Self-Healing Topology Discovery Protocol for Software-Defined Networks

Ochoa-Aday, Leonardo; Cervelló-Pastor, Cristina; Fernández-Fernández, Adriana

doi:10.1109/lcomm.2018.2816921

Cited by 20 publications

(4 citation statements)

References 10 publications

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“…In [34], a similar distributed operation was briefly introduced to support self-healing properties in SDN. However, this related work lacks of crucial features for protocol implementation such as message types and dataframes structure.…”

Section: B Non-openflow Approachesmentioning

confidence: 99%

eTDP: Enhanced Topology Discovery Protocol for Software-Defined Networks

2019

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Discovering network elements in a dynamic and optimized manner and being able to contend with ever-growing traffic is a key requirement for current networking environments. In software-defined networks (SDNs), the controller collects the topology information from the data plane and maintains an abstract view of the entire network, which is crucial for the proper functioning of applications and network services. However, there is still the need for an enhanced protocol for automatic discovery and mechanisms of autoconfiguration of network elements according to new policies and business requirements. To overcome this challenge, this paper presents a novel protocol that, unlike existing approaches, enables a distributed layer-2 discovery without the need for previous network configurations or controller knowledge of the network. By using this mechanism, the SDN controller can discover the network view without incurring scalability issues, while taking advantage of the shortest control paths toward each switch. The obtained results show that our enhanced protocol is efficient in terms of time and message load over a wide range of generated networks and outperforms the state-of-the-art techniques. INDEX TERMS Network management, protocols, software-defined networks, topology discovery. CRISTINA CERVELLÓ-PASTOR received the M.Sc. and Ph.D. degrees in telecommunication engineering from the Barcelona School of Telecommunications Engineering, Politècnica de Catalunya, Barcelona, Spain, where she is currently an Associate Professor and the Head of the Department of Network Engineering. Being part of the BAMPLA Research Group, she is responsible and actively participated in diverse national and European competitive projects (NOVI, FEDER-ICA, ATDMA, A@DAN, Euro-NGI, Euro-FGI, and EURONF) and private funding research and development projects. She has published diverse papers in national and international journals and conferences. She is supervising dissertation in the field of management, optimal resource allocation, topology discovery, and routing in software-defined networks/NFV and 5G.

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Section: B Non-openflow Approachesmentioning

confidence: 99%

eTDP: Enhanced Topology Discovery Protocol for Software-Defined Networks

2019

Self Cite

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“…Recently, authors in Ochoa‐Aday et al propose a design of a self‐healing protocol for automatic topology discovery and maintenance in SDN. The proposed approach integrates 2 enhanced features (ie, layer 2 topology discovery and autonomic fault recovery) in a unified mechanism.…”

Section: Related Workmentioning

confidence: 99%

TILAK: A token‐based prevention approach for topology discovery threats in SDN

Nehra

Tripathi

Gaur

et al. 2018

Int J Communication

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Software-defined networks (SDNs) decouple the data plane from the control plane. Thus, it provides logically centralized visibility of the entire networking infrastructure to the controller. It enables the applications running on top of the control plane to innovate through network management and programmability. To envision the centralized control and visibility, the controller needs to discover the networking topology of the entire SDN infrastructure. However, discovering and maintaining a global view of the underlying network topology is a challenging task because of (i) frequently changing network topology caused by migration of the virtual machines in the data centers, mobile, end hosts and change in the number of data plane switches because of technical faults or network upgrade; (ii) lack of authentication mechanisms and scarcity in SDN standards; and (iii) availability of security solutions during topology discovery process. To this end, the aim of this paper is threefold. First, we investigate the working methodologies used to achieve global view by different SDN controllers, specifically, POX, Ryu, OpenDaylight, Floodlight, Beacon, ONOS, and HPEVAN. Second, we identify vulnerabilities that affect the topology discovery process in the above controller implementation. In particular, we provide a detailed analysis of the threats namely link layer discovery protocol (LLDP) poisoning, LLDP flooding, and LLDP replay attack concerning these controllers. Finally, to countermeasure the identified risks, we propose a novel mechanism called TILAK which generates random MAC destination addresses for LLDP packets and use this randomness to create a flow entry for the LLDP packets. It is a periodic process to prevent LLDP packet-based attacks that are caused only because of lack of verification of source authentication and integrity of LLDP packets. The implementation results for TILAK confirm that it covers targeted threats with lower resource penalty. KEYWORDSflooding, link layer discovery protocol (LLDP), replay attack, route poisoning, software-defined networking (SDN), topology discovery

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“…When the currentInterval expires, the node reinitialises its redundancy counter (counter = 0), and duplicates the value of currentInterval, until reaching a maximum value of Imax (lines 32-39). Lines (23)(24)(25)(26)(27)(28)(29)(30) define the part of the self-healing algorithm that shares the topology data when a node connects with a newly created node.…”

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confidence: 99%

A Decentralised Self-Healing Approach for Network Topology Maintenance

Rodríguez,

Gómez,

Diaconescu

2020

Preprint

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In many distributed systems, from cloud to sensor networks, different configurations impact system performance, while strongly depending on the network topology. Hence, topological changes may entail costly reconfiguration and optimisation processes. This paper proposes a multi-agent solution for recovering networks from node failures. To preserve the network topology, the proposed approach relies on local information about the network's structure, which is collected and disseminated at runtime. The paper studies two strategies for distributing topological data: one based on Mobile Agents (our proposal) and the other based on Trickle (a reference gossiping protocol from the literature). These two strategies were adapted for our self-healing approach -to collect topological information for recovering the network; and were evaluated in terms of resource overheads. Experimental results show that both variants can recover the network topology, up to a certain node failure rate, which depends on the network topology. At the same time, Mobile Agents collect less information, focusing on local dissemination, which suffices for network recovery. This entails less bandwidth overheads than when Trickle is used. Still, Mobile Agents utilise more memory and exchange more messages, during data-collection, than Trickle does. These results validate the viability of the proposed self-healing solution, offering two variant implementations

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Self-Healing Topology Discovery Protocol for Software-Defined Networks

Cited by 20 publications

References 10 publications

eTDP: Enhanced Topology Discovery Protocol for Software-Defined Networks

eTDP: Enhanced Topology Discovery Protocol for Software-Defined Networks

TILAK: A token‐based prevention approach for topology discovery threats in SDN

A Decentralised Self-Healing Approach for Network Topology Maintenance

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