Open AccessDSL: Dynamic and Self‐Learning Schedule Method of Multiple Controllers in SDN
Author(s) -
Li Junfei,
Wu Jiangxing,
Hu Yuxiang,
Li Kan
Publication year - 2017
Publication title -
etri journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.295
H-Index - 46
eISSN - 2233-7326
pISSN - 1225-6463
DOI - 10.4218/etrij.17.0116.0460
Subject(s) - digital subscriber line , schedule , computer science , reliability (semiconductor) , metric (unit) , controller (irrigation) , reliability engineering , real time computing , distributed computing , computer network , engineering , operations management , physics , quantum mechanics , biology , operating system , agronomy , power (physics)
For the reliability of controllers in a software defined network (SDN), a dynamic and self‐learning schedule method (DSL) is proposed. This method is original and easy to deploy, and optimizes the combination of multiple controllers. First, we summarize multiple controllers’ combinations and schedule problems in an SDN and analyze its reliability. Then, we introduce the architecture of the schedule method and evaluate multi‐controller reliability, the DSL method, and its optimized solution. By continually and statistically learning the information about controller reliability, this method treats it as a metric to schedule controllers. Finally, we compare and test the method using a given testing scenario based on an SDN network simulator. The experiment results show that the DSL method can significantly improve the total reliability of an SDN compared with a random schedule, and the proposed optimization algorithm has higher efficiency than an exhaustive search.