Package jline.api.cache

Class Cache_is

java.lang.Object

jline.api.cache.Cache_is

public final class Cache_is
extends Object

Method Summary

Modifier and Type	Method	Description
static Ret.cacheIs	cache_is(Matrix gamma, Matrix m)
static Ret.cacheIs	cache_is(Matrix gamma, Matrix m, int samples)	Estimate the normalizing constant of the cache steady state distribution using Monte Carlo importance sampling.
static Ret.cacheIs	cache_is(Matrix gamma, Matrix m, int samples, Matrix sigma, Matrix k)	Estimate the (cost-capped) normalizing constant with the feasibility indicator I{S in O} of Casale-Gast, IEEE/ACM Trans.

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Method Details

cache_is

public static Ret.cacheIs cache_is(Matrix gamma,
 Matrix m,
 int samples)

Estimate the normalizing constant of the cache steady state distribution using Monte Carlo importance sampling.

cache_is

public static Ret.cacheIs cache_is(Matrix gamma,
 Matrix m,
 int samples,
 Matrix sigma,
 Matrix k)

Estimate the (cost-capped) normalizing constant with the feasibility indicator I{S in O} of Casale-Gast, IEEE/ACM Trans. Networking 29(2), 2021, Sec. IX-B.

Parameters:

gamma - Cache access factors (n x h).

m - Cache capacity vector (1 x h).

samples - Number of Monte Carlo samples.

sigma - Item storage costs (sizes); null or empty for none.

k - Per-list storage cost caps; null or empty for none.

Returns:

the estimate and its logarithm.

cache_is

public static Ret.cacheIs cache_is(Matrix gamma,
 Matrix m)