Lexicographic Bit Allocation for MPEG Video

We consider the problem of allocating bits among pictures in an MPEG video coder to equalize the visual quality of the coded pictures, while meeting bu er and channel constraints imposed by the MPEG Video Bu ering Veri er. We address this problem within a framework that consists of three components: 1) a bit production model for the input pictures, 2) a set of bit-rate constraints imposed by the Video Bu ering Veri er, and 3) a novel lexicographic criterion for optimality. Under this framework, we derive simple necessary and su cient conditions for optimality that lead to e cient algorithms

Virtual machine scheduling in dedicated computing clusters

Time-critical applications process a continuous stream of input data and have to meet specific timing constraints. A common approach to ensure that such an application satisfies its constraints is over-provisioning: The application is deployed in a dedicated cluster environment with enough processing power to achieve the target performance for every specified data input rate. This approach comes with a drawback: At times of decreased data input rates, the cluster resources are not fully utilized. A typical use case is the HLT-Chain application that processes physics data at runtime of the ALICE experiment at CERN. From a perspective of cost and efficiency it is desirable to exploit temporarily unused cluster resources. Existing approaches aim for that goal by running additional applications. These approaches, however, a) lack in flexibility to dynamically grant the time-critical application the resources it needs, b) are insufficient for isolating the time-critical application from harmful side-effects introduced by additional applications or c) are not general because application-specific interfaces are used. In this thesis, a software framework is presented that allows to exploit unused resources in a dedicated cluster without harming a time-critical application. Additional applications are hosted in Virtual Machines (VMs) and unused cluster resources are allocated to these VMs at runtime. In order to avoid resource bottlenecks, the resource usage of VMs is dynamically modified according to the needs of the time-critical application. For this purpose, a number of previously not combined methods is used. On a global level, appropriate VM manipulations like hot migration, suspend/resume and start/stop are determined by an informed search heuristic and applied at runtime. Locally on cluster nodes, a feedback-controlled adaption of VM resource usage is carried out in a decentralized manner. The employment of this framework allows to increase a cluster’s usage by running additional applications, while at the same time preventing negative impact towards a time-critical application. This capability of the framework is shown for the HLT-Chain application: In an empirical evaluation the cluster CPU usage is increased from 49% to 79%, additional results are computed and no negative effect towards the HLT-Chain application are observed

Virtual machine scheduling in dedicated computing clusters

Time-critical applications process a continuous stream of input data and have to meet specific timing constraints. A common approach to ensure that such an application satisfies its constraints is over-provisioning: The application is deployed in a dedicated cluster environment with enough processing power to achieve the target performance for every specified data input rate. This approach comes with a drawback: At times of decreased data input rates, the cluster resources are not fully utilized. A typical use case is the HLT-Chain application that processes physics data at runtime of the ALICE experiment at CERN. From a perspective of cost and efficiency it is desirable to exploit temporarily unused cluster resources. Existing approaches aim for that goal by running additional applications. These approaches, however, a) lack in flexibility to dynamically grant the time-critical application the resources it needs, b) are insufficient for isolating the time-critical application from harmful side-effects introduced by additional applications or c) are not general because application-specific interfaces are used. In this thesis, a software framework is presented that allows to exploit unused resources in a dedicated cluster without harming a time-critical application. Additional applications are hosted in Virtual Machines (VMs) and unused cluster resources are allocated to these VMs at runtime. In order to avoid resource bottlenecks, the resource usage of VMs is dynamically modified according to the needs of the time-critical application. For this purpose, a number of previously not combined methods is used. On a global level, appropriate VM manipulations like hot migration, suspend/resume and start/stop are determined by an informed search heuristic and applied at runtime. Locally on cluster nodes, a feedback-controlled adaption of VM resource usage is carried out in a decentralized manner. The employment of this framework allows to increase a cluster’s usage by running additional applications, while at the same time preventing negative impact towards a time-critical application. This capability of the framework is shown for the HLT-Chain application: In an empirical evaluation the cluster CPU usage is increased from 49% to 79%, additional results are computed and no negative effect towards the HLT-Chain application are observed

