Software-Defined Networks Supporting Time-Sensitive In-Vehicular Communication

Future in-vehicular networks will be based on Ethernet. The IEEE Time-Sensitive Networking (TSN) is a promising candidate to satisfy real-time requirements in future car communication. Software-Defined Networking (SDN) extends the Ethernet control plane with a programming option that can add much value to the resilience, security, and adaptivity of the automotive environment. In this work, we derive a first concept for combining Software-Defined Networking with Time-Sensitive Networking along with an initial evaluation. Our measurements are performed via a simulation that investigates whether an SDN architecture is suitable for time-critical applications in the car. Our findings indicate that the control overhead of SDN can be added without a delay penalty for the TSN traffic when protocols are mapped properly.Comment: To be published at IEEE VTC2019-Sprin

Packet scheduling algorithms for a software-defined manufacturing environment

With the vision of Industry 4.0, Internet of things (IoT) and Internet of Services (IoS) are making their way to the modern manufacturing systems and industrial automation. As a consequence, modern day manufacturing systems need wider product variation and customization to meet the customer's demands and survive in the competitive markets. Traditional, dedicated systems like assembly lines cannot adapt the rapidly changing requirement of today's manufacturing industries. A flexible and highly scalable infrastructure is needed to support such systems. However, most of the applications in manufacturing systems require strict QoS guarantees. For instance, time-sensitive networks like in industrial automation and smart factories need hard real-time guarantees. Deterministic networks with bounded delay and jitter are essential requirement for such systems. To support such systems, non-deterministic queueing delay has to be eliminated from the network. To this end, we present Time-Sensitive Software-Defined Networks (TSSDN) with a logically centralized controller which computes transmission schedules based on the global view of the network. SDN control logic computes optimized transmission schedules for the end hosts to avoid in network queueing delay. To compute transmission schedules, we present Integer Linear Programming and Routing and Scheduling Algorithms with heuristics that schedule and route unicast and multicast flows. Our evaluations show that it is possible to compute near optimal transmission schedules for TSSDN and bound network delays and jitter

NPTSN:RL-Based Network Planning with Guaranteed Reliability for In-Vehicle TSSDN

To achieve strict reliability goals with lower redundancy cost, Time-Sensitive Software-Defined Networking (TSSDN) enables run-time recovery for future in-vehicle networks. While the recovery mechanisms rely on network planning to establish reliability guarantees, existing network planning solutions are not suitable for TSSDN due to its domain-specific scheduling and reliability concerns. The sparse solution space and expensive reliability verification further complicate the problem. We propose NPTSN, a TSSDN planning solution based on deep Reinforcement Learning (RL). It represents the domain-specific concerns with the RL environment and constructs solutions with an intelligent network generator. The network generator iteratively proposes TSSDN solutions based on a failure analysis and trains a decision-making neural network using a modified actor-critic algorithm. Extensive performance evaluations show that NPTSN guarantees reliability for more test cases and shortens the decision trajectory compared to state-of-the-art solutions. It reduces the network cost by up to 6.8x in the performed experiments

SDN4CoRE: A Simulation Model for Software-Defined Networking for Communication over Real-Time Ethernet

Ethernet has become the next standard for automotive and industrial automation networks. Standard extensions such as IEEE 802.1Q Time-Sensitive Networking (TSN) have been proven to meet the real-time and robustness requirements of these environments. Augmenting the TSN switching by Software-Defined Networking functions promises additional benefits: A programming option for TSN devices can add much value to the resilience, security, and adaptivity of the environment. Network simulation allows to model highly complex networks before assembly and is an essential process for the design and validation of future networks. Still, a simulation environment that supports programmable real-time networks is missing. This paper fills the gap by sharing our simulation model for Software-Defined Networking for Communication over Real-Time Ethernet (SDN4CoRE) and present initial results in modeling programmable real-time networks. In a case study, we show that SDN4CoRE can simulate complex programmable real-time networks and allows for testing and verifying the programming of real-time devices.Comment: If you cite this paper, please use the original reference: T. H\"ackel, P. Meyer, F. Korf, and T. C. Schmidt. SDN4CoRE: A Simulation Model for Software-Defined Networking for Communication over Real-Time Ethernet. In: Proceedings of the 6th International OMNeT++ Community Summit. September, 2019, Easychai

Dynamic Quality-of-Service Management Under Software-Defined Networking Architectures

