We introduce a task model for embedded systems operating on packet streams, such as network processors. This model along with a calculus meant for reasoning about packet streams allows a unified treatment of several problems arising in the network packet processing domain such as packet scheduling, task scheduling and architecture/algorithm explorations in the design of network processors. The model can take into account quality of service constraints such as data throughput and deadlines associated with packets. To illustrate its potential, we provide two applications: (a) a new task scheduling algorithm for network processors to support a mix of real-time and non-real-time flows, (b) a scheme for design space exploration of network processors.

Abstract not found

With the term flexibility, we introduce a new design dimension of an embedded system that quantitatively characterizes its feasibility in implementing not only one, but possibly several alternative behaviors. This is important when designing systems that may adopt their behavior during operation, e.g., due to new environmental conditions, or when dimensioning a platform-based system that must implement a set of different behaviors. A hierarchical graph model is introduced that allows to model flexibility and cost of a system formally. Based on this model, an efficient exploration algorithm to find the optimal flexibility/cost-tradeoff-curve of a system using the example of the design of a family of Set-Top boxes is proposed.

In this chapter, we propose an approach for the synthesis of heterogenous embedded systems, including allocation and binding problems. For solving these in general NP-complete problems, Evolutionary Algorithms have been proven to provide good solutions for search spaces of moderate size. For realistic embedded system applications, however, two more challenges must be considered: a) the complexity of the search space, and b) the multi-objective nature of the optimization problem to solve. I.e., the desired result of system synthesis is a design space exploration that provides the set of so-called Pareto-optimal solutions or an approximation thereof instead of just a single solution. Here, we propose a solution based on a Multi-Objective Evolutionary Algorithm (MOEA) which denotes a class of Evolutionary Algorithms that have recently proposed for design space exploration problems. Secondly, in order to reduce the complexity of typical search spaces, we propose a hierarchical problem and solution structure.

In this paper we present an approach to incremental design of distributed embedded systems for hard real-time applications. We start from an already existing system running a set of applications and the design problem is to implement new functionality so that the already running applications are not disturbed and there is a good chance that, later, new functionality can easily be added to the resulted system. The mapping and scheduling problem are considered in the context of a realistic communication model based on a TDMA protocol. 1.

Wearable computing has recently gained much popularity as an ambitious vision for future personalized mobile systems. It targets intelligent, environment aware systems unobtrusively embedded into the mobile environments of the human body. With the combination of complex processing requirements, the necessity of placing sensors and input/output modules at different locations on the user's body, and stringent limits on size, weight and battery capacity, the design of such systems is an inherently difficult problem. This

The design of embedded systems has to address several interacting design dimensions to implement parallelism, distribution over different locations, hard real-time requirements and design space exploration today. Thus a structured design process has to deal with heterogeneous requirements and restrictions. The integration of dedicated tasks for HW-design and SW-design as well as real-time operating system functionality into the embedded system design flow is the main challenge. On system level, tasks must be mapped to complex functional units, with consideration of communications between the tasks and the costs for the functional units. The structured design process of an embedded system distinguishes among others specification, partitioning, HW-synthesis and SW-synthesis tasks. Keywords: automated system level synthesis, design methodology, embedded system design, HW/SW-system. 1 Introduction The design of embedded systems (ES) has to address several interacting design dimen...

This paper presents an approach for dynamic software reconfiguration in sensor networks. Our approach utilizes explicit models of the design space of the embedded application. The design space is captured by formally modeling all the software components, their interfaces, and their composition. System requirements are expressed as formal constraints on QoS parameters that are measured at runtime. Reconfiguration is performed by transitioning from one point of the operation space to another based on the constraints. We demonstrate our approach using simulation results for a simple sensor network that performs one-dimensional tracking.

This paper introduces design space exploration as one of the major tasks in embedded system design. After reviewing existing exploration methods at various layers of abstraction, a generic approach is described based on multi-objective criteria, black-box optimisation and randomised search strategies. The interface between problem-specific and generic parts of the exploration framework is made explicit by defining an interface called PISA. This specification and implementation interface and the availability of a wide range of randomised multi-objective search methods makes the proposed framework accessible to a wide range of exploration problems. It resolves the problem that existing optimisation methods can not be coupled easily to the problem-specific part of a design exploration tool. 1

Increasing reliability is one of the most important design goals for current and future embedded systems. In this paper, we will put focus on the design phase in which reliability constitutes one of several competing design objectives. Existing approaches considered the simultaneous optimization of reliability with other objectives to be too extensive. Hence, they firstly design a system, secondly analyze the system for reliability and finally exchange critical parts or introduce redundancy in order to satisfy given reliability constraints or optimize reliability. Unfortunately, this may lead to suboptimal designs concerning other design objectives. Here, we will present a) a novel approach that considers reliability with all other design objectives simultaneously, b) an evaluation technique that is able to perform a quantitative analysis in reasonable time even for real-world applications, and c) experimental results showing the effectiveness of our approach. 1.