line::lossn Namespace Reference

Classes
struct	ErlangFpResult
struct	LossnManjunathOptions
	Controls of lossn_manjunath. More...
struct	LossnManjunathResult
	Result of lossn_manjunath. More...
struct	LossnMciOptions
	Options of lossn_mci, MATLAB's options struct. More...
struct	LossnMciResult
	Result of lossn_mci. More...
struct	LossnRecResult
	Carried load, blocking, log normalising constant and walk count. More...

Functions
template<class T>
T	erlang_b (const T &nu, int C)
	Erlang's loss formula B(nu, C), evaluated through logs as MATLAB does so the factorials stay in range for large C.
template<class T>
T	erlang_b_real (const T &nu, const T &C)
	Erlang B for a REAL capacity, the reference's ErlangB(nu, C) evaluated as it stands: the sum runs over i = 0..floor(C) and factln(C) is lgamma(C+1).
da::FpiOptions	lossn_erlangfp_options ()
	The reference's fixed-point settings: iter_max 10000, iter_tol 1e-10, the max-norm of the increment (da_norm = @(d) max(abs(d(:))), the driver's default) and da_nanstop = true.
template<class T>
ErlangFpResult< T >	lossn_erlangfp (const std::vector< T > &nu, const Matrix< T > &A, const std::vector< T > &C, const da::FpiOptions &options=lossn_erlangfp_options())
	Erlang fixed-point (reduced-load) approximation for a loss network.
template<class T>
ErlangFpResult< T >	lossn_erlangfp (const std::vector< T > &nu, const Matrix< T > &A, const std::vector< int > &C, const da::FpiOptions &options=lossn_erlangfp_options())
	lossn_erlangfp with integer capacities.
template<class T>
LossnManjunathResult< T >	lossn_manjunath (const std::vector< T > &nu, const Matrix< T > &A, const std::vector< T > &C, const LossnManjunathOptions &options=LossnManjunathOptions())
	Exact normalizing constant, carried load and blocking of a loss network.
template<class T, class Rng>
LossnMciResult< T >	lossn_mci (const std::vector< T > &nu, const Matrix< T > &A, const std::vector< T > &C, const LossnMciOptions< T > &opt, Rng &gen)
	Estimate the normalizing constant and the blocking probabilities.
template<class T>
LossnMciResult< T >	lossn_mci (const std::vector< T > &nu, const Matrix< T > &A, const std::vector< T > &C, const LossnMciOptions< T > &opt, std::uint64_t seed)
	Overload seeding a local engine.
template<class T>
LossnRecResult< T >	lossn_rec (const std::vector< T > &nu, const Matrix< T > &A, const std::vector< T > &C)
	Exact loss-network analysis by MDD-rec.

Function Documentation

erlang_b()

template<class T>

T line::lossn::erlang_b	(	const T &	nu,
		int	C )

Erlang's loss formula B(nu, C), evaluated through logs as MATLAB does so the factorials stay in range for large C.

Definition at line 63 of file lossn_erlangfp.h.

References erlang_b(), line::InputError::InputError(), and line::num_factorial().

Referenced by erlang_b().

erlang_b_real()

template<class T>

T line::lossn::erlang_b_real	(	const T &	nu,
		const T &	C )

Erlang B for a REAL capacity, the reference's ErlangB(nu, C) evaluated as it stands: the sum runs over i = 0..floor(C) and factln(C) is lgamma(C+1).

Definition at line 84 of file lossn_erlangfp.h.

References erlang_b_real(), and line::num_factorial().

Referenced by erlang_b_real().

lossn_erlangfp() [1/2]

template<class T>

ErlangFpResult< T > line::lossn::lossn_erlangfp	(	const std::vector< T > &	nu,
		const Matrix< T > &	A,
		const std::vector< int > &	C,
		const da::FpiOptions &	options = lossn_erlangfp_options() )

lossn_erlangfp with integer capacities.

Definition at line 257 of file lossn_erlangfp.h.

References lossn_erlangfp(), and lossn_erlangfp_options().

lossn_erlangfp() [2/2]

template<class T>

ErlangFpResult< T > line::lossn::lossn_erlangfp	(	const std::vector< T > &	nu,
		const Matrix< T > &	A,
		const std::vector< T > &	C,
		const da::FpiOptions &	options = lossn_erlangfp_options() )

Erlang fixed-point (reduced-load) approximation for a loss network.

Parameters

nu	offered load per class (R)
A	(J x R) capacity requirement of link j for class r; fractional entries are scaled to integers row by row (see the file comment)
C	(J) link capacities
options	fixed-point options; the default is the reference's (max-norm, iter_tol 1e-10, nanstop), see lossn_erlangfp_options()

Returns the carried traffic QLen_r = nu_r prod_j (1 - B(j,r)), the loss 1 - prod_j (1 - B(j,r)) and the (J x R) blocking matrix E = B.

Definition at line 191 of file lossn_erlangfp.h.

