An L2-in-L3 tunneling technology plays an important role in network virtualization based on the concept of Software-Defined Networking (SDN). VXLAN (Virtual eXtensible LAN) and NVGRE (Network Virtualization using Generic Routing Encapsulation) protocols are being widely used in public cloud datacenters. These protocols resolve traditional VLAN problems such as a limitation of the number of virtual networks, however, their network performances are low without dedicated hardware acceleration. Although STT (Stateless Transport Tunneling) achieves far better performance, it has pragmatic problems in that STT packets can be dropped by network middleboxes like stateful firewalls because of modified TCP header semantics. In this paper, we propose yet another layer 4 protocol (Segment-oriented Connection-less Protocol, SCLP) for existing tunneling protocols. Our previous study revealed that the high-performance of STT mainly comes from 2-level software packet pre-reassembly before decapsulation. The SCLP header is designed to take advantage of such processing without modifying existing protocol semantics. We implement a VXLAN over SCLP tunneling and evaluate its performance by comparing with the original VXLAN (over UDP), NVGRE, Geneve, and STT. The results show that the throughput of the proposed method was comparable to STT and almost 70% higher than that of other protocols.

In this paper, we posit that extension of SDN to support deeply and flexibly programmable, software-defined data plane significantly enhance SDN and NFV and their interaction in terms of (1) enhanced interaction between applications and networks, (2) optimization of network functions, and (3) rapid development of new network protocols. All of these benefits are expected to contribute to improving the quality of diversifying communication networks and services. We identify three major technical challenges for enabling software-defined data plane as (1) ease of programming, (2) reasonable and predictable performance and (3) isolation among multiple concurrent logics. We also promote application-driving thinking towards defining software defined data-plane. We briefly introduce our project FLARE and its related technologies and review four use cases of flexible and deeply programmable data plane.

Due to limitations of today's widely-deployed commercial networks, some end-user applications are only possible through, or greatly improved by execution on virtualized networks that have been enhanced or idealized in a way which specifically supports the application. This paper describes US Ignite and the advantages provided to US Ignite end-user applications running on virtual networks which variously: (a) minimize latency, (b) minimize jitter, (c) minimize or eliminate packet drops, (d) optimize branch points for multicast packet duplication, (e) provide isolation for sensitive information flows, and/or (f) bundle network billing with application use. Examples of US Ignite applications in these categories are provided.

We propose TagFlow, a data plane mechanism for classification in Software-Defined Networking (SDN). We first argue that simple field-matching proposals of current SDN APIs are not efficient and flexible enough and then propose a tag based classification mechanism as an alternative. Moreover, we propose user-defined actions as an improvement over current hardcoded actions in SDN APIs. Our experiments show TagFlow forwarding is almost 40% faster than OpenFlow. Furthermore, our user-defined actions at SDN southbound are thousands of times faster that equivalent northbound implementations in the literature.

The paper presents a survey on OpenFlow related technologies that have been proposed as a means for researchers, network service creators, and others to easily design, test, and deploy their innovative ideas in experimental or production networks to accelerate research activities on network technologies. Rather than having programmability within each network node, separated OpenFlow controllers provide network control through pluggable software modules; thus, it is easy to develop new network control functions in executable form and test them in production networks. The emergence of OpenFlow has started various research activities. The paper surveys these activities and their results.

Software-Defined Networking currently appears to be a major evolution towards network programmability. In this paper, we first analyze the network management capabilities of OpenFlow in order to identify the main challenges that are raised for SDN management. We address current deficiencies of SDN management and suggest solutions that incur research directions to be carried out for the management of enhanced SDN.

The use of computing resources on network is becoming active in the Internet and private networks. OpenFlow/Software-Defined Networking (SDN) is drawing attention as a method to control network virtualization for the cloud computing services and other carrier services. This paper introduces examples of OpenFlow/SDN technologies applied to commercial cloud services. Various activities to expand coverage over commercial carrier networks are also mentioned.

Overlay networking makes it easy for users add new network functionalities while keeping existing Internet connectivity intact. This paper introduces SCONE (Service-COmposable InterNEt) as a networking service to facilitate the management of service overlay networking. By looking into the structure of programmable overlay nodes, SCONE provides programmable IP service gateways (PSGs) that ensure high-speed per-flow packet processing for overlay networking. In order to meet the data-rate requirements of various host applications, each PSG is accelerated by hardware packet processing for its data plane. It also leverages the space-efficient pattern matching of entity cloning and provides localized (i.e., de-centralized) services to assist the scalable support for software-defined networking (SDN). An experiment result shows that the proposed PSGs can support high-fidelity overlay networking from both performance and scalability perspectives.