VNode infrastucture enhancement — Deeply programmable network virtualization

Yamada, K.; Kanada, Yasusi; Amemiya, Kenta; Nakao, Akihiro; Saida, Yoshinori

doi:10.1109/apcc.2015.7412518

Cited by 3 publications

(3 citation statements)

References 2 publications

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“…At that time, a slice has been defined as an isolated set of network bandwidth, computational, storage, resources allocated for a group of users that "program" network functions and services over their overlay networks overlaid on top of the planet. Since then, various network virtualization testbed research efforts such as PlanetLab EU [14], GENI [12], VNode [48], FLARE [6], Fed4Fire [5], have inherited the concept of slices as a basis of the infrastructures.…”

Section: A Brief History Of Network Slicingmentioning

confidence: 99%

End-to-end Network Slicing for 5G Mobile Networks

Nakao

Kiriha

et al. 2017

Journal of Information Processing

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114

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Abstract:The research and development (R&D) and the standardization of the 5th Generation (5G) mobile networking technologies are proceeding at a rapid pace all around the world. In this paper, we introduce the emerging concept of network slicing that is considered one of the most significant technology challenges for 5G mobile networking infrastructure, summarize our preliminary research efforts to enable end-to-end network slicing for 5G mobile networking, and finally discuss application use cases that should drive the designs of the infrastructure of network slicing.

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Section: A Brief History Of Network Slicingmentioning

confidence: 99%

End-to-end Network Slicing for 5G Mobile Networks

Nakao

Kiriha

et al. 2017

Journal of Information Processing

Self Cite

114

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“…The general advantages of FLARE architecture are supporting the extension of SDN capabilities and the development of new protocols (e.g., non-IP protocols) in the research community. Later, improvements in VNode infrastructure using the FLARE node have been presented in [196]- [199]. Support for edge network virtualization and better resource management has been added.…”

Section: ) Original Approach To the Realization Of Dpn Ideamentioning

confidence: 99%

A Survey on Data Plane Flexibility and Programmability in Software-Defined Networking

et al. 2019

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Software-defined networking (SDN) attracts the attention of the research community in recent years, as evidenced by a large number of survey and review papers. The architecture of SDN clearly recognizes three planes: application, control, and data plane. The application plane executes network applications; control plane regulates the rules for the entire network based on the requests generated by network applications; and based on the set rules, the controller configures the switches in the data plane. The role of the switch in the data plane is to simply forward packets based on the instructions given by the controller. By analyzing SDN-related research papers, it is observed that research, from the very beginning, is insufficiently focused on the data plane. Therefore, this paper gives a comprehensive overview of the data plane survey with particular emphasis on the problem of programmability and flexibility. The first part of the survey is dedicated to the evaluation of actual data plane architectures through several definitions and aspects of data plane flexibility and programmability. Then, an overview of SDN-related research was presented with the aim of identifying key factors influencing the gradual deviation from the original data plane architectures given with ForCES and OpenFlow specifications, which we called the data plane evolution. By establishing a correlation between the treated problem and the problem-solving approaches, the limitations of ForCES and OpenFlow data plane architectures were identified. Based on identified limitations, a generalization of approaches to addressing the problem of data plane flexibility and programmability is made. By examining generalized approaches, open issues have been identified, establishing the grounds for future research directions proposal.

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“…Before network slicing gains popularity among mobile networking researchers, we have defined "slice" as an isolated set of programmable resources to implement network functions and application services through software programs for accommodating individual network functions and application services within each slice without interfering with the other functions and services on the coexisting slices [10]. In fact, the concept of slice in networking Copyright c 2018 The Institute of Electronics, Information and Communication Engineers has been introduced in network virtualization research efforts such as PlanetLab [11], in 2002, PlanetLab EU [12], GENI [13], VNode [14], FLARE [15], and Fed4Fire [16].…”

Section: Application Specific End-to-end Network Slicingmentioning

confidence: 99%

Toward In-Network Deep Machine Learning for Identifying Mobile Applications and Enabling Application Specific Network Slicing

Nakao

2018

IEICE Trans. Commun.

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In this paper, we posit that, in future mobile network, network softwarization will be prevalent, and it becomes important to utilize deep machine learning within network to classify mobile traffic into fine grained slices, by identifying application types and devices so that we can apply Quality-of-Service (QoS) control, mobile edge/multi-access computing, and various network function per application and per device. This paper reports our initial attempt to apply deep machine learning for identifying application types from actual mobile network traffic captured from an MVNO, mobile virtual network operator and to design the system for classifying it to application specific slices.

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VNode infrastucture enhancement — Deeply programmable network virtualization

Cited by 3 publications

References 2 publications

End-to-end Network Slicing for 5G Mobile Networks

End-to-end Network Slicing for 5G Mobile Networks

A Survey on Data Plane Flexibility and Programmability in Software-Defined Networking

Toward In-Network Deep Machine Learning for Identifying Mobile Applications and Enabling Application Specific Network Slicing

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