@INPROCEEDINGS{Pietri2013,
AUTHOR="Marcello Pietri and Stefania Tosi and Mauro Andreolini and Michele
Colajanni",
TITLE="{Real-Time} Adaptive Algorithm for Resource Monitoring",
BOOKTITLE="9th International Conference on Network and Service Management 2013 (CNSM
2013)",
ADDRESS="Zürich, Switzerland",
DAYS=14,
MONTH=Oct,
YEAR=2013,
pages = {67-74},
KEYWORDS="Adaptive Sampling; Monitoring; Cloud Computing; Large-Scale; Scalability",
ABSTRACT="In large scale systems, real-time monitoring of hardware and software
resources is a crucial means for any management purpose. In architectures
consisting of thousands of servers and hundreds of thousands of component
resources, the amount of data monitored at high sampling frequencies
represents an overhead on system performance and communication, while
reducing sampling may cause quality degradation. We present a real-time
adaptive algorithm for scalable data monitoring that is able to adapt the
frequency of sampling and data updating for a twofold goal: to minimize
computational and communication costs, to guarantee that reduced samples do
not affect the accuracy of information about resources. Experiments carried
out on heterogeneous data traces referring to synthetic and real
environments confirm that the proposed adaptive approach reduces
utilization and communication overhead without penalizing the quality of
data with respect to existing monitoring algorithms."
}