Reference : EnPlace: Energy-Aware Network Partitioning for Controller Placement in SDN
Scientific journals : Article
Engineering, computing & technology : Computer science
Computational Sciences
http://hdl.handle.net/10993/52974
EnPlace: Energy-Aware Network Partitioning for Controller Placement in SDN
English
Maity, Ilora mailto [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > SigCom >]
Dhiman, Ravi [Indian Institute of Technology Kharagpur]
Misra, Sudip [Indian Institute of Technology Kharagpur]
17-May-2022
IEEE Transactions on Green Communications and Networking
Institute of Electrical and Electronics Engineers (IEEE)
Yes
International
2473-2400
[en] SDN ; Controller Placement ; Network Partitioning ; Game Theory ; IoT ; Energy Efficiency
[en] This paper addresses the energy-aware controller placement problem (CPP) in Software-Defined Networking (SDN), considering the Internet of Things (IoT) flows. CPP involves partitioning the network into multiple subsets of switches with a single controller assigned to each subset. On the other hand, an energy-aware CPP reduces the energy consumption by link deactivation and ensures that each controller is reachable from the associated switches with a minimal set of active links. Existing literature considers static data traffic and out-of-band control plane having dedicated control links. However, the out-of-band control plane increases the infrastructure cost. Moreover, with IoT devices, SDN experiences uneven data traffic volume due to diverse activation models of the IoT devices. Hence, an energy-aware CPP should consider the effects of dynamic data traffic as improper controller placement and unplanned link deactivation cause link congestion and controller overload. In this work, we present an energy-aware controller placement scheme, named EnPlace, considering in-band control plane and IoT traffic. Additionally, we propose an energy-aware route selection scheme for existing flows. EnPlace increases energy savings significantly as compared to the existing works. In particular, for 200 IoT devices, the proposed scheme increases energy savings by 22.74% as compared to GreCo, an existing scheme.
http://hdl.handle.net/10993/52974
10.1109/TGCN.2022.3175901
https://ieeexplore.ieee.org/document/9776504

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