Perfomance Analysis and Resource Optimisation of Critical Systems Modelled by Petri Nets

Un sistema crítico debe cumplir con su misión a pesar de la presencia de problemas de seguridad. Este tipo de sistemas se suele desplegar en entornos heterogéneos, donde pueden ser objeto de intentos de intrusión, robo de información confidencial u otro tipo de ataques. Los sistemas, en general, tienen que ser rediseñados después de que ocurra un incidente de seguridad, lo que puede conducir a consecuencias graves, como el enorme costo de reimplementar o reprogramar todo el sistema, así como las posibles pérdidas económicas. Así, la seguridad ha de ser concebida como una parte integral del desarrollo de sistemas y como una necesidad singular de lo que el sistema debe realizar (es decir, un requisito no funcional del sistema). Así pues, al diseñar sistemas críticos es fundamental estudiar los ataques que se pueden producir y planificar cómo reaccionar frente a ellos, con el fin de mantener el cumplimiento de requerimientos funcionales y no funcionales del sistema. A pesar de que los problemas de seguridad se consideren, también es necesario tener en cuenta los costes incurridos para garantizar un determinado nivel de seguridad en sistemas críticos. De hecho, los costes de seguridad puede ser un factor muy relevante ya que puede abarcar diferentes dimensiones, como el presupuesto, el rendimiento y la fiabilidad. Muchos de estos sistemas críticos que incorporan técnicas de tolerancia a fallos (sistemas FT) para hacer frente a las cuestiones de seguridad son sistemas complejos, que utilizan recursos que pueden estar comprometidos (es decir, pueden fallar) por la activación de los fallos y/o errores provocados por posibles ataques. Estos sistemas pueden ser modelados como sistemas de eventos discretos donde los recursos son compartidos, también llamados sistemas de asignación de recursos. Esta tesis se centra en los sistemas FT con recursos compartidos modelados mediante redes de Petri (Petri nets, PN). Estos sistemas son generalmente tan grandes que el cálculo exacto de su rendimiento se convierte en una tarea de cálculo muy compleja, debido al problema de la explosión del espacio de estados. Como resultado de ello, una tarea que requiere una exploración exhaustiva en el espacio de estados es incomputable (en un plazo prudencial) para sistemas grandes. Las principales aportaciones de esta tesis son tres. Primero, se ofrecen diferentes modelos, usando el Lenguaje Unificado de Modelado (Unified Modelling Language, UML) y las redes de Petri, que ayudan a incorporar las cuestiones de seguridad y tolerancia a fallos en primer plano durante la fase de diseño de los sistemas, permitiendo así, por ejemplo, el análisis del compromiso entre seguridad y rendimiento. En segundo lugar, se proporcionan varios algoritmos para calcular el rendimiento (también bajo condiciones de fallo) mediante el cálculo de cotas de rendimiento superiores, evitando así el problema de la explosión del espacio de estados. Por último, se proporcionan algoritmos para calcular cómo compensar la degradación de rendimiento que se produce ante una situación inesperada en un sistema con tolerancia a fallos

Reliability Analysis of the Hypercube Architecture.

This dissertation presents improved techniques for analyzing network-connected (NCF), 2-connected (2CF), task-based (TBF), and subcube (SF) functionality measures in a hypercube multiprocessor with faulty processing elements (PE) and/or communication elements (CE). These measures help study system-level fault tolerance issues and relate to various application modes in the hypercube. Solutions discussed in the text fall into probabilistic and deterministic models. The probabilistic measure assumes a stochastic graph of the hypercube where PE\u27s and/or CE\u27s may fail with certain probabilities, while the deterministic model considers that some system components are already failed and aims to determine the system functionality. For probabilistic model, MIL-HDBK-217F is used to predict PE and CE failure rates for an Intel iPSC system. First, a technique called CAREL is presented. A proof of its correctness is included in an appendix. Using the shelling ordering concept, CAREL is shown to solve the exact probabilistic NCF measure for a hypercube in time polynomial in the number of spanning trees. However, this number increases exponentially in the hypercube dimension. This dissertation, then, aims to more efficiently obtain lower and upper bounds on the measures. Algorithms, presented in the text, generate tighter bounds than had been obtained previously and run in time polynomial in the cube dimension. The proposed algorithms for probabilistic 2CF measure consider PE and/or CE failures. In attempting to evaluate deterministic measures, a hybrid method for fault tolerant broadcasting in the hypercube is proposed. This method combines the favorable features of redundant and non-redundant techniques. A generalized result on the deterministic TBF measure for the hypercube is then described. Two distributed algorithms are proposed to identify the largest operational subcubes in a hypercube C\sb{n} with faulty PE\u27s. Method 1, called LOS1, requires a list of faulty components and utilizes the CMB operator of CAREL to solve the problem. In case the number of unavailable nodes (faulty or busy) increases, an alternative distributed approach, called LOS2, processes m available nodes in O(mn) time. The proposed techniques are simple and efficient

