@article {10.3844/jcssp.2006.513.520,
article_type = {journal},
title = {Predictive Autonomicity of Web Services in the MAWeS Framework},
author = {Mancini, Emilio P. and Rak, Massimiliano and Torella, Roberto and Villano, Umberto},
volume = {2},
number = {6},
year = {2006},
month = {Jun},
pages = {513-520},
doi = {10.3844/jcssp.2006.513.520},
url = {https://thescipub.com/abstract/jcssp.2006.513.520},
abstract = {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. },
journal = {Journal of Computer Science},
publisher = {Science Publications}
}