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Distributed controller clustering in software defined networks

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ABSTRACT

Software Defined Networking (SDN) is an emerging promising paradigm for network management because of its centralized network intelligence. However, the centralized control architecture of the software-defined networks (SDNs) brings novel challenges of reliability, scalability, fault tolerance and interoperability. In this paper, we proposed a novel clustered distributed controller architecture in the real setting of SDNs. The distributed cluster implementation comprises of multiple popular SDN controllers. The proposed mechanism is evaluated using a real world network topology running on top of an emulated SDN environment. The result shows that the proposed distributed controller clustering mechanism is able to significantly reduce the average latency from 8.1% to 1.6%, the packet loss from 5.22% to 4.15%, compared to distributed controller without clustering running on HP Virtual Application Network (VAN) SDN and Open Network Operating System (ONOS) controllers respectively. Moreover, proposed method also shows reasonable CPU utilization results. Furthermore, the proposed mechanism makes possible to handle unexpected load fluctuations while maintaining a continuous network operation, even when there is a controller failure. The paper is a potential contribution stepping towards addressing the issues of reliability, scalability, fault tolerance, and inter-operability.

No MeSH data available.


Agis network topology map.
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pone.0174715.g004: Agis network topology map.

Mentions: The research work uses a standard network topology from the Internet topology zoo (ITZ), which is a store for data of network topologies in graphical descriptions. Network operators publish information about their networks, such that the Internet topology zoo database contains topologies from AboveNet to Zamren [36]. All topologies are in a graphical format that uses the extensible markup language (XML) as description basis. The graphical format provides enough information to build up testbed networks with respect to real world topologies. Agis Network topology is used in this research work. The network contains twenty-five (25) switches, twenty-five (25) hosts with thirty (30) connected links. Fig 4 shows the Agis network topology map with all connected end points. Fig 5 depicts a section of the Agis network topology in graphml and the transformed python script of the topology. The mininet will emulate the network based on the python script of the topology.


Distributed controller clustering in software defined networks
Agis network topology map.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC5383233&req=5

pone.0174715.g004: Agis network topology map.
Mentions: The research work uses a standard network topology from the Internet topology zoo (ITZ), which is a store for data of network topologies in graphical descriptions. Network operators publish information about their networks, such that the Internet topology zoo database contains topologies from AboveNet to Zamren [36]. All topologies are in a graphical format that uses the extensible markup language (XML) as description basis. The graphical format provides enough information to build up testbed networks with respect to real world topologies. Agis Network topology is used in this research work. The network contains twenty-five (25) switches, twenty-five (25) hosts with thirty (30) connected links. Fig 4 shows the Agis network topology map with all connected end points. Fig 5 depicts a section of the Agis network topology in graphml and the transformed python script of the topology. The mininet will emulate the network based on the python script of the topology.

View Article: PubMed Central - PubMed

ABSTRACT

Software Defined Networking (SDN) is an emerging promising paradigm for network management because of its centralized network intelligence. However, the centralized control architecture of the software-defined networks (SDNs) brings novel challenges of reliability, scalability, fault tolerance and interoperability. In this paper, we proposed a novel clustered distributed controller architecture in the real setting of SDNs. The distributed cluster implementation comprises of multiple popular SDN controllers. The proposed mechanism is evaluated using a real world network topology running on top of an emulated SDN environment. The result shows that the proposed distributed controller clustering mechanism is able to significantly reduce the average latency from 8.1% to 1.6%, the packet loss from 5.22% to 4.15%, compared to distributed controller without clustering running on HP Virtual Application Network (VAN) SDN and Open Network Operating System (ONOS) controllers respectively. Moreover, proposed method also shows reasonable CPU utilization results. Furthermore, the proposed mechanism makes possible to handle unexpected load fluctuations while maintaining a continuous network operation, even when there is a controller failure. The paper is a potential contribution stepping towards addressing the issues of reliability, scalability, fault tolerance, and inter-operability.

No MeSH data available.