The Bus Goes Wireless: Routing-Free Data Collection with QoS Guarantees in Sensor Networks

Abstract—We present the low-power wireless bus (LWB), a new communication paradigm for QoS-aware data collection in lowpower sensor networks. The LWB maps all communication onto network floods by using Glossy, an efficient flooding architecture for wireless sensor networks. Therefore, unlike current solutions, the LWB requires no information of the network topology, and inherently supports networks with mobile nodes and multiple data sinks. A LWB prototype implemented in Contiki guarantees bounded end-to-end communication delay and duplicate-free, inorder packet delivery—key QoS requirements in many control and mission-critical applications. Experiments on two testbeds demonstrate that the LWB prototype outperforms state-of-theart data collection and link layer protocols, in terms of reliability and energy efficiency. For instance, we measure an average radio duty cycle of 1.69 % and an overall data yield of 99.97 % in a typical data collection scenario with 85 sensor nodes on Twist. I

03471 Abstracts Collection -- Design of Systems with Predictable Behaviour

On 16.11.-19.11.2003, the Perspectives Workshop 03471 "Design of Systems with Predictable Behaviour" was held in the International Conference and Research Center (IBFI), Schloss Dagstuhl. During the workshop, several participants presented their current research, and ongoing work and open problems were discussed. Abstracts of the presentations given during the seminar as well a digest of seminar results and ideas are put together in this paper. The first section describes the seminar topics and goals in general. Links to extended abstracts or full papers are provided, if available

Design for Time-Predictability

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

An Adaptive Scheme to Generate the Pareto Front Based on the Epsilon-Constraint Method

We discuss methods for generating or approximating the Pareto set of multiobjective optimization problems by solving a sequence of constrained single-objective problems. The necessity of determining the constraint value a priori is shown to be a serious drawback of the original epsilon-constraint method. We therefore propose a new, adaptive scheme to generate appropriate constraint values during the run. A simple example problem is presented, where the running time (measured by the number of constrained single-objective sub-problems to be solved) of the original epsilon-constraint method is exponential in the problem size (number of decision variables), although the size of the Pareto set grows only linearly. We prove that --- independent of the problem or the problem size --- the time complexity of the new scheme is O(k^{m-1}), where k is the number of Pareto-optimal solutions to be found and m the number of objectives. Simulation results for the example problem as well as for different instances of the multiobjective knapsack problem demonstrate the behavior of the method, and links to reference implementations are provided

Quantitative Characterization of Event Streams in Analysis of Hard Real-Time Applications

Many real-time embedded systems process event streams that are composed of a finite number of different event types. Each different event type on the stream would typically impose a different workload to the system, and thus the knowledge of possible correlations and dependencies between the different event types could be exploited to get tighter analytic performance bounds of the complete system. We propose an abstract stream model to characterize such an event stream. The model captures the needed information of all possible traces of a class of event streams. Hence, it can be used to obtain hard bounded worst-case and best-case analysis results of a system. We show how the proposed abstract stream model can be obtained from a concrete stream specification, and how it can be used for performance analysis. The applicability of our approach and its advantages over traditional worst-case performance analysis are shown in a case study of a multimedia applicatio