References line::Matrix< T >::cols(), line::da::FpiResult< T >::converged, line::lossn::ErlangFpResult< T >::converged, line::da::da_fpi(), line::lossn::ErlangFpResult< T >::E, line::InputError::InputError(), line::da::FpiResult< T >::iterations, line::lossn::ErlangFpResult< T >::iterations, line::lossn::ErlangFpResult< T >::Loss, lossn_erlangfp(), lossn_erlangfp_options(), line::Matrix< T >::Matrix(), line::lossn::ErlangFpResult< T >::QLen, line::Matrix< T >::rows(), and line::da::FpiResult< T >::x.

Referenced by lossn_erlangfp(), lossn_erlangfp(), and line::nc::solver_nc_lossn_analyzer().

lossn_erlangfp_options()

da::FpiOptions line::lossn::lossn_erlangfp_options ( )

inline

The reference's fixed-point settings: iter_max 10000, iter_tol 1e-10, the max-norm of the increment (da_norm = @(d) max(abs(d(:))), the driver's default) and da_nanstop = true.

Definition at line 104 of file lossn_erlangfp.h.

References line::da::FpiOptions::iter_max, line::da::FpiOptions::iter_tol, lossn_erlangfp_options(), and line::da::FpiOptions::nanstop.

Referenced by lossn_erlangfp(), lossn_erlangfp(), lossn_erlangfp_options(), and line::nc::solver_nc_lossn_analyzer().

lossn_manjunath()

template<class T>

LossnManjunathResult< T > line::lossn::lossn_manjunath	(	const std::vector< T > &	nu,
		const Matrix< T > &	A,
		const std::vector< T > &	C,
		const LossnManjunathOptions &	options = LossnManjunathOptions() )

Exact normalizing constant, carried load and blocking of a loss network.

Parameters

nu	offered load of route r, nonnegative (R)
A	(J x R) nonnegative integer circuit requirements
C	(J) nonnegative integer capacities
options	the live-coefficient cap

Definition at line 365 of file lossn_manjunath.h.

References line::Matrix< T >::cols(), line::InputError::InputError(), line::lossn::LossnManjunathResult< T >::lG, line::lossn::LossnManjunathResult< T >::Loss, lossn_manjunath(), line::NumericError::NumericError(), line::lossn::LossnManjunathResult< T >::peak_states, line::lossn::LossnManjunathResult< T >::QLen, and line::Matrix< T >::rows().

Referenced by lossn_manjunath(), and line::nc::solver_nc_lossn_analyzer().

lossn_mci() [1/2]

template<class T, class Rng>

LossnMciResult< T > line::lossn::lossn_mci	(	const std::vector< T > &	nu,
		const Matrix< T > &	A,
		const std::vector< T > &	C,
		const LossnMciOptions< T > &	opt,
		Rng &	gen )

Estimate the normalizing constant and the blocking probabilities.

Parameters

nu	(R) offered load per route
A	(J x R) circuit requirement of link j for route r
C	(J) link capacity
opt	options
gen	the caller's random engine, advanced in place

Definition at line 162 of file lossn_mci.h.

References line::lossn::LossnMciResult< T >::acceptCI, line::lossn::LossnMciResult< T >::acceptPoint, line::Matrix< T >::cols(), line::InputError::InputError(), line::lossn::LossnMciResult< T >::level, line::lossn::LossnMciResult< T >::lG, line::lossn::LossnMciResult< T >::Loss, line::lossn::LossnMciResult< T >::lossCI, lossn_mci(), line::lossn::LossnMciResult< T >::lossPoint, line::Matrix< T >::Matrix(), line::lossn::LossnMciResult< T >::nsamples, line::NumericError::NumericError(), line::lossn::LossnMciResult< T >::QLen, and line::Matrix< T >::rows().

Referenced by lossn_mci(), lossn_mci(), and line::nc::solver_nc_lossn_analyzer().

lossn_mci() [2/2]

template<class T>

LossnMciResult< T > line::lossn::lossn_mci	(	const std::vector< T > &	nu,
		const Matrix< T > &	A,
		const std::vector< T > &	C,
		const LossnMciOptions< T > &	opt,
		std::uint64_t	seed )

Overload seeding a local engine.

Deterministic in the seed and independent of any global state; the engine is created and destroyed here.

Definition at line 369 of file lossn_mci.h.

References lossn_mci().

lossn_rec()

template<class T>

LossnRecResult< T > line::lossn::lossn_rec	(	const std::vector< T > &	nu,
		const Matrix< T > &	A,
		const std::vector< T > &	C )

Exact loss-network analysis by MDD-rec.

Parameters

nu	offered load per class, length K
A	J x K non-negative resource requirement matrix
C	capacity vector, length J

Returns

the carried load, the blocking probabilities and the normalising constant

Definition at line 141 of file lossn_rec.h.

References line::Matrix< T >::cols(), line::lossn::LossnRecResult< T >::G, line::InputError::InputError(), line::lossn::LossnRecResult< T >::iterations, line::lossn::LossnRecResult< T >::lG, line::lossn::LossnRecResult< T >::Loss, lossn_rec(), line::mdd::mdd_rec_marginal(), line::lossn::LossnRecResult< T >::QLen, and line::Matrix< T >::rows().

Referenced by lossn_rec(), and line::nc::solver_nc_lossn_analyzer().