Efficient Orchestration of Data Centers Via Comprehensive and Application Aware Trade Off Exploration

Abstract

Software-defined network (SDN) orchestration, the problem of integrating and deploying multiple network control functions (NCFs)while minimizing suboptimal network states that can result from competing NCF proposals, is a challenging open problem. In this work, we formulate SDN orchestration as a multiobjective optimization problem, present an evolutionary algorithm designed to explore the NCF tradeoff space comprehensively and avoid local optima, and propose a new application-aware approach that explicitly models resource preferences of individual application workloads. Further, we propose a new logical application workload (LAW) abstraction to enable precomputation of the required relative positioning of an applications virtual machines (VMs) and allocation of these VMs in a single atomic step, leading to online algorithms that are one order of magnitude faster than existing solutions for placing data center workloads. For an instance of the SDN orchestration problem subject to four independent NCFs attempting to optimize network survivability, bandwidth efficiency, power conservation, and computational contention, we demonstrate that our approach enumerates a wider range of, and potentially better, solutions than current orchestrators, for data centers with hundreds of switches, thousands of servers, and tens of thousands of VM slots.

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Document Details

Document Type
Technical Report
Publication Date
Dec 01, 2016
Accession Number
AD1030686

Entities

People

  • Alan M. Bairley

Organizations

  • Naval Postgraduate School

Tags

Communities of Interest

  • Energy and Power Technologies
  • Engineered Resilient Systems

DTIC Thesaurus Topics

  • Algorithms
  • Computations
  • Computer Science
  • Computers
  • Data Centers
  • Energy Consumption
  • Evolutionary Algorithms
  • Genetic Algorithms
  • Heuristic Methods
  • Infrastructure
  • Multiobjective Optimization
  • Network Architecture
  • Optimization
  • Software Defined Networks
  • Throughput
  • Virtual Machines
  • Workload

Fields of Study

  • Computer science

Readers

  • Distributed Systems and Data Platform Development
  • Operations Research
  • Parallel and Distributed Computing.

Technology Areas

  • Space