Real-time scheduling for energy harvesting sensor nodes

Energy harvesting has recently emerged as a feasible option to increase the operating time of sensor networks. If each node of the network, however, is powered by a fluctuating energy source, common power management solutions have to be reconceived. This holds in particular if real-time responsiveness of a given application has to be guaranteed. Task scheduling at the single nodes should account for the properties of the energy source, capacity of the energy storage as well as deadlines of the single tasks. We show that conventional scheduling algorithms (like e.g. EDF) are not suitable for this scenario. Based on this motivation, we have constructed optimal scheduling algorithms that jointly handle constraints from both energy and time domain. Further we present an admittance test that decides for arbitrary task sets, whether they can be scheduled without deadline violations. To this end, we introduce the concept of energy variability characterization curves (EVCC) which nicely captures the dynamics of various energy sources. Simulation results show that our algorithms allow significant reductions of the battery size compared to Earliest Deadline First scheduling.

A General Framework for Expressing Preferences in Causal Reasoning and Planning

We consider the problem of representing arbitrary preferencesin causal reasoning and planning systems. In planning, a preferencemay be seen as a goal or constraint that is desirable, but notnecessary, to satisfy. To begin, we define a very general querylanguage for histories, or interleaved sequences of world statesand actions. Based on this, we specify a second language inwhich preferences are defined. A single preference defines abinary relation on histories, indicating that one history ispreferred to the other. From this, one can define global preferenceorderings on the set of histories, the maximal elements of whichare the preferred histories. The approach is very general andflexible; thus it constitutes a ‘base’ languagein terms of which higher-level preferences may be defined. Tothis end, we investigate two fundamental types of preferencesthat we call choice and temporal preferences. We consider concretestrategies for these types of preferences and encode them interms of our framework. We suggest how to express aggregatesin the approach, allowing, e.g. the expression of a preferencefor histories with lowest total action costs. Last, our approachcan be used to express other approaches and so serves as a commonframework in which such approaches can be expressed and compared.We illustrate this by indicating how an approach due to Sonand Pontelli can be encoded in our approach, as well as thelanguage PDDL3.     

Service level management with agent technology

This paper outlines a generic evaluation methodology for multimedia and real time applications. It concentrates on the application layer and the service aspect. Principles of software evaluation for quality assessment and measurement for networked services and distributed applications are used to present a specific method for measuring important characteristics. The method and the measurement procedure allow comparison of the actual characteristics of service quality with the required characteristics and thresholds. The proof of concepts will be made by the implementation of quality measurement agents following the approach outlined in this paper. Our approach of performing service level management (SLM) with agent technology is distributed, slim, minimizable to the maximum, independent in its methodology and offers comparable, objective results.     

Design for Timing Predictability

A large part of safety-critical embedded systems has to satisfy hard real-time constraints. These need sound methods and tools to derive run-time guarantees that are not only reliable but also precise. The achievable precision highly depends on characteristics of the target architecture, the implementation methods and system layers of the software. Trends in hardware and software design run contrary to predictability. This article describes threats to timing predictability of systems, and proposes design principles that support timing predictability. The ultimate goal is to design performant systems with sharp upper and lower bounds on execution times.     

Reactor Concept for Contactless Kinetic Measurement in Oscillating Droplets via Raman Spectroscopy

A millistructured reactor and spectroscopic setup for contactless kinetic measurements in oscillating droplets is presented in this work. The polymerization of acrylic acid serves as a model reaction. Design and construction of the reactor focus on the optical access for Raman measurement, the nearly isothermal behavior, and the preservation of droplets during long‐term reactions with a high increase of viscosity. Another key aspect is the possibility of full automation at a later stage.     

Real-time worst-case temperature analysis with temperature-dependent parameters

With the evolution of today’s semiconductor technology, chip temperature increases rapidly mainly due to the growth in power density. Therefore, for modern embedded real-time systems it is crucial to estimate maximal temperatures early in the design in order to avoid burnout and to guarantee that the system can meet its real-time constraints. This paper provides answers to a fundamental question: What is the worst-case peak temperature of a real-time embedded system under all feasible scenarios of task arrivals? A novel thermal-aware analytic framework is proposed that combines a general event/resource model based on network and real-time calculus with system thermal equations. This analysis framework has the capability to handle a broad range of uncertainties in terms of task execution times, task invocation periods, jitter in task arrivals, and resource availability. The considered model takes both dynamic and leakage power as well as thermal dependent conductivity into consideration. Thorough simulation experiments validate the theoretical results.