By Vincenzo De Florio
"This publication is a entire number of wisdom on expanding the notions and versions in adaptive and constant platforms, improving the notice of the position of adaptability and resilience in process environments"--Provided by means of publisher.
summary: "This e-book is a finished selection of wisdom on expanding the notions and versions in adaptive and constant platforms, improving the notice of the function of adaptability and resilience in procedure environments"--Provided via writer
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Additional info for Innovations and approaches for resilient and adaptive systems
Example text
To summarize, both the physical components of the system (so-called hardware) and their usage (so-called software) are extremely dynamic in most modern system contexts (as conceptually shown in Figure 1). It is important that the system allows the exploitation of dynamism by having not so large load-independent cost as shown in Figure 2. Today many platforms are not designed to expose the underlying true cost Figure 1. Multi-pronged dynamism in modern system contexts Systematic Design Principles for Cost-Effective Hard Constraint Management Figure 2.
UBR_OW1 shows the schedule obtained by the reactive one-taskat-a-time strategy discussed before with these refined upper bounds. Note the better modes for T1 and T5, compared to DTWC_OW1. Optimize the Present and Future Together Up to now, the switching opportunities are still limited by the conservative assumption that the subsequent tasks might require worst-case mode. , considering the mode decisions of current and future tasks together. This not only increases switching opportunities but also avoids unnecessary switching oscillations and greedy slack usage.
Dynamic voltage and frequency scaling (DVFS or DVS) is the most popular knob available in many commercial processors. , 2005). Changing the knob settings involves non-negligible switching overhead, both in time and energy, which depends on the type of knobs, system state, and on the desired system configuration. The computational requirement of the tasks varies significantly (>10x) over time. , upper-bound, with the given knob setting and the actual time is only known at the completion of the task instance.