This presentation discusses the implementation for integration of cloud infrastructure with SDN using OpenStack and OpenDaylight (ODL). After integration, network services such as load balancer (LB) and web server (WS) are implemented on the cloud. Performance analysis of the effect of load balancer in SDN based cloud is discussed.

1. Performance Analysis of the
Effect of a Load Balancer on
Software Defined Networking
(SDN) based Cloud
By: Dr. Rinki Sharma,
Ramaiah University of Applied Sciences,Bangalore
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2. Contemporary Network Infrastructure
• Continuous rise in communication
and computing devices
• Need for bandwidth, storage, and
computing power has grown
exponentially
• Management and maintenance
through traditional networking is
expensive and complex
• Cloud computing:
• Better scalability
• Reduced infrastructure cost
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3. Software Defined
Networking (SDN)
3

4. Software Defined Networking
Traditional Networking Software Defined Networking
SDN eliminates manual configuration of individual switches, routers,and
other network hardware
All networking hardware is managed through a controller 4

5. Integration of SDN
and Cloud allows
better scalability
and manageability
5

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Introduction
• SDN and cloud are integrated using OpenStack and OpenDayLight
(ODL)
• Web server implemented on the cloud processes requests
• Load balancer allocates processing requests to the web servers for
simultaneous processing
• Time taken by the web servers to process requests with and without
the presence of web servers is analyzed

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Implementation
• OpenStack
• An open source cloud computing software. Provides Infrastructure as a Service(IaaS).
• OpenDayLight (ODL) controller
• Network controller for SDN
• OpenFlow
• Protocol for communication between controller and control plane of networknodes
• Open vSwitch
• Open source virtualization switch
• Open source software switch for virtualization supports functionalities such as VLAN, QoS
shaping, Layer 2 and Layer 4 based access control lists
• Open vSwitch Data Base (OVSDB)
• Data base in Open vSwitch

8. Nodes Configured
• Nodes configured
• Controller
• Compute
• Network
• OpenDaylight
OpenStack installed on Controller, Compute and Network Nodes
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9. Components Installed on Controller, Compute and Network Node
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10. OpenDaylight and OpenStack Interactions
ML-2 (Modular Layer 2)
plugin used for integration
of OpenDayLight and
OpenStack
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11. Web Server and Load Balancer
Web Server 1, Web Server
2 and the load balancer
instances are launched on
OpenStack
Load balancer allocates
based on round
requests to web server
robin
scheduling
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12. Time Taken to Process Requests with Load
Balancer
• Time taken to process the
requests increases linearly with
the number of requests sent
concurrently.
• It is due to the queuing of
requests at the LB
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13. Time Taken to Process Requests without Load
Balancer
• Inclusion of load balancer
increases time take to process
requests due to inclusion of
additional processing unit
• LB enables system to serve
multiple requests,
simultaneously, with no
downtime
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Conclusion
• Time taken to process requests with or without the presence of load
balancer increases linearly with increase in the number of concurrent
requests, as expected
• For the same number of requests, the time taken to serve the requests with
the presence of the LB is more when compared to that without the presence
of the LB.
• This is due to the extra processing unit introduced by the LB and also due to
queuing delay at the LB.
• Advantage of using LB is that it can serve multiple simultaneous requests
without downtime.

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Future Work
• This work will be extended further to implement other job scheduling
algorithms for SDN based clouds available in the literature and
compare their performance
• The experiments will be conducted to estimate the expected saturation
rate with increasing requests

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Related Work
Ananth, M. D., & Sharma, R. (2016, December). Cloud management using network function
virtualization to reduce capex and opex. In 2016 8th International Conference on Computational
Intelligence and Communication Networks (CICN) (pp. 43-47). IEEE.
Ananth, M. D., & Sharma, R. (2017, January). Cost and performance analysis of network function
virtualization based cloud systems. In 2017 IEEE 7th International Advance Computing Conference
(IACC) (pp. 70-74). IEEE.
Sharma, R., & Reddy, H. (2019, December). Effect of Load Balancer on Software-Defined
Networking (SDN) based Cloud. In 2019 IEEE 16th India Council International Conference
(INDICON) (pp. 1-4). IEEE.

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Thank You