An application aware approach to scalable online placement of data center workloads
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Authors
Bairley, Alan
Xie, Geoffrey G.
Subjects
Software-Defined Networking
Network State
Datacenter Network
Genetic Algorithms
Network State
Datacenter Network
Genetic Algorithms
Advisors
Date of Issue
2016-12-16
Date
December 16, 2016
Publisher
Monterey, California. Naval Postgraduate School
Language
Abstract
Data center operators strive for maximum resource utilization while satisfying tenant service level agreements; however, they face
major challenges as application workload types are diverse and tenants add, remove, and update their workloads sporadically to
meet changing user demands.Currently, operators allocate workload VMs primarily in an application agnostic fashion, focusing on
minimizing total resource usage.In this work, we first show that such allocations can be suboptimal and then present a new application
aware approach that explicitly models resource preferences of individual workloads.Further, we propose a new logical application
workload (LAW) abstraction to enable precomputation of the required relative positioning of an application’s VMs and allocation of
these VMs in a single atomic step, leading to online algorithms that are one order of magnitude faster than existing per VM placement
solutions.We then develop a statistical extension of LAW to add flexibility in characterizing application requirements and to support
prioritization of workloads.Using realistic workload traces and physical topologies, we evaluate our algorithms in a simulated largescale
data center setting, and demonstrate their performance advantages and potential tradeoffs versus existing solutions.
Type
Technical Report
Description
Series/Report No
Department
Computer Science (CS)
Organization
Meteorology (MR)
Graduate School of Engineering and Applied Science (GSEAS)
Identifiers
NPS Report Number
NPS-CS-16-003
Sponsors
Office of the Department of Defense Chief Information Officer 6000 Defense Pentagon Washington, D.C. 20301-6000
Funder
Department of Defense Information Assurance Scholarship Program (DoD IASP).
Format
Citation
Distribution Statement
Approved for public release; distribution is unlimited.
Rights
This publication is a work of the U.S. Government as defined in Title 17, United States Code, Section 101. Copyright protection is not available for this work in the United States.