Towards self-powered wireless sensor networks

Ubiquitous computing aims at creating smart environments in which computational and communication capabilities permeate the word at all scales, improving the human experience and quality of life in a totally unobtrusive yet completely reliable manner. According to this vision, an huge variety of smart devices and products (e.g., wireless sensor nodes, mobile phones, cameras, sensors, home appliances and industrial machines) are interconnected to realize a network of distributed agents that continuously collect, process, share and transport information. The impact of such technologies in our everyday life is expected to be massive, as it will enable innovative applications that will profoundly change the world around us. Remotely monitoring the conditions of patients and elderly people inside hospitals and at home, preventing catastrophic failures of buildings and critical structures, realizing smart cities with sustainable management of traffic and automatic monitoring of pollution levels, early detecting earthquake and forest fires, monitoring water quality and detecting water leakages, preventing landslides and avalanches are just some examples of life-enhancing applications made possible by smart ubiquitous computing systems. To turn this vision into a reality, however, new raising challenges have to be addressed, overcoming the limits that currently prevent the pervasive deployment of smart devices that are long lasting, trusted, and fully autonomous. In particular, the most critical factor currently limiting the realization of ubiquitous computing is energy provisioning. In fact, embedded devices are typically powered by short-lived batteries that severely affect their lifespan and reliability, often requiring expensive and invasive maintenance. In this PhD thesis, we investigate the use of energy-harvesting techniques to overcome the energy bottleneck problem suffered by embedded devices, particularly focusing on Wireless Sensor Networks (WSNs), which are one of the key enablers of pervasive computing systems. Energy harvesting allows to use energy readily available from the environment (e.g., from solar light, wind, body movements, etc.) to significantly extend the typical lifetime of low-power devices, enabling ubiquitous computing systems that can last virtually forever. However, the design challenges posed both at the hardware and at the software levels by the design of energy-autonomous devices are many. This thesis addresses some of the most challenging problems of this emerging research area, such as devising mechanisms for energy prediction and management, improving the efficiency of the energy scavenging process, developing protocols for harvesting-aware resource allocation, and providing solutions that enable robust and reliable security support. %, including the design of mechanisms for energy prediction and management, improving the efficiency of the energy harvesting process, the develop of protocols for harvesting-aware resource allocation, and providing solutions that enable robust and reliable security support

Compositional Scheduling Analysis Using Standard Event Models

Embedded real-time systems must meet a variety of timing requirements, such as deadlines and limited load or bandwidth. These properties depend heavily on interactions between tasks and on the scheduling of tasks and communications. Unfortunately, the current practice of specialization and re-use results in increasingly heterogeneous systems, which specifically complicates the scheduling analysis problem. Todays best practice of timed simulation is increasingly unreliable, mainly because the corner cases are extremely difficult to find and debug. As an alternative, a variety of systematic and formal approaches to scheduling analysis have been proposed. Most of them, however, are either limited to sub-problems, or use unwieldy and complex models that distract designers in practice. This thesis presents a novel, structured analysis procedure that a) can cope with the increasing complexity and heterogeneity of embedded systems, b) provides the modularity and flexibility that the established, re-use driven system integration style requires, and c) facilitates system integration using a comprehensible analytical model. The approach uses intuitive and standardized event models to represent the interfaces between different components and their scheduling. The clear interface structure allows -for the first time- the modular composition of heterogeneous sub-system analysis techniques. This provides designers with the flexibility to use their preferred scheduling and analysis techniques locally without compromising global scheduling analysis. This new analysis procedure has been implemented in the SymTA/S tool. As it can be efficiently applied in practice, it provides a serious and promising complement to simulation.Eingebettete Echtzeitsysteme müssen eine Vielzahl von Zeit- und Performanzanforderungen erfüllen, z.B. maximale Reaktionszeiten oder vorgegebene Kommunikationsbandbreiten. Die Echtzeiteigenschaften hängen stark vom Zusammenspiel der Einzelkomponenten sowie deren Scheduling ab. Unglücklicherweise führt gerade die in der Praxis etablierte Wiederverwendung von spezialisierten Komponenten zu einer Heterogenität, die die Schedulinganalyse zusätzlich erschwert. Die heute eingesetzten Simulationsverfahren sind zusehends unzuverlässig, da die kritischen Randfälle in der Praxis kaum mehr vollständig bestimmt werden können. Als Alternative wurde eine Vielzahl systematischer und formaler Ansätze vorgeschlagen. Meist sind diese jedoch entweder auf spezielle Teilprobleme beschränkt oder für den Allgemeinfall zu unhandlich und finden daher nur eine geringe Akzeptanz in der industriellen Praxis. In dieser Arbeit wird ein neues Verfahren zur Schedulinganalyse vorgestellt, das a) die steigende Komplexität und Heterogenität angemessen erfasst, b) über die Modularität und Flexibilität verfügt, die mit Wiederverwendung und Integration erforderlich ist, und c) die Integration durch ein nachvollziehbares Analysemodell unterstützt. Das Analysemodell erfasst die komplexen Abhängigkeiten zwischen Komponenten mit Hilfe von intuitiven, standardisierten Ereignismodellen. Die klare Strukturierung dieser Schnittstellen erlaubt erstmals die modulare Komposition von Analysen heterogener Systemteile. Dies gibt Entwicklern die nötige Flexibilität, ihre bevorzugten lokalen Entwurfsmethoden zu benutzen, ohne auf die globale Schedulinganalyse verzichten zu müssen. Das Verfahren bildet die Grundlage für das SymTA/S Analysewerkzeug und ist in der Praxis sehr effizient einsetzbar, womit sich eine ernstzunehmende und viel versprechende Ergänzung zur heute etablierten Performanz-Simulation eröffnet

Aportes a la reducción de consumo en FPGAs

Tesis doctoral inédita leída en la Universidad Autónoma de Madrid. Escuela Politécnica Superior, Departamento de Ingeniería Informática. Fecha de lectura: 15-04-200