Software implementation of multiple embedded control loops often share compute resources. The control performance of such implementations have been shown to improve if the sharing of bandwidth between control loops can be dynamically regulated in response to input disturbances. In the absence of a structured methodology for planning such measures, the scheduler may spend too much time in deciding the optimal scheduling pattern. Our work leverages well known results in the domain of network control systems and applies them in the context of bandwidth sharing among controllers. We provide techniques that may be used a priori for computing co-schedulable execution patterns for a given set of control loops such that stability is guaranteed under all possible disturbance scenarios. Additionally, the design of the control loops optimize the average case control performance by adaptive sharing of bandwidth under time varying input disturbances.

A wide variety of periodic tasks in embedded systems require reliable service guarantees under a given fault distribution. Reliable execution requires the periodic task to be replicated more often under normal circumstances so that the desired service throughput is achieved under the fault distribution. This paper presents a formal approach for verifying whether an input distribution meets the desired service guarantee under a fault distribution, where all the distributions are specified in real time calculus. The proposed methodology leverages the recently discovered relationship between real time calculus specifications and omega-regular languages.

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