Research Area: Software Defined Networks
In Software Defined Networks (SDNs), the global view of the underlying network topology is created and maintained at the logically centralized controller. SDN achieves it by decoupling the data plane from the control plane. The up-to-date global view at SDN controller enables the applications (running on top of it) to innovate through dynamic network programmability. To establish a global view, a controller needs to discover a physical topology of the underlying SDN network infrastructure, which is challenging due to various reasons such as the lack of SDN protocols standardization and authentication mechanisms, use of sub-optimal link discovery protocols (e.g., OFDP and LLDP), dynamic topology due to movement of virtualized data centers, switches, and multi-tenant cloud networks, and lack of integration of security schemes for the topology discovery. In this paper, we propose a SDN Link Discovery Protocol (SLDP) for efficient discovery and extraction of topology information in SDN networks. The design of SLDP is motivated from the need of a secure, lightweight, and efficient link discovery protocol in SDN. SLDP aims to prevent, detect, and mitigate various security threats such as poison, replay, and flooding attacks, which are due to lack of source authentication, lack of packet integrity checks, and reuse of static packets. SLDP creates and maintains the global network topology at SDN controller by using smaller size and lower number of SLDP packets during the topology discovery process. Thus, it significantly minimizes the topology discovery overhead in the network. We implemented SLDP on Mininet emulator, and the results show the effectiveness and correctness of SLDP concerning topology discovery time, CPU computational time, and bandwidth overheads, when compared with the traditional OpenFlow Link Discovery Protocol (OFDP). Additionally, SLDP successfully prevent, detect, and mitigate various attacks (e.g., poison, replay, and flooding) in different SDN scenarios.
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Author(s) Name: Ajay Nehra, Meenakshi Tripathi, Manoj Singh Gaur, Ramesh Babu Battula, Chhagan Lal,
Journal name: Computer Networks
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Publisher name: Elsevier
DOI: 10.1016/j.comnet.2018.12.014
Volume Information: Volume 150, 26 February 2019, Pages 102-116
