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Assessing a Real-time Adaptive Traffic Route Based on Ranking Software Defined Networking (SDN) Cluster of Controllers in a Datacenter
Software Defined Networking (SDN) is the new network model that uses the notion of centralized administration and control to promote network management. Although SDN offered many advantages to promote network performance, some challenges arose due to its architecture. A centralized controller must not constitute a single point of failure for the network to achieve high availability. This reveals the need for a Real-time fault tolerance mechanism. This mechanism aims to address potential failures by providing redundancy and failover capabilities within the network infrastructure. By distributing control and decision-making responsibilities across the cluster control, the system can continue to operate seamlessly by selecting the better controller by routing the traffic from the cluster to it even if one controller experiences a failure. This real-time fault tolerance mechanism plays a vital role in maintaining uninterrupted network operations and achieving the desired level of availability. This paper presents a Real-time Efficiently Adaptive Traffic Route RATR algorithm that ensures fault tolerance and load balancing which achieves high availability consistency based on real-time measurements of cluster members’ performance monitoring and records the results as votes. Then calculate the collected votes for each performance metrics load which are CPU, Memory, Network traffic, and Response time. Finally, run the proposed grading mechanism to elect the leader controller and his vices from among all cluster members. Extensive experiments are conducted to prove the effectiveness of RATR. The results show that RATR achieves an optimal performance not only on the network throughput but also on the delay and packet loss compared with Round Robin and SMCLBRT algorithms.
Keywords
Software Defined Networking, Controller, Cluster, Traffic, Load-Balancing, Fault-Tolerance Throughput, RATR.
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