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Industrial networks require real-time guarantees for the flows they carry. That is, flows have hard end-to-end delay requirements that have to be deterministically guaranteed. While proprietary extensions of Ethernet have provided solutions, these often require expensive forwarding devices. The rise of Software-Defined Networking (SDN) opens the door to the design of centralized traffic engineering frameworks for providing such real-time guarantees. As part of such a framework, a network model is needed for the computation of worst-case delays and for access control. In this article, we propose two network models based on network calculus theory for providing deterministic services (DetServ). While our first model, the multi-hop model (MHM), assigns a rate and a buffer budget to each queue in the network, our second model, the threshold-based model (TBM), simply fixes a maximum delay for each queue. Via a packet-level simulation, we confirm that the delay bounds guaranteed by both models are never exceeded and that no packet loss occurs. We further show that the TBM provides more flexibility with respect to the characteristics of the flows to be embedded and that it has the potential of accepting more flows in a given network. Finally, we show that the runtime cost for this increase in flexibility stays reasonable for online request processing in industrial scenarios.

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This paper presents Chameleon, a cloud network providing both predictable latency and high utilization, typically two conflicting goals, especially in multi-tenant datacenters. Chameleon exploits routing flexibilities available in modern communication networks to dynamically adapt toward the demand, and uses network calculus principles along individual paths. More specifically, Chameleon employs source routing on the "queue-level topology", a network abstraction that accounts for the current states of the network queues and, hence, the different delays of different paths. Chameleon is based on a simple greedy algorithm and can be deployed at the edge; it does not require any modifications of network devices. We implement and evaluate Chameleon in simulations and a real testbed. Compared to state-of-the-art, we find that Chameleon can admit and embed significantly, i.e., up to 15 times more flows, improving network utilization while meeting strict latency guarantees.

Wind energy is one of the most attractive and one of the fastest growing sources of green energy in the world. With the expansion of wind parks, there is a growing need for an efficient coordination of the diverse energy production systems, as well as a tighter coupling between the production and the consumer side of the grid. Current grid operators suffer unnecessarily high costs due to the lack of an integrated management system towards diverse set of proprietary network protocols, complex and error prone operation of the networks, as well as the rigid security mechanisms. Network softwarization concepts, i.e., Software Defined Networking (SDN) and Network Function Virtualization (NFV), offer a great potential for reducing capital and operational expenditures by providing simplified network management and automated control. Recent works have demonstrated the feasibility of achieving stringent industrial-grade quality of service and fine grain security control with SDN and NFV. In this article, we provide an insight into wind park communication network requirements, analyze the technological benefits of the network softwarization, and demonstrate the economic profits in a case study of a typical Northwestern Europe wind park. I. INTRODUCTION ind energy is one of the most affordable and fastest growing sources of renewable energy, with more than 500 GW of installed capacity worldwide in the past 20 years. Incentives from national governments, as well as the ones proposed through the Renewable Energy Directive by European Commission targeting at covering 20% of energy needs with renewables by 2020, further promote the widespread adoption of green power plants. As the number of installed wind parks is rapidly increasing, there is a need for their tighter coupling and the efficient coordination of energy production schedules [1]. Smart Grids, which are considered as a promising solution for the integration of a diverse set of energy production and distribution systems, require deep penetration of ICT technologies in all of its subsystems. However, current wind parks are not yet prepared for a seamless integration into the Smart Grids, mainly due to the lack of mechanisms for automated and secure exchange of information [2]. Industrial communication networks, such as the one in wind parks, which in the past have been developed as closed systems, rely on closed proprietary protocol stacks, which have been tailored and optimized for their particular requirements.