Abstract:
Estimate request service demand is vital for resource management
and capacity planning in large web servicing system. Most existing works assume
the service demand is load-independent. This study showed that it is not the
case for modern processors with Dynamic Frequency Scaling (DFS) and Simultaneous
Multi-Threading (SMT) capabilities. Through experiments in a Xeon processor
under Linux, this study showed that the CPU demand can be modeled as a polynomial
function of CPU utilization with degree 2 or 3. This study proposed a quadratic
programming based optimization method to infer the polynomial coefficients from
readily available CPU utilization and response time data. Comparing with widely
used regression method, proposed optimization method can reduce the error by
more than half in most cases. Proposed method is also more accurate than the
existing load-dependent estimation method, particularly in workload of requests
with different sizes.
