Many embedded system applications are implemented today using distributed architectures, consisting of several hardware nodes interconnected in a network. Each hardware node can consist of a processor, memory, interfaces to I/O and to the network. The networks are using specialized communication protocols, depending on the application area. For example, in the automotive electronics area communication protocols such as CAN, FlexRay and TTP are used.

As the complexity of the functionality increases, the way it is distributed has changed. If we take as an example the automotive applications, initially, each function was running on a dedicated hardware node, allowing the system integrators to purchase nodes implementing required functions from different vendors, and to integrate them into their system. Currently, number of such nodes has reached more than 100 in a high-end car, which can lead to large cost and performance penalties.

Not only the number of nodes has increased, but the resulting solutions based on dedicated hardware nodes do not use the available resources efficiently in order to reduce costs. For example, it should be possible to move functionality from one node to another node where there are enough resources (e.g., memory) available. Moreover, emerging functionality, such as brake-by-wire, is inherently distributed, and achieving an efficient fault-tolerant implementation is very difficult in the current setting.
Moreover, as the communications become a critical component, new protocols are needed that can cope with the high bandwidth and predictability required. The trend is towards hybrid communication protocols, such as the FlexRay protocol, which allows the sharing of the bus by event-driven and time-driven messages. Time-triggered protocols have the advantage of simplicity and predictability, while event-triggered protocols are flexible and have low cost. A hybrid communication protocol like FlexRay offers some of the advantages of both worlds.

With growing embedded system complexity more and more parts of a system are reused or supplied, often from external sources. These parts range from single hardware components or software processes to hardware-software (HW-SW) subsystems. They must cooperate and share resources with newly developed parts such that the design constraints are met. There are many software interface standards such as CORBA, COM or DCOM, to name just a few examples that are specifically designed for that task. Nevertheless in practice, software integration is not a solved but a growing problem.

New design optimization tools are needed to handle the increasing complexity of such systems, and their competing requirements in terms of performance, reliability, low power consumption, cost, time-to-market, etc. As the complexity of the systems continues to increase, the development time lengthens dramatically, and the manufacturing costs become prohibitively high. To cope with this complexity, it is necessary to reuse as much as possible at all levels of the design process, and to work at higher and higher abstraction levels.

One of the most significant achievements in the cultural landscape of low-power embedded systems design is the consensus on the strategic role of power management technology. It is now widely acknowledged that resource usage in embedded system platforms depends on application workload characteristics, desired quality of service and environmental conditions. System workload is highly non-stationary due to the heterogeneous nature of information content. Quality of service depends on user requirements, which may change over time. In addition, both can be affected by environmental conditions such as network congestion and wireless link quality.

Power management is viewed as a strategic technology both for integrated and distributed embedded systems. In the first area, the trend is toward supporting power management in multi-core architectures, with a large number of power-manageable resourcers. Silicon technology is rapidly evolving to provide an increased level of control of-on chip power resources. Technologies such as multiple power distribution regions, multiple power-gating circuits for partial shutdown, multiple variable-voltage supply circuits are now commonplace. In the area of distributed low-power systems, wireless sensor networks are the key technology drivers, given their tightly power constrained nature. One important trend in this area is toward “battery free” operation. This can be achieved through energy storage devices (e.g. super-capacitors) coupled with additional devices capable of harversting energy from environmental sources (e.g. solar energy, vibrational energy). Battery-free operation requires carefully balancing harvested energy and stored energy agains the energy consumed by the system, in a compromise between quality of service and sustainable lifetime.

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