movavg_lib.h File Reference
Public interface for the Moving Average predictor. More...
#include <linux/aquosa/rres_config.h>#include <linux/aquosa/qres_config.h>#include <linux/aquosa/qos_debug.h>Go to the source code of this file.
Defines | |
| #define | MOVAVG_DEF_SAMPLESIZE 3 |
| Default sample size. | |
| #define | MOVAVG_DEF_FORGETF 1.0 |
| Default forgetting factor. | |
Functions | |
| qos_rv | movavg_set_defaults (void) |
| Configures a Moving Average predictor with default parameters. | |
| qos_rv | movavg_set_sample_size (int sample_size) |
| Sets the sample size for the Moving Average predictor. | |
| qos_rv | movavg_set_forget_f (float ff) |
| Sets a forgetting factor lower than 1. | |
| qos_rv | movavg_register_lib (void) |
| Registration of the submodule with the library. | |
Detailed Description
Public interface for the Moving Average predictor.
A Moving Average predictor computes the expected value of the next sample as a moving average on a fixed number of last execution times. The size of the moving window on the past samples sequence is expected to be provided by the application. Precisely, if N denotes the size of the moving window, and 
are the N last observed samples at step k, then the expected value 
, returned by the get_exp_value() function, computes
![\[ p_k = \frac{1}{N} \cdot \sum_{i=0}^{N-1} x_{k-1-i} \]](form_2.png)
Actually, it is possible to specify more than 1 moving average to be used. This is possible by cascading the movavg predictor with the multipred predictor. See documentation for multipred_t for details.
- Forgetting Factor
If a forgetting factor lower than 1 is used, then the samples are averaged by using exponentially reducing weights, with higher weights for recent samples and lower weights for older ones. Precisely, denoting with 
the forgetting factor and with N the sample size, the formula for prediction 
at step k is
![\[ p = \frac{1-\alpha}{1-\alpha^N} \cdot \sum_{i=0}^{N-1} \alpha^j x_{k-1-i} \]](form_5.png)
In the same example as above, with a factor of 0.5, the expected value for sample k is computed approximatively as (0.5714*x(k-2)+0.2857*x(k-4)+0.1429*x(k-6))/3. The used weights always sum to 1.
- Note:
- When using a forgetting factor of 1.0, the module uses functions optimized for a simple moving average, so to avoid the unuseful additional overhead.
Definition in file movavg_lib.h.
Function Documentation
| qos_rv movavg_register_lib | ( | void | ) |
Registration of the submodule with the library.
