Rethinking Software Network Data Planes in the Era of Microservices

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A Survey on Data Plane Programming with P4: Fundamentals, Advances, and Applied Research

With traditional networking, users can configure control plane protocols to match the specific network configuration, but without the ability to fundamentally change the underlying algorithms. With SDN, the users may provide their own control plane, that can control network devices through their data plane APIs. Programmable data planes allow users to define their own data plane algorithms for network devices including appropriate data plane APIs which may be leveraged by user-defined SDN control. Thus, programmable data planes and SDN offer great flexibility for network customization, be it for specialized, commercial appliances, e.g., in 5G or data center networks, or for rapid prototyping in industrial and academic research. Programming protocol-independent packet processors (P4) has emerged as the currently most widespread abstraction, programming language, and concept for data plane programming. It is developed and standardized by an open community and it is supported by various software and hardware platforms. In this paper, we survey the literature from 2015 to 2020 on data plane programming with P4. Our survey covers 497 references of which 367 are scientific publications. We organize our work into two parts. In the first part, we give an overview of data plane programming models, the programming language, architectures, compilers, targets, and data plane APIs. We also consider research efforts to advance P4 technology. In the second part, we analyze a large body of literature considering P4-based applied research. We categorize 241 research papers into different application domains, summarize their contributions, and extract prototypes, target platforms, and source code availability.Comment: Submitted to IEEE Communications Surveys and Tutorials (COMS) on 2021-01-2

Advancing SDN from OpenFlow to P4: a survey

Software-defined Networking (SDN) marked the beginning of a new era in the field of networking by decoupling the control and forwarding processes through the OpenFlow protocol. The Next Generation SDN is defined by Open Interfaces and full programmability of the data plane. P4 is a domain-specific language that fulfills these requirements and has known wide adoption over recent years from Academia and Industry. This work is an extensive survey of the P4 language covering domains of application, a detailed overview of the language, and future directions

Expression and Composition of Optimization-Based Applications for Software-Defined Networking

Motivated by the adoption of the Software Defined Networking and its increasing focus on applications for resource management, we propose a novel framework for expressing network optimization applications. Named the SDN Optimization Layer (SOL), the framework and its extensions alleviate the burden of constructing optimization applications by abstracting the low-level details of mathematical optimization techniques such as linear programming. SOL utilizes the path abstraction to express a wide variety of network constraints and resource-management logic. We show that the framework is general and efficient enough to support various classes of applications. We extend SOL to support composition of multiple applications in a fair and resource-efficient way. We demonstrate that SOL’s composition produces better resource efficiency than previously available composition approaches and is tolerant to network variations. Finally, as a case study, we develop a new application for load balancing network intrusion prevention systems, called SNIPS. We highlight the challenges in developing the SNIPS optimization from the ground up, show SOL’s (conceptually) simplified version, and verify that both produce nearly identical solutions.Doctor of Philosoph

The Road to BOFUSS: The Basic OpenFlow User-space Software Switch

Software switches are pivotal in the Software-Defined Networking (SDN) paradigm, particularly in the early phases of development, deployment and testing. Currently, the most popular one is Open vSwitch (OVS), leveraged in many production-based environments. However, due to its kernel-based nature, OVS is typically complex to modify when additional features or adaptation is required. To this regard, a simpler user-space is key to perform these modifications. In this article, we present a rich overview of BOFUSS, the basic OpenFlow user-space software switch. BOFUSS has been widely used in the research community for diverse reasons, but it lacked a proper reference document. For this purpose, we describe the switch, its history, architecture, uses cases and evaluation, together with a survey of works that leverage this switch. The main goal is to provide a comprehensive overview of the switch and its characteristics. Although the original BOFUSS is not expected to surpass the high performance of OVS, it is a useful complementary artifact that provides some OpenFlow features missing in OVS and it can be easily modified for extended functionality. Moreover, enhancements provided by the BEBA project brought the performance from BOFUSS close to OVS. In any case, this paper sheds light to researchers looking for the trade-offs between performance and customization of BOFUSS.Comment: 24 pages, 7 figures; submitted to Telecommunications Systems journa

Ultra-reliable Low-latency, Energy-efficient and Computing-centric Software Data Plane for Network Softwarization

