4.5 Article

A Distributed Software Defined Networking Model to Improve the Scalability and Quality of Services for Flexible Green Energy Internet for Smart Grid Systems

Journal

COMPUTERS & ELECTRICAL ENGINEERING
Volume 84, Issue -, Pages -

Publisher

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.compeleceng.2020.106634

Keywords

Software defined networking; Internet of Energy; Internet of Things; Quality of services; Scalability; Network

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Green energy Internet is a new concept for future power systems based on high-level interconnection among different systems for energy efficient delivery and manage energy resources. Smart grid is one of the core energy management system based on multiple routing and data transferring services for energy management, distribution, pricing, and demand services. The traditional energy networks have suffered from high and complex computing operations and lead to degradation of services and the overall performance of all operations. Software-Defined Networking (SDN) is one of the platform to enhance the flexibility and efficiency by decoupled the control plane from its data plane. A detachment of these two-planes improved dynamic configuration, controller programmability, centralized and decentralized network operations. In this paper, a distributed SDN approach is used to address the scalability and robustness issues and improve the overall energy efficiency in smart grid systems. The SDN controller logically centralized but it works on multiple nodes that physically distributed. Distributed nodes are communicating with each other and improve the network performance to assist data flow. When flow arrives through end devices to any data plane in distributed SDN, the proposed approach supports the data plane to increase the controller response time. Also, the controller checks, whether the data needs to prioritize flow to send it locally or globally with the help of Elephant or Mice flow. The proposed approach is used to reduce the controller workload, response time, and manage Quality of Services (QoS) and enhanced energy efficiency among controllers. This approach also improves the green energy utilization in smart grid systems. The experimental results indicate that the proposed approach is more suitable and feasible for smart grid systems. (C) 2020 Elsevier Ltd. All rights reserved.

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