A variety of communication networks, such as industrial communication systems, have to provide strict delay guarantees to the carried flows. Fast and close to optimal quality of service (QoS) routing ...algorithms, e.g., delay-constrained leastcost (DCLC) routing algorithms, are required for routing flows in such networks with strict delay requirements. The emerging software-defined networking (SDN) paradigm centralizes the network control in SDN controllers that can centrally execute QoS routing algorithms. A wide range of QoS routing algorithms have been proposed in the literature and examined in individual studies. However, a comprehensive evaluation framework and quantitative comparison of QoS routing algorithms that can serve as a basis for selecting and further advancing QoS routing in SDN networks is missing in the literature. This makes it difficult to select the most appropriate QoS routing algorithm for a particular use case, e.g., for SDN controlled industrial communications. We close this gap in the literature by conducting a comprehensive up-to-date survey of centralized QoS routing algorithms. We introduce a novel four-dimensional (4D) evaluation framework for QoS routing algorithms, whereby the 4D correspond to the type of topology, two forms of scalability of a topology, and the tightness of the delay constraint. We implemented 26 selected DCLC algorithms and compared their runtime and cost inefficiency within the 4D evaluation framework. While the main conclusion of this evaluation is that the best algorithm depends on the specific sub-space of the 4D space that is targeted, we identify two algorithms, namely Lagrange relaxation-based aggregated cost (LARAC) and search space reduction delay-cost-constrained routing (SSR+DCCR), that perform very well in most of the 4D evaluation space.
Industrial networks demand centrally controlled quality of service (QoS), often in the form of hard real-time guarantees. Software-defined networking (SDN) provides a convenient paradigm for central ...QoS control. However, existing SDN-based solutions cannot guarantee hard real-time QoS as they rely on a control loop over the forwarding (data) and control planes. We propose a novel SDN-based QoS control framework that maintains an accurate network model through network calculus to avoid a control loop over forwarding and control planes, allocates resources to and routes flows over a network of "queue links," whereby each physical network link houses multiple queue links (with different QoS levels), and manages QoS through a function split between delay-constrained least-cost routing on the network of queue links and the resource allocation to the queue links. This function split greatly reduces the computational complexity while achieving hard real-time QoS with high bandwidth utilization. Our evaluation results indicate that our function split approach allows for online runtime admission control and can achieve bandwidth utilization above 80% while meeting deterministic real-time QoS requirements.
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 paper, 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.
State synchronisation in clustered Software Defined Networking controller deployments ensures that all instances of the controller have the same state information in order to provide redundancy. ...Current implementations of controllers use a strong consistency model, where configuration changes must be synchronised across a number of instances before they are applied on the network infrastructure. For large deployments, this blocking process increases the delay of state synchronisation across cluster members and consequently has a detrimental effect on network operations that require rapid response, such as fast failover and Quality of Service applications. In this paper, we introduce an adaptive consistency model for SDN Controllers that employs concepts of eventual consistency models along with a novel `cost-based' approach where strict synchronisation is employed for critical operations that affect a large portion of the network resources while less critical changes are periodically propagated across cluster nodes. We use simulation to evaluate our model and demonstrate the potential gains in performance.
The routing algorithms used by current operators aim at coping with the demanded QoS requirements while optimizing the use of their network resources. These algorithms rely on the optimal ...substructure property (OSP), which states that an optimal path contains other optimal paths within it. However, we show that QoS metrics such as queuing delay and buffer consumption do not satisfy this property, which implies that the used algorithms lose their optimality and/or completeness. This negatively impacts the operator economy by causing a waste of network resources and/or violating Service Level Agreements (SLAs). In this paper, we propose a new so-called Mn taxonomy defining new metric classes. An Mn metric corresponds to a metric which requires the knowledge of the n previously traversed edges to compute its value at a given edge. Based on this taxonomy, we present three solutions for solving routing problems with the newly defined classes of metrics. We show that state-of- the-art algorithms based on the OSP indeed lose their original optimality and/or completeness properties while our proposed solutions do not, at the price of an increased computation time.
