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Published in: Mobile Networks and Applications 1/2020

03-01-2019

WECAN: an Efficient West-East Control Associated Network for Large-Scale SDN Systems

Authors: Haisheng Yu, Heng Qi, Keqiu Li

Published in: Mobile Networks and Applications | Issue 1/2020

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Abstract

Software-Defined Networking (SDN) has been proposed as a promising way for its centralized network control and management. However, the latest SDN research focuses on smaller network environments such as data centers and enterprises, which easily lead to single point of failure and unbalanced network load in large-scale network environments. One effective way to solve this problem is to establish a standardized mechanism between network entities such as data centers, enterprises and Internet service providers (ISPs). In this paper, we propose WECAN, an efficient West-East Control Associated Network for enabling communication between different SDN entities. WECAN has three complementary modules: Network Information Collection (NIC) module, Cross-domain Management (CDM) module and Controller Selection Management(CSM) module. NIC collects network information from a different set of controllers and generates a domain-wide network view. CDM collects domain information from other domains to generate a global network view. Base on the domain-wide network view and global network view, CSM selects the most efficient controller for each network flow in the network. To test WECAN, we develop a prototype system. Our experimental results show that WECAN can effectively control network entities to communicate, and WECAN has greatly improved network latency, network throughput and network reliability compared to a single controller-controlled network. Moreover, WECAN is very easy to use.

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Metadata
Title
WECAN: an Efficient West-East Control Associated Network for Large-Scale SDN Systems
Authors
Haisheng Yu
Heng Qi
Keqiu Li
Publication date
03-01-2019
Publisher
Springer US
Published in
Mobile Networks and Applications / Issue 1/2020
Print ISSN: 1383-469X
Electronic ISSN: 1572-8153
DOI
https://doi.org/10.1007/s11036-018-1194-9

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