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Online Load Balancing for Distributed Control Plane in Software-Defined Data Center Network
Author(s) -
Shaojun Zhang,
Julong Lan,
Penghao Sun,
Yiming Jiang
Publication year - 2018
Publication title -
ieee access
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.587
H-Index - 127
ISSN - 2169-3536
DOI - 10.1109/access.2018.2820148
Subject(s) - aerospace , bioengineering , communication, networking and broadcast technologies , components, circuits, devices and systems , computing and processing , engineered materials, dielectrics and plasmas , engineering profession , fields, waves and electromagnetics , general topics for engineers , geoscience , nuclear engineering , photonics and electrooptics , power, energy and industry applications , robotics and control systems , signal processing and analysis , transportation
Distributed control plane is a common approach to improve the scalability of software-defined data center networks. However, learning how to balance the load among the controllers remains a difficult problem, since the flows in the network fluctuate frequently. In this paper, we propose an online controller load balancing (OCLB) scheme to address this issue. We first formulate the load balancing problem as an optimization problem to minimize the average controller response time. Then we decompose it into a sequence of switch migrations, with each migration aiming to reduce the average response time as much as possible based on the realtime request distribution. An OCLB algorithm is designed based on the derived optimality and termination conditions of switch migration, and is proved to be near optimal with a bounded competitive ratio. Evaluations demonstrate that our scheme can achieve near-optimal load balancing among the control plane in an online manner.

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