Industrial networks demand centrally controlled Quality of Service (QoS), often in the form of hard real-time guarantees. We propose a novel SDN-based QoS control paradigm that (i) maintains an ...accurate network model through network calculus to avoid a control loop over forwarding and control planes, (ii) routes flows over a network of "queue links", whereby each physical network link houses multiple queue links (with different QoS levels), and (iii) manages QoS through delay-constrained least-cost (DCLC) routing on the network of queue links.
Due to the distributed nature of the network protocols, the provisioning of end-to-end Quality of Service (QoS) in IP-based networks is a complex task. We argue that Software Defined Networking (SDN) ...delivers a key technology to improve QoS provisioning. The core idea of SDN is the establishment of a standardized interface between the control and forwarding planes, allowing a logically centralized controller to control each forwarding element in a unified way. This unified interface provides three key features of SDN: flexibility, a centralized view and programmability. In this paper we exploit these features to create an end-to-end real-time QoS communication service based on SDN. In particular, our concept allows to flexibly allocate each flow in a network to different priority queues in each hop along its way to optimize the resource usage while being able to keep the delay and bandwidth constraints. This concept can be used, for example, to realize a more fine granular access control for real-time communication services allowing potentially more flows to be accepted than with traditional QoS reservation concepts. For our concept, we introduce a deterministic network model using network calculus to compute the optimal paths for each flow through the priority queues. We validate our concept with a simulation based performance analysis for a selected network scenario. In this setting our concept improves the average link utilization from 30% to more than 60% compared to traditional QoS reservation concepts.
State synchronisation in clustered Software Defined Networking controller deployments ensures that all instances of the controller have the same state information in order to provide redundancy. ...Current implementations of controllers use a strong consistency model, where configuration changes must be synchronised across a number of instances before they are applied on the network infrastructure. For large deployments, this blocking process increases the delay of state synchronisation across cluster members and consequently has a detrimental effect on network operations that require rapid response, such as fast failover and Quality of Service applications. In this paper, we introduce an adaptive consistency model for SDN Controllers that employs concepts of eventual consistency models along with a novel `cost-based' approach where strict synchronisation is employed for critical operations that affect a large portion of the network resources while less critical changes are periodically propagated across cluster nodes. We use simulation to evaluate our model and demonstrate the potential gains in performance.
Optical tomography has emerged as a non-invasive imaging method, providing three-dimensional insights into subcellular structures and thereby enabling a deeper understanding of cellular functions, ...interactions, and processes. Conventional optical tomography methods are constrained by a limited illumination scanning range, leading to anisotropic resolution and incomplete imaging of cellular structures. To overcome this problem, we employ a compact multi-core fibre-optic cell rotator system that facilitates precise optical manipulation of cells within a microfluidic chip, achieving full-angle projection tomography with isotropic resolution. Moreover, we demonstrate an AI-driven tomographic reconstruction workflow, which can be a paradigm shift from conventional computational methods, often demanding manual processing, to a fully autonomous process. The performance of the proposed cell rotation tomography approach is validated through the three-dimensional reconstruction of cell phantoms and HL60 human cancer cells. The versatility of this learning-based tomographic reconstruction workflow paves the way for its broad application across diverse tomographic imaging modalities, including but not limited to flow cytometry tomography and acoustic rotation tomography. Therefore, this AI-driven approach can propel advancements in cell biology, aiding in the inception of pioneering therapeutics, and augmenting early-stage cancer diagnostics.
Abstract Devices implanted into the body become encapsulated due to a foreign body reaction. In the central nervous system (CNS), this can lead to loss of functionality in electrodes used to treat ...disorders. Around CNS implants, glial cells are activated, undergo gliosis and ultimately encapsulate the electrodes. The primary cause of this reaction is unknown. Here we show that the mechanical mismatch between nervous tissue and electrodes activates glial cells. Both primary rat microglial cells and astrocytes responded to increasing the contact stiffness from physiological values ( G ′ ∼ 100 Pa) to shear moduli G ′ ≥ 10 kPa by changes in morphology and upregulation of inflammatory genes and proteins. Upon implantation of composite foreign bodies into rat brains, foreign body reactions were significantly enhanced around their stiff portions in vivo . Our results indicate that CNS glial cells respond to mechanical cues, and suggest that adapting the surface stiffness of neural implants to that of nervous tissue could minimize adverse reactions and improve biocompatibility.
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