Resource Management for Edge Computing in Internet of Things (IoT)

Die große Anzahl an Geräten im Internet der Dinge (IoT) und deren kontinuierliche Datensammlungen führen zu einem rapiden Wachstum der gesammelten Datenmenge. Die Daten komplett mittels zentraler Cloud Server zu verarbeiten ist ineffizient und zum Teil sogar unmöglich oder unnötig. Darum wird die Datenverarbeitung an den Rand des Netzwerks verschoben, was zu den Konzepten des Edge Computings geführt hat. Informationsverarbeitung nahe an der Datenquelle (z.B. auf Gateways und Edge Geräten) reduziert nicht nur die hohe Arbeitslast zentraler Server und Netzwerke, sondern verringer auch die Latenz für Echtzeitanwendungen, da die potentiell unzuverlässige Kommunikation zu Cloud Servern mit ihrer unvorhersehbaren Netzwerklatenz vermieden wird. Aktuelle IoT Architekturen verwenden Gateways, um anwendungsspezifische Verbindungen zu IoT Geräten herzustellen. In typischen Konfigurationen teilen sich mehrere IoT Edge Geräte ein IoT Gateway. Wegen der begrenzten verfügbaren Bandbreite und Rechenkapazität eines IoT Gateways muss die Servicequalität (SQ) der verbundenen IoT Edge Geräte über die Zeit angepasst werden. Nicht nur um die Anforderungen der einzelnen Nutzer der IoT Geräte zu erfüllen, sondern auch um die SQBedürfnisse der anderen IoT Edge Geräte desselben Gateways zu tolerieren. Diese Arbeit untersucht zuerst essentielle Technologien für IoT und existierende Trends. Dabei werden charakteristische Eigenschaften von IoT für die Embedded Domäne, sowie eine umfassende IoT Perspektive für Eingebettete Systeme vorgestellt. Mehrere Anwendungen aus dem Gesundheitsbereich werden untersucht und implementiert, um ein Model für deren Datenverarbeitungssoftware abzuleiten. Dieses Anwendungsmodell hilft bei der Identifikation verschiedener Betriebsmodi. IoT Systeme erwarten von den Edge Geräten, dass sie mehrere Betriebsmodi unterstützen, um sich während des Betriebs an wechselnde Szenarien anpassen zu können. Z.B. Energiesparmodi bei geringen Batteriereserven trotz gleichzeitiger Aufrechterhaltung der kritischen Funktionalität oder einen Modus, um die Servicequalität auf Wunsch des Nutzers zu erhöhen etc. Diese Modi verwenden entweder verschiedene Auslagerungsschemata (z.B. die übertragung von Rohdaten, von partiell bearbeiteten Daten, oder nur des finalen Ergebnisses) oder verschiedene Servicequalitäten. Betriebsmodi unterscheiden sich in ihren Ressourcenanforderungen sowohl auf dem Gerät (z.B. Energieverbrauch), wie auch auf dem Gateway (z.B. Kommunikationsbandbreite, Rechenleistung, Speicher etc.). Die Auswahl des besten Betriebsmodus für Edge Geräte ist eine Herausforderung in Anbetracht der begrenzten Ressourcen am Rand des Netzwerks (z.B. Bandbreite und Rechenleistung des gemeinsamen Gateways), diverser Randbedingungen der IoT Edge Geräte (z.B. Batterielaufzeit, Servicequalität etc.) und der Laufzeitvariabilität am Rand der IoT Infrastruktur. In dieser Arbeit werden schnelle und effiziente Auswahltechniken für Betriebsmodi entwickelt und präsentiert. Wenn sich IoT Geräte in der Reichweite mehrerer Gateways befinden, ist die Verwaltung der gemeinsamen Ressourcen und die Auswahl der Betriebsmodi für die IoT Geräte sogar noch komplexer. In dieser Arbeit wird ein verteilter handelsorientierter Geräteverwaltungsmechanismus für IoT Systeme mit mehreren Gateways präsentiert. Dieser Mechanismus zielt auf das kombinierte Problem des Bindens (d.h. ein Gateway für jedes IoT Gerät bestimmen) und der Allokation (d.h. die zugewiesenen Ressourcen für jedes Gerät bestimmen) ab. Beginnend mit einer initialen Konfiguration verhandeln und kommunizieren die Gateways miteinander und migrieren IoT Geräte zwischen den Gateways, wenn es den Nutzen für das Gesamtsystem erhöht. In dieser Arbeit werden auch anwendungsspezifische Optimierungen für IoT Geräte vorgestellt. Drei Anwendungen für den Gesundheitsbereich wurden realisiert und für tragbare IoT Geräte untersucht. Es wird auch eine neuartige Kompressionsmethode vorgestellt, die speziell für IoT Anwendungen geeignet ist, die Bio-Signale für Gesundheitsüberwachungen verarbeiten. Diese Technik reduziert die zu übertragende Datenmenge des IoT Gerätes, wodurch die Ressourcenauslastung auf dem Gerät und dem gemeinsamen Gateway reduziert wird. Um die vorgeschlagenen Techniken und Mechanismen zu evaluieren, wurden einige Anwendungen auf IoT Plattformen untersucht, um ihre Parameter, wie die Ausführungszeit und Ressourcennutzung, zu bestimmen. Diese Parameter wurden dann in einem Rahmenwerk verwendet, welches das IoT Netzwerk modelliert, die Interaktion zwischen Geräten und Gateway erfasst und den Kommunikationsoverhead sowie die erreichte Batterielebenszeit und Servicequalität der Geräte misst. Die Algorithmen zur Auswahl der Betriebsmodi wurden zusätzlich auf IoT Plattformen implementiert, um ihre Overheads bzgl. Ausführungszeit und Speicherverbrauch zu messen

