No author has a financial or proprietary interest in any material or method mentioned.

One of the main predictability bottlenecks of modern multi-core embedded systems is contention for access to shared memory resources. Partitioning and software-driven allocation of memory resources is an effective strategy to mitigate contention in the memory hierarchy. Unfortunately, however, many of the strategies adopted so far can have unforeseen side-effects when practically implemented latest-generation, highperformance embedded platforms. Predictability is further jeopardized by cache eviction policies based on random replacement, targeting average performance instead of timing determinism. In this paper, we present a framework of software-based techniques to restore memory access determinism in highperformance embedded systems. Our approach leverages OStransparent and DMA-friendly cache coloring, in combination with an invalidation-driven allocation (IDA) technique. The proposed method allows protecting important cache blocks from (i) external eviction by tasks concurrently executing on different cores, and (ii) internal eviction by tasks running on the same core. A working implementation obtained by extending the Jailhouse partitioning hypervisor is presented and evaluated with a combination of synthetic and real benchmarks.

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A data chain is a sequence of periodic realtime communicating tasks that are processing the data from sensors up to actuators. It determines an order in which the tasks propagate data but not in which they are executed: inter-task communication and scheduling are independent. In this paper, we focus on the latency computation, considered as the time elapsed from getting the data from an input and processing it to an output of a data chain. We propose a method for the worst-case latency calculation of periodic tasks' data chains executed by a partitioned fixed-priority preemptive scheduler upon a multiprocessor platform. As far as we know, there is no such formal approach based on closed-form expression for communicating real-time tasks.