SLA) that along with compute capacity, explicitly guarantees intra-datacenter network bandwidth to the tenants in a virtualized, multi-tenant datacenter environment. We design a modified greedy approach that uses virtual machine placement and path selection to solve the joint resource allocation problem. In recent years, several algorithms have been proposed for resource allocation problems to meet a specific SLA. However they do not provide any practical recommendations for the realization of these solutions from a datacenter designer's standpoint. Another main contribution of our work is the design of a rigorous simulation setup to derive a definitive set of guidelines for the datacenter designer implementing the proposed SLA. The guideline answers questions of key practical importance to datacenter designers and enables derivation of effective estimates about the switch fabric and server capacity to be bought and installed, as a function of tenant demands.