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http://hdl.handle.net/10603/389507
Title: | Control and Data Planes In Software Defined Data center Networks A Scalable and Resilient Approach |
Researcher: | Hegde, Saumya |
Guide(s): | Koolagudi , Shashidhar G and Swapan, Bhattacharya |
Keywords: | Computer Science Computer Science Information Systems Engineering and Technology |
University: | National Institute of Technology Karnataka |
Completed Date: | 2019 |
Abstract: | The single central controller of Software Defined Network (SDN) eases network newlinemanagement, but leads to scalability problems. It is therefore ideal to have a newlinelogically centralized but physically distributed set of controllers. As part of this newlinework we developed a novel placement metric called subgraph-survivability and newlinedesigned an algorithm for controller placement using this metric, such that the newlinecontrol plane is not only scalable but also resilient to failure of the controller itself. newlineThe controller collects the network statistics information and also communicates newlinethe forwarding rules to the switches. This lead to the Edge-Core SDN architecture, newlinewhere the edge and core network have their own edge and core controller. For newlinesuch networks, we have developed a separate edge and core controller placement newlinealgorithms using suitable metrics for each. The scalability problem of the data newlineplane is due to the limited switch memory and increased size of SDN forwarding newlinerule. Using source routing to forward packets, not only alleviates this problem but newlinealso complements the Edge-Core SDN model. Here, we have proposed a source newlinerouting mechanism that is scalable, is fair to both elephant and mice traffic, and newlineis resilient to link failures, thus making the data plane scalable and resilient. newlineThe algorithm and routing mechanism are validated, through both analytical newlineand empirical methods. The performance metrics of Average Inverse Shortest newlinePath Length (AISPL) and Network Disconnectedness (ND) are used to evaluate newlineour placement algorithms. An improvement of 55.88% for the AISPL metric and newline49.22% for ND metric, was observed with our proposed algorithm as compared to newlinethe random controller placement. With our source routing mechanism we observe newlinea reduction, in the number of flow table entries and the flow set up time, that is newlineproportional to the number of hops along the path of the packet. newlineKeywords: SDN, Edge-Core SDN, Controller Placement, Source newlineRouting, Scalability, Reliability, Fairness newline |
Pagination: | |
URI: | http://hdl.handle.net/10603/389507 |
Appears in Departments: | Department of Computer Science & Engineering |
Files in This Item:
File | Description | Size | Format | |
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10. chapter - 3.pdf | Attached File | 408.06 kB | Adobe PDF | View/Open |
11. chapter - 4.pdf | 266.88 kB | Adobe PDF | View/Open | |
12. chapter - 5.pdf | 1.44 MB | Adobe PDF | View/Open | |
13. chapter - 6.pdf | 71.49 kB | Adobe PDF | View/Open | |
14. chapter - 7.pdf | 99.59 kB | Adobe PDF | View/Open | |
1. title.pdf | 345.85 kB | Adobe PDF | View/Open | |
2. declaration.pdf | 57.38 kB | Adobe PDF | View/Open | |
3. certificate.pdf | 57.18 kB | Adobe PDF | View/Open | |
4. acknowledgements.pdf | 45.01 kB | Adobe PDF | View/Open | |
5.contents.pdf | 49.44 kB | Adobe PDF | View/Open | |
6. list of figures.pdf | 70.16 kB | Adobe PDF | View/Open | |
7. abstract.pdf | 56.2 kB | Adobe PDF | View/Open | |
80_recommendation.pdf | 445.19 kB | Adobe PDF | View/Open | |
8. chapter - 1.pdf | 192.49 kB | Adobe PDF | View/Open | |
9. chapter - 2.pdf | 158.74 kB | Adobe PDF | View/Open | |
references.pdf | 81 kB | Adobe PDF | View/Open |
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