@Article{cmc.2020.06418,
AUTHOR = {Xiaojun Shi, Yangyang Li, Haiyong Xie, Tengfei Yang, Linchao Zhang, Panyu Liu, Heng Zhang, Zhiyao Liang},
TITLE = {An OpenFlow-Based Load Balancing Strategy in SDN},
JOURNAL = {Computers, Materials \& Continua},
VOLUME = {62},
YEAR = {2020},
NUMBER = {1},
PAGES = {385--398},
URL = {http://www.techscience.com/cmc/v62n1/38119},
ISSN = {1546-2226},
ABSTRACT = {In today’s datacenter network, the quantity growth and complexity increment of
traffic is unprecedented, which brings not only the booming of network development, but
also the problem of network performance degradation, such as more chance of network
congestion and serious load imbalance. Due to the dynamically changing traffic patterns,
the state-of the-art approaches that do this all require forklift changes to data center
networking gear. The root of problem is lack of distinct strategies for elephant and mice
flows. Under this condition, it is essential to enforce accurate elephant flow detection and
come up with a novel load balancing solution to alleviate the network congestion and
achieve high bandwidth utilization. This paper proposed an OpenFlow-based load
balancing strategy for datacenter networks that accurately detect elephant flows and enforce
distinct routing schemes with different flow types so as to achieve high usage of network
capacity. The prototype implemented in Mininet testbed with POX controller and verify the
feasibility of our load-balancing strategy when dealing with flow confliction and network
degradation. The results show the proposed strategy can adequately generate flow rules and
significantly enhance the performance of the bandwidth usage compared against other
solutions from the literature in terms of load balancing.},
DOI = {10.32604/cmc.2020.06418}
}