Routing in turn-prohibition based feed-forward networks

Abstract. The application of queuing theory to communications systems often requires that the respective networks are of a feed-forward nature, that is they have to be free of cyclic dependencies. An effective way to ensure this property is to identify a certain set of critical turns and to prohibit their use. A turn is a concatenation of two adjacent, consecutive links. Unfortunately, current routing algorithms are usually not equipped to handle forbidden turns and the required extensions are nontrivial. We discuss the relevant issues for the example of the widely deployed Dijkstra algorithm. Then, we address the general case and introduce the Turnnet concept, which supports arbitrary combinations of routing algorithms with turn-prohibiting feed-forward mechanisms

On Cyclic Dependencies and Regulators in Time-Sensitive Networks

For time-sensitive networks, as in the context of IEEE TSN and IETF Detnet, cyclic dependencies are associated with certain fundamental properties such as improving availability and decreasing reconfiguration effort. Nevertheless, the existence of cyclic dependencies can cause very large latency bounds or even global instability, thus making the proof of the timing predictability of such networks a much more challenging issue. Cyclic dependencies can be removed by reshaping flows inside the network, by means of regulators. We consider FIFO-per-class networks with two types of regulators: perflow regulators and interleaved regulators (the latter reshape entire flow aggregates). Such regulators come with a hardware cost that is less for an interleaved regulator than for a perflow regulator; both can affect the latency bounds in different ways. We analyze the benefits of both types of regulators in partial and full deployments in terms of latency. First, we propose Low-Cost Acyclic Network (LCAN), a new algorithm for finding the optimum number of regulators for breaking all cyclic dependencies. Then, we provide another algorithm, Fixed- Point Total Flow Analysis (FP-TFA), for computing end-to-end delay bounds for general topologies, i.e., with and without cyclic dependencies. An extensive analysis of these proposed algorithms was conducted on generic grid topologies. For these test networks, we find that FP-TFA computes small latency bounds; but, at a medium to high utilization, the benefit of regulators becomes apparent. At high utilization or for high line transmission-rates, a small number of per-flow regulators has an effect on the latency bound larger than a small number of interleaved regulators. Moreover, interleaved regulators need to be placed everywhere in the network to provide noticeable improvements. We validate the applicability of our approaches on a realistic industrial timesensitive network

Torii: Multipath Distributed Ethernet Fabric Protocol for Data Centers with Zero-Loss Path Repair

This paper describes and evaluates Torii, a layer-two data center network fabric protocol. The main features of Torii are being fully distributed, scalable, fault-tolerant and with automatic setup. Torii is based on multiple, tree-based, topological MAC addresses that are used for table-free forwarding over multiple equal-cost paths, and it is capable of rerouting frames around failed links on the fly without needing a central fabric manager for any function. To the best of our knowledge, it is the first protocol that does not require the exchange of periodic messages to work under normal conditions and to recover from link failures, as Torii exchanges messages just once. Moreover, another important characteristic of Torii is that it is compatible with a wide range of data center topologies. Simulation results show an excellent distribution of traffic load and latencies, similar to shortest path protocols

Torii: Multipath Distributed Ethernet Fabric Protocol for Data Centers with Zero-Loss Path Repair

This paper describes and evaluates Torii, a layer-two data center network fabric protocol. The main features of Torii are being fully distributed, scalable, fault-tolerant and with automatic setup. Torii is based on multiple, tree-based, topological MAC addresses that are used for table-free forwarding over multiple equal-cost paths, and it is capable of rerouting frames around failed links on the fly without needing a central fabric manager for any function. To the best of our knowledge, it is the first protocol that does not require the exchange of periodic messages to work under normal conditions and to recover from link failures, as Torii exchanges messages just once. Moreover, another important characteristic of Torii is that it is compatible with a wide range of data center topologies. Simulation results show an excellent distribution of traffic load and latencies, similar to shortest path protocols

Exact Worst-case Delay in FIFO-multiplexing Feed-forward Networks

In this paper, we compute the actual worst-case end-to-end delay for a flow in a feed-forward network of first-in–first-out (FIFO)-multiplexing service curve nodes, where flows are shaped by piecewise-affine concave arrival curves, and service curves are piecewise affine and convex. We show that the worst-case delay problem can be formulated as a mixed integer linear programming problem, whose size grows exponentially with the number of nodes involved. Furthermore, we present approximate solution schemes to find upper and lower delay bounds on the worst-case delay. Both only require to solve just one linear programming problem and yield bounds that are generally more accurate than those found in the previous work, which are computed under more restrictive assumptions

