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Big Data Analysis-Based Secure Cluster Management for Optimized Control Plane in Software-Defined Networks
مدیریت خوشه امن مبتنی بر تحلیل داده های بزرگ برای کنترل بهینه هواپیما در شبکه های تعریف شده توسط نرم افزار-2018 In software-defined networks (SDNs), the abstracted
control plane is its symbolic characteristic, whose core component is the software-based controller. The control plane is logically
centralized, but the controllers can be physically distributed and
composed of multiple nodes. To meet the service management
requirements of large-scale network scenarios, the control plane
is usually implemented in the form of distributed controller clusters. Cluster management technology monitors all types of events
and must maintain a consistent global network status, which usually leads to big data in SDNs. Simultaneously, the cluster security
is an open issue because of the programmable and dynamic
features of SDNs. To address the above challenges, this paper
proposes a big data analysis-based secure cluster management
architecture for the optimized control plane. A security authentication scheme is proposed for cluster management. Moreover,
we propose an ant colony optimization approach that enables big
data analysis scheme and the implementation system that optimizes the control plane. Simulations and comparisons show the
feasibility and efficiency of the proposed scheme. The proposed
scheme is significant in improving the security and efficiency SDN
control plane.
Index Terms: Software-defined networks, big data, swarm computing, security, cluster management |
مقاله انگلیسی |