To make distributed systems resource aware and adaptive, they can be modeled as self-adaptive systems. Such systems have a view of their own state and context, which can be represented by a model that is continuously updated and analyzed at runtime. However, such analyses need to be concise and efficient to allow large models and high adaptation rates. To achieve this, we apply reference attribute grammar controlled rewriting to implement the runtime model of a distributed task-scheduling case study for energy optimization.
['Johannes Mey', 'René Schöne', 'Daniel Langner', 'Christoff Bürger']
Using reference attribute grammar-controlled rewriting for runtime resource management