The Internet is facing new challenges emerging from new trends in Information and Communication Technologies (ICT) for example, cloud services, Big Data, increased mobile usage etc. Traditional IP networks rely in two design principles that, despite serving as an effective solution in the last decades, have become deprecated and not well fit for the new challenges. First, the control and data plane are tightly embedded in the networking devices and second, the structure is highly decentralized with no centralized point of management. This static and rigid architecture leaves no space for innovation with a consequence lack of scalability. Also, it leads to high management and operation costs. The SDN paradigm provides a more dynamic, manageable, cost-effective and adaptable architecture that is ready for the dynamic nature of today's applications. The goal of this thesis is a novel SDN-enabled solution that provides dynamic Quality of Service management for real-time and multimedia applications. This solution will be tested and implemented over a real, not-simulated testbed, composed by OpenFlow-enabled devices, the ONOS SDN controller and client terminals that produced/consume data streams. Furthermore, it is also expected to characterize and evaluate the benefits of the SDN-based solution against a traditional usage of the network (non-SDN)

A Real-Time Software Defined Networking Framework for Next-Generation Industrial Networks

Industry 4.0 brings in a whole set of new requirements to engineering industrial systems, with notorious impact at the networking layer. A key challenge posed by Industry 4.0 is the operational flexibility needed to support on-the-fly reconfiguration of production cells, stations, and machines. At the networking layer, this flexibility implies dynamic packet handling, scheduling, and dispatching. SoftwareDefined Networking (SDN) provides this level of flexibility in the general Local Area Network (LAN) domain. However, its application in the industry has been hindered by a lack of support for real-time services. This paper addresses this limitation, proposing an extended SDN OpenFlow framework that includes realtime services, leveraging existing real-time data plane Ethernet technologies. We show the OpenFlow enhancements, a real-time SDN controller, and experimental validation and performance assessment. Using a proof-of-concept prototype with 3 switches and cycles of 250µs, we could achieve 1µs jitter on timetriggered traffic and a reconfiguration time between operational modes below 10msinfo:eu-repo/semantics/publishedVersio

Just a Second -- Scheduling Thousands of Time-Triggered Streams in Large-Scale Networks

Deterministic real-time communication with bounded delay is an essential requirement for many safety-critical cyber-physical systems, and has received much attention from major standardization bodies such as IEEE and IETF. In particular, Ethernet technology has been extended by time-triggered scheduling mechanisms in standards like TTEthernet and Time-Sensitive Networking. Although the scheduling mechanisms have become part of standards, the traffic planning algorithms to create time-triggered schedules are still an open and challenging research question due to the problem's high complexity. In particular, so-called plug-and-produce scenarios require the ability to extend schedules on the fly within seconds. The need for scalable scheduling and routing algorithms is further supported by large-scale distributed real-time systems like smart energy grids with tight communication requirements. In this paper, we tackle this challenge by proposing two novel algorithms called Hierarchical Heuristic Scheduling (H2S) and Cost-Efficient Lazy Forwarding Scheduling (CELF) to calculate time-triggered schedules for TTEthernet. H2S and CELF are highly efficient and scalable, calculating schedules for more than 45,000 streams on random networks with 1,000 bridges as well as a realistic energy grid network within sub-seconds to seconds

Time-Sensitive Networking for Industrial Automation: Challenges, Opportunities, and Directions

With the introduction of Cyber-Physical Systems (CPS) and Internet of Things (IoT) into industrial applications, industrial automation is undergoing tremendous change, especially with regard to improving efficiency and reducing the cost of products. Industrial automation applications are often required to transmit time- and safety-critical data to monitor and control industrial processes, especially for critical control systems. There are a number of solutions to meet these requirements (e.g., priority-based real-time schedules and closed-loop feedback control systems). However, due to their different processing capabilities (e.g., in the end devices and network switches), different vendors may come out with distinct solutions, and this makes the large-scale integration of devices from different vendors difficult or impossible. IEEE 802.1 Time-Sensitive Networking (TSN) is a standardization group formed to enhance and optimize the IEEE 802.1 network standards, especially for Ethernet-based networks. These solutions can be evolved and adapted into a cross-industry scenario, such as a large-scale distributed industrial plant, which requires multiple industrial entities working collaboratively. This paper provides a comprehensive review on the current advances in TSN standards for industrial automation. We present the state-of-the-art IEEE TSN standards and discuss the opportunities and challenges when integrating each protocol into the industry domains. Finally, we discuss some promising research about applying the TSN technology to industrial automation applications

Enabling Delegation of Control Plane Functionalities for Time Sensitive Networks

This paper proposes a new paradigm for control plane in Time Sensitive Networks (TSN). An SDN controller proactively instructs network elements on the reconfigurations to perform locally if some specific events occur (e.g., failures, performance degradations). Instructions are given in the form of Finite State Machines (FSMs), which store information related to the actions that each network element should execute to react against a specific event. Thus, if such event occurs, the SDN controller is by-passed reducing reaction (e.g., recovery) time. Such an approach is here implemented for recovery upon failures in TSN. Experiments of failure recovery are carried out and measurements are presented comparing the FSM-based solution with a fully-centralized reactive restoration. Moreover, the proposed approach is compared through simulations against Frame Replication and Elimination for Reliability. Results will show how proactive FSM manipulation can strongly reduce recovery time in SDN-based TSN networks without overloading the network with frame replicas