Energy-aware routing based on link utilization in domain network
DOI:
https://doi.org/10.18311/ijprvd/2022/30048Keywords:
Energy-aware routing, SDN, self-adaptive, link utilizationAbstract
Aimed at the characteristic of the software defined network (SDN), several green routing algorithms are proposed. However, there are many drawbacks consisted in the existing algorithms. Therefore, we propose a self-adaptive energy saving routing algorithm (LAR) which is based on residual bandwidth of links and SDN. The proposed algorithm makes the link utilization which is changing in real time as the link cost. It would obtain the topology information and link status to optimize and prune the topology for reducing the computing time of routing algorithm before selecting routing path. After a period of time, the incoming flows will automatically be gathered in heavily-loaded links. The links without traffic will be switched off while the whole network connectivity and QoS are guaranteed. Simulation results show that it is possible to reduce considerable energy consumption during off-peak hours and link energy saving can be up to 55%. And, the algorithm has the distinct advantage in terms of complexity and network performance comparing related schemes.Downloads
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Accepted 2022-04-25
Published 2022-04-25
References
Guangming, C, (2014): “Research on the key issues of green network and component sleeping”, Nanjing University of Posts.
Zuo, Qing Yun(2013): ,”Research on OpenFlow-based SDN technologies”, Journal of Software 24.5, 1078-1097.
Christensen K, Nordman B, (2005): “Reducing the energy consumption of network device”, IEEE.
Gunaratne C, Christensen K, Nordman B, et al, (2008): “Reducing the Energy Consumption ofEthernet with Adaptive Link Rate (ALR) “, IEEE Transactions on Computers, ,57(4): 448-461.
Nedevschi, Sergiu (2008): “Reducing Network Energy Consumption via Rate-Adaptation and Sleeping”, Proceedings of the 5th USENIX Symposium on Networked Systems Design and Implementation USENIX Association, 323-336.
Kim, Young Min (2012): “Ant colony based self-adaptive energy saving routing for energy efficient Internet”, Computer Networks 56.10:2343-2354.
Cianfrani, A.(2010): “An Energy Saving Routing Algorithm for a Green OSPF Protocol”, INFOCOMIEEE Conference on Computer Communications Workshops, IEEE, 1-5.
Chiaraviglio, L., M. Mellia, and F. Neri (2012): , “Minimizing ISP Network Energy Cost: Formulation and Solutions”, IEEE/ACM Transactions on Networking.
Chiaraviglio, Luca, M. Mellia, and F. Neri,(2009): “Reducing Power Consumption in BackboneNetworks”, IEEE International Conference on Communications, 1-6.
Chiaraviglio, L., M. Mellia, and F. Neri(23009): “Energy- Aware Backbone Networks: A Case Study”, Communications Workshops, 2009. ICC Workshops 2009. IEEE International Conference on IEEE, 1-5.
Wang, Rui, (2014): “Energy-aware routing algorithms in Software-Defined Networks”, AWorld of Wireless, Mobile and Multimedia Networks (WoWMoM), 2014 IEEE 15th International Symposium on IEEE, :1-6.
Xu, Guan,(2015): “Bandwidth-Aware Energy Efficient Routing with SDN in Data Center Networks”, High Performance Computing and Communications (HPCC), 2015 IEEE 7th International Symposium on Cyberspace Safety and Security (CSS), IEEE 12th International Conference on Embedded Software and Systems (ICESS), 2015 IEEE 17th International Conference on IEEE.
Wang Y, Chen H, Wu X, (2015): “An energy-efficient SDN based sleep scheduling algorithm for WSNs”, Journal of Network & Computer Application.
Bianzino, A. P. (2010): “Energy-Aware Routing: a Reality Check”, GLOBECOM Workshops(GC Wkshps),1422- 1427.
Lin, Heng, M. Xu, and Y. Yang. (2015): “Robust Energy- Aware Routing with Uncertain Traffic Demands”, IEEE International Conference on Computer Communications and Networks (ICCCN).
Yang Xiao qin, (2012): “Routing algorithm based on link bandwidth utilization rate”, Journal of Computer Applications, Sept.
Guan Li’ an, Wang Binqiang, Zhu Xuanyong, (2010): “Path Selection Algorithm Based on Residual Bandwidth and Link Utilization Rate of Next Hop”, Telecommunications Science.
Wang Xinhong, (2005): “TE Routing Algorithm to Minimize Maximum Link Utilization”, MINI-MICRO SYSTEMS, Mar.