TY  - JOUR
AU  - Mancini, Emilio P. 
AU  - Rak, Massimiliano 
AU  - Torella, Roberto 
AU  - Villano, Umberto 
PY  - 2006
TI  - Predictive Autonomicity of Web Services in the MAWeS Framework
JF  - Journal of Computer Science
VL  - 2
IS  - 6
DO  - 10.3844/jcssp.2006.513.520
UR  - https://thescipub.com/abstract/jcssp.2006.513.520
AB  - In Web Services designs classical optimization techniques are not applicable. A possible solution to guarantee critical requirements is the use of an autonomic architecture, able to auto-configure and to auto-tune. This study presents MAWeS (MetaPL/HeSSE Autonomic Web Services), a framework whose aim is to support the development of self-optimizing predictive autonomic systems for Web service architectures. It adopts a simulation-based methodology, which allows to predict system performance in different status and load conditions. The predicted results are used for a feedforward control of the system, which self-tunes before the new conditions and the subsequent performance losses are actually observed.