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The client provides the name of the LDD (again, giving the object name that uniquely identi es the LDD factory), the supported version number, the unit number, an optional PDD name and an optional extra information block. For example:

Expressed in the form of transforms, Eqs. (17.27) and (17.28) become ^ 1 gk s ^ ^ Pjk sjx % hjk sjx s for j T k and ^ Pjj sjx % ^ 1 gj sjx P f^lj s ^ hjl sjx Plj : s s l 17:30 P^ f^ s hjl sjx Plk lk s l 17:29

Numerical inversion can easily be applied with Eqs. (17.29) and (17.30). However, since the time-domain formulas (17.27) and (17.28) involve single convolution integrals, numerical computation of Eqs. (17.27) and (17.28) in the time domain is also a feasible alternative. Moreover, if the underlying distributions have special structure, then the integrals in Eqs. (17.27) and (17.28) can be calculated analytically. For example, analytical integration can easily be done when all holding-time distributions are hyperexponential. In Duf eld and Whitt [15, Section 3] we give a numerical example illustrating how the two approximations compare to the exact conditional mean for a single source with four levels. 17.6 THE VALUE OF INFORMATION

DoCreate(_L("Serial"), version, KUnit0, NULL, NULL); DoCreate(_L("Serial"), version, KUnit0, _L( 16550 ), NULL);

class Butler implements CSProcess { private final AltingChannelInput[] enters; private final AltingChannelInput[] exits; Butler(AltingChannelInput[] e, AltingChannelInput[] x) { enters = e; exits = x; } public void run() { int seats = enterslength; int nseated = 0; // set up arrays for select AltingChannelInput[] chans = new AltingChannelInput[2*seats]; for (int i = 0; i < seats; ++i) { chans[i] = exits[i]; chans[seats + i] = enters[i]; } Alternative either = new Alternative(chans); Alternative exit = new Alternative(exits); for (;;) { // if max number are seated, only allow exits Alternative alt = (nseated < seats-1) either : exit; int i = altfairSelect(); chans[i]read(); // if i is in first half of array, it is an exit message if (i < seats) --nseated; else ++nseated; } }

We can use the source model to investigate the value of information. We can consider how prediction is improved when we condition rst, on, only the level and, second, on both level and age. The reference case is the steady-state mean M

These examples demonstrate the two different mechanisms that the kernel device driver framework provides for opening channels to device drivers: 1. Automatic search for a suitable physical device (no PDD name is speci ed) 2. User-speci ed physical device (a PDD name is provided). I will discuss both of these methods in the following sections, in which I will show how channels are created using LDD and PDD factory objects.

bij pij ;

The Philosopher processes run forever in a loop, alternating between thinking and eating Before eating, philosophers must first enter their seats, then get both forks After eating, they do the opposite The eat and think methods are just no-ops here, but could be fleshed out to (for example) help animate a demonstration version by reporting status to JCSP channels and processes that interface into AWT

17:31

When you call RBusLogicalChannel::DoCreate(), it performs an executive call to create the kernel-side instance of a logical channel (DLogicalChannelBase) before initializing the client-side handle:

where pij is the steady-state probability, that is, pij m Gji pij P i i ; k pk m Gk 17:32

EXPORT_C TInt RBusLogicalChannel::DoCreate( const TDesC& aLogicalDevice, const TVersion& aVer, TInt aUnit, const TDesC* aPhysicalDevice, const TDesC8* anInfo, TInt aType) { TInt r = User::ValidateName(aLogicalDevice); if(KErrNone!=r) return r; TBuf8<KMaxKernelName> name8; name8.Copy(aLogicalDevice); TBuf8<KMaxKernelName> physicalDeviceName; TChannelCreateInfo8 info; info.iVersion=aVer; info.iUnit=aUnit;

with pi the steady-state vector of the Markov chain Pi pi pi Pi and m Gji the mean of Gji for Gj in Eq. (17.8), for all sources i. With the steady-state mean, there is no conditioning. Section 17.2 gives the formula for conditioning on both level and age. Now we give the formulas conditioning only on the level; that is, we condition on the level, assuming that we are in the steady state. We omit the i superscript. Then the age in level j has the stationary-excess cdf Gje t 1 m Gj t

class Philosopher implements CSProcess {

Gjc u du;

if(aPhysicalDevice) { physicalDeviceName.Copy(*aPhysicalDevice); info.iPhysicalDevice = &physicalDeviceName; } else info.iPhysicalDevice = NULL; info.iInfo=anInfo; return SetReturnedHandle(Exec::ChannelCreate(name8, info, aType),*this); }

t ! 0:

leftFork; rightFork; enter; exit;

The info parameter is of type TChannelCreateInfo, which encapsulates the user-supplied version, unit number and optional information block:

17:33

Let Pjk t be the probability of being in level k at time t conditional on being in ^ level j in the steady state at time 0. Let Pjk s be its Laplace transform. Let mj t be ^ the conditional steady-state mean given level j at time 0 and let mj s be its Laplace transform. Clearly, mj t

class TChannelCreateInfo { public: TVersion iVersion; TInt iUnit; const TDesC* iPhysicalDevice; const TDesC8* iInfo; };