However, the inherent dynamic of self-adaptive systems requires intensive evaluation and benchmarking efforts in order to ensure the intended system behaviour.

One promising approach to cope with these challenges are self-adaptive distributed systems that are characterized by the capability to configure and maintain.

However, the inherent dynamic of self-adaptive systems requires intensive evaluation and benchmarking efforts in order to ensure the intended system behaviour.

For instance, both dependability and performance metrics were embedded in benchmarking resilience, in order to evaluate "if a system is effective and efficient ...

In fact, currently there is no practical way to characterize self-daptation capabilities, especially when comparing alternative systems concerning resilience.

Oct 22, 2024 · The problem is that nowadays there is no practical way to characterize self-adaptation capabilities or to compare alternative solutions ...

The self-adaptive distributed decision support model consists of three major components: environment recognition, knowledge merging and decision making.

that aim to support time series forecasting: linear time series, neural net- works, wavelet analysis, support vector machines (SVM), fuzzy systems. The ...

Apr 15, 2024 · We evaluate AntDT by three typical workloads over two open-source benchmarks and one Ant Group production dataset in the TensorFlow Parameter ...

Large-Scale Distributed Systems. Panel ... – Developing benchmarks to evaluate “-ilities” ... – Embodying the results in techniques for self-adaptive systems.