Limits to parallelism in scientific computing

The goal of our research is to decrease the execution time of scientific computing applications. We exploit the application\u27s inherent parallelism to achieve this goal. This exploitation is expensive as we analyze sequential applications and port them to parallel computers. Many scientifically computational problems appear to have considerable exploitable parallelism; however, upon implementing a parallel solution on a parallel computer, limits to the parallelism are encountered. Unfortunately, many of these limits are characteristic of a specific parallel computer. This thesis explores these limits.;We study the feasibility of exploiting the inherent parallelism of four NASA scientific computing applications. We use simple models to predict each application\u27s degree of parallelism at several levels of granularity. From this analysis, we conclude that it is infeasible to exploit the inherent parallelism of two of the four applications. The interprocessor communication of one application is too expensive relative to its computation cost. The input and output costs of the other application are too expensive relative to its computation cost. We exploit the parallelism of the remaining two applications and measure their performance on an Intel iPSC/2 parallel computer. We parallelize an Optimal Control Boundary Value Problem. This guidance control problem determines an optimal trajectory of a boat in a river. We parallelize the Carbon Dioxide Slicing technique which is a macrophysical cloud property retrieval algorithm. This technique computes the height at the top of a cloud using cloud imager measurements. We consider the feasibility of exploiting its massive parallelism on a MasPar MP-2 parallel computer. We conclude that many limits to parallelism are surmountable while other limits are inescapable.;From these limits, we elucidate some fundamental issues that must be considered when porting similar problems to yet-to-be designed computers. We conclude that the technological improvements to reduce the isolation of computational units frees a programmer from many of the programmer\u27s current concerns about the granularity of the work. We also conclude that the technological improvements to relax the regimented guidance of the computational units allows a programmer to exploit the inherent heterogeneous parallelism of many applications

Discrete Wavelet Transform and Optimal Spectral Transform Applied to Multicomponent Image Coding

ISBN 978-953-307-482-5 Chapitre 10International audienc

Radio Communications

In the last decades the restless evolution of information and communication technologies (ICT) brought to a deep transformation of our habits. The growth of the Internet and the advances in hardware and software implementations modified our way to communicate and to share information. In this book, an overview of the major issues faced today by researchers in the field of radio communications is given through 35 high quality chapters written by specialists working in universities and research centers all over the world. Various aspects will be deeply discussed: channel modeling, beamforming, multiple antennas, cooperative networks, opportunistic scheduling, advanced admission control, handover management, systems performance assessment, routing issues in mobility conditions, localization, web security. Advanced techniques for the radio resource management will be discussed both in single and multiple radio technologies; either in infrastructure, mesh or ad hoc networks

