TITLE:
Contribution to the Optimization of the Energy Consumption in SDN Networks
AUTHORS:
Lagasane Kra, Yaké Gondo, Bi Tra Gooré, Olivier Asseu
KEYWORDS:
IoT, SDN, Big Data, Optimization, Peak Period, Normal Period, Heuristic Algorithms
JOURNAL NAME:
Journal of Sensor Technology,
Vol.8 No.3,
September
29,
2018
ABSTRACT: With the advent of new technologies such as IoT (Internet of Things) and Big Data, the increase in users and their different communications have led to a significant increase in energy consumption in network equipment. A new networking technology called SDN (Software Defined Network) is born. It aims to make network management easier. The SDN consists of decoupling the control plane that is the brain, the data plane or the muscles of the network. It allows the programmability of network devices and also the redirection of flows. One or more centralized controllers use algorithms to act remotely on network devices. Because of its operation, this new technology offers opportunities to improve network performance and optimize energy consumption. In this paper, we will use this technology (SDN) to suspend links or routers when they are not used while taking into account the congestion that degrades the quality of service in the network. We have formulated this problem as a linear integer program and proposed algorithms to process it in normal period and peak period. We have used the OMNET ++ simulator to evaluate our algorithms. Thus, our approach showed that 87.5% of ports and 33.33% of links could be shut down to save energy.