Network Slicing On Software Defined Network Using Flowvisor and POX Controller To Flowspace Isolation Enforcement

Kurniawan, M. Teguh; Moszardo, Ibram; Almaarif, Ahmad

doi:10.1109/icsmartgrid55722.2022.9848585

Cited by 2 publications

(3 citation statements)

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“…Traffic, CPU, forwarding tables, bandwidth, and topology are the dimensions taken into account for slicing in FlowVisor. Each network slice supports a controller, allowing several controllers to coexist in the same physical network while each controller is free to operate on its own network slice [301].…”

Section: Network Hypervisorsmentioning

confidence: 99%

A Comprehensive Survey on Knowledge-Defined Networking

Wijesekara

Gunawardena

2023

Telecom

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Traditional networking is hardware-based, having the control plane coupled with the data plane. Software-Defined Networking (SDN), which has a logically centralized control plane, has been introduced to increase the programmability and flexibility of networks. Knowledge-Defined Networking (KDN) is an advanced version of SDN that takes one step forward by decoupling the management plane from control logic and introducing a new plane, called a knowledge plane, decoupled from control logic for generating knowledge based on data collected from the network. KDN is the next-generation architecture for self-learning, self-organizing, and self-evolving networks with high automation and intelligence. Even though KDN was introduced about two decades ago, it had not gained much attention among researchers until recently. The reasons for delayed recognition could be due to the technology gap and difficulty in direct transformation from traditional networks to KDN. Communication networks around the globe have already begun to transform from SDNs into KDNs. Machine learning models are typically used to generate knowledge using the data collected from network devices and sensors, where the generated knowledge may be further composed to create knowledge ontologies that can be used in generating rules, where rules and/or knowledge can be provided to the control, management, and application planes for use in decision-making processes, for network monitoring and configuration, and for dynamic adjustment of network policies, respectively. Among the numerous advantages that KDN brings compared to SDN, enhanced automation and intelligence, higher flexibility, and improved security stand tall. However, KDN also has a set of challenges, such as reliance on large quantities of high-quality data, difficulty in integration with legacy networks, the high cost of upgrading to KDN, etc. In this survey, we first present an overview of the KDN architecture and then discuss each plane of the KDN in detail, such as sub-planes and interfaces, functions of each plane, existing standards and protocols, different models of the planes, etc., with respect to examples from the existing literature. Existing works are qualitatively reviewed and assessed by grouping them into categories and assessing the individual performance of the literature where possible. We further compare and contrast traditional networks and SDN against KDN. Finally, we discuss the benefits, challenges, design guidelines, and ongoing research of KDNs. Design guidelines and recommendations are provided so that identified challenges can be mitigated. Therefore, this survey is a comprehensive review of architecture, operation, applications, and existing works of knowledge-defined networks.

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Section: Network Hypervisorsmentioning

confidence: 99%

A Comprehensive Survey on Knowledge-Defined Networking

Wijesekara

Gunawardena

2023

Telecom

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Section: B Network Slicing Implementationmentioning

confidence: 99%

“…Figure 6 shows the structure of the SDN proxy in the slicing environment. As indicated in Figure 7, one of the most important hypervisors used to achieve this scenario is FlowVisor, which works as an SDN proxy intercepting messages between the data layer and the control layer [27]. FlowVisor is an infrastructure resource virtualization layer that enables the creation of multiple network slices, and each slice includes a dedicated SDN controller.…”

Section: B Network Slicing Implementationmentioning

confidence: 99%

Enhanced Security of Software-defined Network and Network Slice Through Hybrid Quantum Key Distribution Protocol

Mahdi¹,

Abdullah²

2022

Infocommunications journal

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Software-defined networking (SDN) has revolutionized the world of technology as networks have become more flexible, dynamic and programmable. The ability to conduct network slicing in 5G networks is one of the most crucial features of SDN implementation. Although network programming provides new security solutions of traditional networks, SDN and network slicing also have security issues, an important one being the weaknesses related to openflow channel between the data plane and controller as the network can be attacked via the openflow channel and exploit communications with the control plane. Our work proposes a solution to provide adequate security for openflow messages through using a hybrid key consisting of classical and quantum key distribution protocols to provide double security depending on the computational complexity and physical properties of quantum. To achieve this goal, the hybrid key used with transport layer security protocol to provide confidentiality, integrity and quantum authentication to secure openflow channel. We experimentally based on the SDN-testbed and network slicing to show the workflow of exchanging quantum and classical keys between the control plane and data plane and our results showed the effectiveness of the hybrid key to enhance the security of the transport layer security protocol. Thereby achieving adequate security for openflow channel against classical and quantum computer attacks.

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Network Slicing On Software Defined Network Using Flowvisor and POX Controller To Flowspace Isolation Enforcement

Cited by 2 publications

References 0 publications

A Comprehensive Survey on Knowledge-Defined Networking

A Comprehensive Survey on Knowledge-Defined Networking

Enhanced Security of Software-defined Network and Network Slice Through Hybrid Quantum Key Distribution Protocol

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