Network softwarization plays a significantly important role in the development and deployment of the latest communication system for 5G and beyond. A more flexible and intelligent network architecture can be enabled to provide support for agile network management, rapid launch of innovative network services with much reduction in Capital Expense (CAPEX) and Operating Expense (OPEX). Despite these benefits, 5G system also raises unprecedented challenges as emerging machine-to-machine and human-to-machine communication use cases require Ultra-Reliable Low Latency Communication (URLLC). According to empirical measurements performed by the author of this dissertation on a practical testbed, State of the Art (STOA) technologies and systems are not able to achieve the one millisecond end-to-end latency requirement of the 5G standard on Commercial Off-The-Shelf (COTS) servers. This dissertation performs a comprehensive introduction to three innovative approaches that can be used to improve different aspects of the current software-driven network data plane. All three approaches are carefully designed, professionally implemented and rigorously evaluated. According to the measurement results, these novel approaches put forward the research in the design and implementation of ultra-reliable low-latency, energy-efficient and computing-first software data plane for 5G communication system and beyond

Network acceleration techniques

Splintered offloading techniques with receive batch processing are described for network acceleration. Such techniques offload specific functionality to a NIC while maintaining the bulk of the protocol processing in the host operating system ("OS"). The resulting protocol implementation allows the application to bypass the protocol processing of the received data. Such can be accomplished this by moving data from the NIC directly to the application through direct memory access ("DMA") and batch processing the receive headers in the host OS when the host OS is interrupted to perform other work. Batch processing receive headers allows the data path to be separated from the control path. Unlike operating system bypass, however, the operating system still fully manages the network resource and has relevant feedback about traffic and flows. Embodiments of the present disclosure can therefore address the challenges of networks with extreme bandwidth delay products (BWDP)

A Cognitive Routing framework for Self-Organised Knowledge Defined Networks

This study investigates the applicability of machine learning methods to the routing protocols for achieving rapid convergence in self-organized knowledge-defined networks. The research explores the constituents of the Self-Organized Networking (SON) paradigm for 5G and beyond, aiming to design a routing protocol that complies with the SON requirements. Further, it also exploits a contemporary discipline called Knowledge-Defined Networking (KDN) to extend the routing capability by calculating the “Most Reliable” path than the shortest one. The research identifies the potential key areas and possible techniques to meet the objectives by surveying the state-of-the-art of the relevant fields, such as QoS aware routing, Hybrid SDN architectures, intelligent routing models, and service migration techniques. The design phase focuses primarily on the mathematical modelling of the routing problem and approaches the solution by optimizing at the structural level. The work contributes Stochastic Temporal Edge Normalization (STEN) technique which fuses link and node utilization for cost calculation; MRoute, a hybrid routing algorithm for SDN that leverages STEN to provide constant-time convergence; Most Reliable Route First (MRRF) that uses a Recurrent Neural Network (RNN) to approximate route-reliability as the metric of MRRF. Additionally, the research outcomes include a cross-platform SDN Integration framework (SDN-SIM) and a secure migration technique for containerized services in a Multi-access Edge Computing environment using Distributed Ledger Technology. The research work now eyes the development of 6G standards and its compliance with Industry-5.0 for enhancing the abilities of the present outcomes in the light of Deep Reinforcement Learning and Quantum Computing

Parallel network protocol stacks using replication

Computing applications demand good performance from networking systems. This includes high-bandwidth communication using protocols with sophisticated features such as ordering, reliability, and congestion control. Much of this protocol processing occurs in software, both on desktop systems and servers. Multi-processing is a requirement on today\u27s computer architectures because their design does not allow for increased processor frequencies. At the same time, network bandwidths continue to increase. In order to meet application demand for throughput, protocol processing must be parallel to leverage the full capabilities of multi-processor or multi-core systems. Existing parallelization strategies have performance difficulties that limit their scalability and their application to single, high-speed data streams. This dissertation introduces a new approach to parallelizing network protocol processing without the need for locks or for global state. Rather than maintain global states, each processor maintains its own copy of protocol state. Therefore, updates are local and don\u27t require fine-grained locks or explicit synchronization. State management work is replicated, but logically independent work is parallelized. Along with the approach, this dissertation describes Dominoes, a new framework for implementing replicated processing systems. Dominoes organizes the state information into Domains and the communication into Channels. These two abstractions provide a powerful, but flexible model for testing the replication approach. This dissertation uses Dominoes to build a replicated network protocol system. The performance of common protocols, such as TCP/IP, is increased by multiprocessing single connections. On commodity hardware, throughput increases between 15-300% depending on the type of communication. Most gains are possible when communicating with unmodified peer implementations, such as Linux. In addition to quantitative results, protocol behavior is studied as it relates to the replication approach