On Dynamic Monitoring Methods for Networks-on-Chip

Rapid ongoing evolution of multiprocessors will lead to systems with hundreds of processing cores integrated in a single chip. An emerging challenge is the implementation of reliable and efficient interconnection between these cores as well as other components in the systems. Network-on-Chip is an interconnection approach which is intended to solve the performance bottleneck caused by traditional, poorly scalable communication structures such as buses. However, a large on-chip network involves issues related to congestion problems and system control, for instance. Additionally, faults can cause problems in multiprocessor systems. These faults can be transient faults, permanent manufacturing faults, or they can appear due to aging. To solve the emerging traffic management, controllability issues and to maintain system operation regardless of faults a monitoring system is needed. The monitoring system should be dynamically applicable to various purposes and it should fully cover the system under observation. In a large multiprocessor the distances between components can be relatively long. Therefore, the system should be designed so that the amount of energy-inefficient long-distance communication is minimized. This thesis presents a dynamically clustered distributed monitoring structure. The monitoring is distributed so that no centralized control is required for basic tasks such as traffic management and task mapping. To enable extensive analysis of different Network-on-Chip architectures, an in-house SystemC based simulation environment was implemented. It allows transaction level analysis without time consuming circuit level implementations during early design phases of novel architectures and features. The presented analysis shows that the dynamically clustered monitoring structure can be efficiently utilized for traffic management in faulty and congested Network-on-Chip-based multiprocessor systems. The monitoring structure can be also successfully applied for task mapping purposes. Furthermore, the analysis shows that the presented in-house simulation environment is flexible and practical tool for extensive Network-on-Chip architecture analysis.Siirretty Doriast

High-speed, economical design implementation of transit network router

Thesis (M.S.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1995.Includes bibliographical references (p. 88-90).by Kazuhiro Hara.M.S

Network-on-Chip

Limitations of bus-based interconnections related to scalability, latency, bandwidth, and power consumption for supporting the related huge number of on-chip resources result in a communication bottleneck. These challenges can be efficiently addressed with the implementation of a network-on-chip (NoC) system. This book gives a detailed analysis of various on-chip communication architectures and covers different areas of NoCs such as potentials, architecture, technical challenges, optimization, design explorations, and research directions. In addition, it discusses current and future trends that could make an impactful and meaningful contribution to the research and design of on-chip communications and NoC systems

Dagstuhl Reports : Volume 1, Issue 2, February 2011

Online Privacy: Towards Informational Self-Determination on the Internet (Dagstuhl Perspectives Workshop 11061) : Simone Fischer-Hübner, Chris Hoofnagle, Kai Rannenberg, Michael Waidner, Ioannis Krontiris and Michael Marhöfer Self-Repairing Programs (Dagstuhl Seminar 11062) : Mauro Pezzé, Martin C. Rinard, Westley Weimer and Andreas Zeller Theory and Applications of Graph Searching Problems (Dagstuhl Seminar 11071) : Fedor V. Fomin, Pierre Fraigniaud, Stephan Kreutzer and Dimitrios M. Thilikos Combinatorial and Algorithmic Aspects of Sequence Processing (Dagstuhl Seminar 11081) : Maxime Crochemore, Lila Kari, Mehryar Mohri and Dirk Nowotka Packing and Scheduling Algorithms for Information and Communication Services (Dagstuhl Seminar 11091) Klaus Jansen, Claire Mathieu, Hadas Shachnai and Neal E. Youn

High Accuracy Distributed Target Detection and Classification in Sensor Networks Based on Mobile Agent Framework

High-accuracy distributed information exploitation plays an important role in sensor networks. This dissertation describes a mobile-agent-based framework for target detection and classification in sensor networks. Specifically, we tackle the challenging problems of multiple- target detection, high-fidelity target classification, and unknown-target identification. In this dissertation, we present a progressive multiple-target detection approach to estimate the number of targets sequentially and implement it using a mobile-agent framework. To further improve the performance, we present a cluster-based distributed approach where the estimated results from different clusters are fused. Experimental results show that the distributed scheme with the Bayesian fusion method have better performance in the sense that they have the highest detection probability and the most stable performance. In addition, the progressive intra-cluster estimation can reduce data transmission by 83.22% and conserve energy by 81.64% compared to the centralized scheme. For collaborative target classification, we develop a general purpose multi-modality, multi-sensor fusion hierarchy for information integration in sensor networks. The hierarchy is com- posed of four levels of enabling algorithms: local signal processing, temporal fusion, multi-modality fusion, and multi-sensor fusion using a mobile-agent-based framework. The fusion hierarchy ensures fault tolerance and thus generates robust results. In the meanwhile, it also takes into account energy efficiency. Experimental results based on two field demos show constant improvement of classification accuracy over different levels of the hierarchy. Unknown target identification in sensor networks corresponds to the capability of detecting targets without any a priori information, and of modifying the knowledge base dynamically. In this dissertation, we present a collaborative method to solve this problem among multiple sensors. When applied to the military vehicles data set collected in a field demo, about 80% unknown target samples can be recognized correctly, while the known target classification ac- curacy stays above 95%

Behavior Trees in Robotics and AI: An Introduction

A Behavior Tree (BT) is a way to structure the switching between different tasks in an autonomous agent, such as a robot or a virtual entity in a computer game. BTs are a very efficient way of creating complex systems that are both modular and reactive. These properties are crucial in many applications, which has led to the spread of BT from computer game programming to many branches of AI and Robotics. In this book, we will first give an introduction to BTs, then we describe how BTs relate to, and in many cases generalize, earlier switching structures. These ideas are then used as a foundation for a set of efficient and easy to use design principles. Properties such as safety, robustness, and efficiency are important for an autonomous system, and we describe a set of tools for formally analyzing these using a state space description of BTs. With the new analysis tools, we can formalize the descriptions of how BTs generalize earlier approaches. We also show the use of BTs in automated planning and machine learning. Finally, we describe an extended set of tools to capture the behavior of Stochastic BTs, where the outcomes of actions are described by probabilities. These tools enable the computation of both success probabilities and time to completion