Site-Specific Rules Extraction in Precision Agriculture

El incremento sostenible en la producción alimentaria para satisfacer las necesidades de una población mundial en aumento es un verdadero reto cuando tenemos en cuenta el impacto constante de plagas y enfermedades en los cultivos. Debido a las importantes pérdidas económicas que se producen, el uso de tratamientos químicos es demasiado alto; causando contaminación del medio ambiente y resistencia a distintos tratamientos. En este contexto, la comunidad agrícola divisa la aplicación de tratamientos más específicos para cada lugar, así como la validación automática con la conformidad legal. Sin embargo, la especificación de estos tratamientos se encuentra en regulaciones expresadas en lenguaje natural. Por este motivo, traducir regulaciones a una representación procesable por máquinas está tomando cada vez más importancia en la agricultura de precisión.Actualmente, los requisitos para traducir las regulaciones en reglas formales están lejos de ser cumplidos; y con el rápido desarrollo de la ciencia agrícola, la verificación manual de la conformidad legal se torna inabordable.En esta tesis, el objetivo es construir y evaluar un sistema de extracción de reglas para destilar de manera efectiva la información relevante de las regulaciones y transformar las reglas de lenguaje natural a un formato estructurado que pueda ser procesado por máquinas. Para ello, hemos separado la extracción de reglas en dos pasos. El primero es construir una ontología del dominio; un modelo para describir los desórdenes que producen las enfermedades en los cultivos y sus tratamientos. El segundo paso es extraer información para poblar la ontología. Puesto que usamos técnicas de aprendizaje automático, implementamos la metodología MATTER para realizar el proceso de anotación de regulaciones. Una vez creado el corpus, construimos un clasificador de categorías de reglas que discierne entre obligaciones y prohibiciones; y un sistema para la extracción de restricciones en reglas, que reconoce información relevante para retener el isomorfismo con la regulación original. Para estos componentes, empleamos, entre otra técnicas de aprendizaje profundo, redes neuronales convolucionales y “Long Short- Term Memory”. Además, utilizamos como baselines algoritmos más tradicionales como “support-vector machines” y “random forests”.Como resultado, presentamos la ontología PCT-O, que ha sido alineada con otras ontologías como NCBI, PubChem, ChEBI y Wikipedia. El modelo puede ser utilizado para la identificación de desórdenes, el análisis de conflictos entre tratamientos y la comparación entre legislaciones de distintos países. Con respecto a los sistemas de extracción, evaluamos empíricamente el comportamiento con distintas métricas, pero la métrica F1 es utilizada para seleccionar los mejores sistemas. En el caso del clasificador de categorías de reglas, el mejor sistema obtiene un macro F1 de 92,77% y un F1 binario de 85,71%. Este sistema usa una red “bidirectional long short-term memory” con “word embeddings” como entrada. En relación al extractor de restricciones de reglas, el mejor sistema obtiene un micro F1 de 88,3%. Este extractor utiliza como entrada una combinación de “character embeddings” junto a “word embeddings” y una red neuronal “bidirectional long short-term memory”.<br /

Securities Fraud Embedded in the Market Structure Crisis: High-Frequency Traders as Primary Violators

This Article analyzes approaches to attaching liability for securities fraud to high-frequency traders as primary violators in connection with the current market structure crisis. One of the manifestations of this crisis pertains to inadequate disclosure of advanced functionalities offered by trading venues, as exemplified by the order type controversy. The Article’s analysis is applied to secret arrangements between trading venues and preferred traders, glitches and gaming, and the reach of the doctrine of market manipulation, and several relevant issues are also viewed from the standpoint of the integrity of the trading process. The Article concludes by arguing for a balanced approach to catching certain problematic practices of high-frequency traders as securities fraud

Applications

Volume 3 describes how resource-aware machine learning methods and techniques are used to successfully solve real-world problems. The book provides numerous specific application examples: in health and medicine for risk modelling, diagnosis, and treatment selection for diseases in electronics, steel production and milling for quality control during manufacturing processes in traffic, logistics for smart cities and for mobile communications