Wireless video streaming for single-hop networks

Limited bandwidth and high packet loss rate pose a serious challenge for video streaming applications over wireless networks. Even when packet loss is not present, the bandwidth fluctuation as a result of an arbitrary number of active flows in an IEEE 802.11 network, can significantly degrade the video quality. This paper aims to enhance the quality of video streaming applications in wireless home networks via a joint optimization of video coding technique, admission control algorithm, and Medium Access Control (MAC) protocol. Using an Aloha-like MAC protocol, we propose a novel admission control framework, which can be viewed as an optimization problem that maximizes the average quality of admitted videos, given a specified minimum video quality for each flow. We present some hardness results for the optimization problem under various conditions, and propose some heuristic algorithms for finding a good solution. In particular, we show that a simple greedy layer-allocation algorithm can perform reasonably well, although it is typically not optimal. Consequently, we present a more expensive heuristic algorithm that guarantees to approximate the optimal solution within a constant factor. Simulation results demonstrate that our proposed framework can improve the video quality up to 26% as compared to those of the existing approaches

Programming a Gate-based Quantum Computer: a Comparative Analysis of the Software Development Kits for Circuit Design Automation

openThe rapid development of gate-based Quantum Computers has opened new possibilities for solving complex computational problems. However, programming these quantum systems has to deal with new challenges due to the fundamental differences between classical and Quantum Computing paradigms. This thesis presents a comparative analysis of Software Development Kits (SDKs) conceived for circuit design automation in gate-based quantum computers. The objective of this research is to evaluate and compare the capabilities, features, and usability of existing SDKs focusing on the functionalities such as allowing users to define quantum circuits, apply gate operations, and simulate their behaviour.   Apart from the widely adopted frameworks such as Qiskit, TKET, and Cirq, the analysis also includes the recently developed SDK from the University of Padua: Quantum Matcha Tea. The comparative analysis is conducted through a series of experiments and benchmarks performed on each SDK having as central points the programming interfaces usability, the documentation completeness, and the availability of support provided by the vendor or the related developer community. Another goal of this work is to explore the efficiency and flexibility of the various SDKs in handling common quantum computing tasks, such as quantum circuit design, gate operation, and circuit execution both on simulators and real quantum hardware.   The ambition of this comparative analysis is to give useful insights to researchers, developers, and practitioners in order to identify strengths and weaknesses of different SDKs depending on the specific requirements of the algorithms that need to be implemented. Additionally, the research aims to contribute to the advancement of SDKs by identifying areas of improvement and potential future directions in the development of quantum programming tools.The rapid development of gate-based Quantum Computers has opened new possibilities for solving complex computational problems. However, programming these quantum systems has to deal with new challenges due to the fundamental differences between classical and Quantum Computing paradigms. This thesis presents a comparative analysis of Software Development Kits (SDKs) conceived for circuit design automation in gate-based quantum computers. The objective of this research is to evaluate and compare the capabilities, features, and usability of existing SDKs focusing on the functionalities such as allowing users to define quantum circuits, apply gate operations, and simulate their behaviour.   Apart from the widely adopted frameworks such as Qiskit, TKET, and Cirq, the analysis also includes the recently developed SDK from the University of Padua: Quantum Matcha Tea. The comparative analysis is conducted through a series of experiments and benchmarks performed on each SDK having as central points the programming interfaces usability, the documentation completeness, and the availability of support provided by the vendor or the related developer community. Another goal of this work is to explore the efficiency and flexibility of the various SDKs in handling common quantum computing tasks, such as quantum circuit design, gate operation, and circuit execution both on simulators and real quantum hardware.   The ambition of this comparative analysis is to give useful insights to researchers, developers, and practitioners in order to identify strengths and weaknesses of different SDKs depending on the specific requirements of the algorithms that need to be implemented. Additionally, the research aims to contribute to the advancement of SDKs by identifying areas of improvement and potential future directions in the development of quantum programming tools