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This command tells the server that there is a command buffer waiting for it. WSERV places many individual commands into this command buffer, saying which server object to send the command to, which command or function to execute on that object and any parameters for that command. Each of these commands potentially needs to be policed for the capabilities of the client. Thus we have to do the policing in the server code that executes the commands. On the server side, each command buffer is unpacked in the function CWsClient::CommandBufL(), which passes the commands onto this functions:

system of 700 linear equations! In contrast, Theorem 10.3.2 readily suggests an ~ asymptotic approximation lB 0:0767=B2 . The approximation is presented on the loss same gure with `` '' symbols. A precise match is apparent from the gure. In fact, ~ relative error jlB lB j=lB for all computed buffers was less than 4%. loss loss loss

In this section we investigate the queueing behavior when the distribution of the arrival sequence has a bounded (truncated) support [32, 34]. This arises quite frequently in practice when the arrival process distribution has a bounded support and inside that support is nicely matched with a heavy-tailed distribution (e.g., Pareto). Our primary interest in this scenario is in its possible application to network control. More precisely, one can imagine network control procedure in which short network ows are separated from long ones. If the distribution of ows is longtailed, this procedure will yield a truncated long-tailed distribution for the short network ows. Assume that long ows are transmitted separately using virtual circuits and short ows are multiplexed together. Intuitively, it can be expected that with short (truncated) ows one can obtain better multiplexing gains than with the original ones (before the separation). These gains are quanti ed in Theorem 10.3.6, which explicitly asymptotically characterizes a unique asymptotic behavior of the queue length distribution. Informally, this distribution on the log scale resembles a stair-wave function that has steep drops at speci c buffer sizes (see Fig. 10.2). This has important design implications suggesting that negligible increases of the buffer

virtual void CWsObject::CommandL(TInt aOpcode,const TAny *aCmdData)=0;

4331 Callables Most designs based on Futures take exactly the form illustrated in class AsynchRenderer The construction and use of such classes can be further standardized and automated by stepping up to a blander interface

Log10(Pr[Q>x])

or at least the version of this function in the respective derived class. This means that we must do the policing in the respective CommandL() function.

size in certain buffer regions can decrease the over ow probabilities by orders of magnitude. Formally, for each B > 0 construct a sequence of truncated random variables AB min An1 B : n Next, consider a single server queue with the arrival process fAB ; AB ; n ! 0g, that is, n QB QB AB Cn 1 : n 1 n n 1 Assume that for all B, QB is in its stationary regime. n Theorem 10.3.6. If E A C < 0, for all n > 0, P C > x e Zx ; Z > 0, and A has a regularly varying distribution P A > x l x =xa , then P QB > k d B hk d l B k 1 1 o 1 B k 1 a 1 as B 3 I; 10:6 10:5

In the same way that interface Runnable describes any pure action, a Callable interface can be used to describe any service method that accepts an Object argument, returns an Object result, and may throw an Exception:

10:7

WSERV checks for three different capabilities SwEvent, WriteDeviceData and PowerMgmt. The details of which APIs police which capabilities are given in any Symbian OS SDK, so there is no need for me to reiterate here. Instead I will describe the type of API that is policed with each of these capabilities, and the motivation for this policing.

HEURISTIC 10.3.7. In order that the queue exceeds a large buffer size b k d B it is needed that exactly k 1 large arrivals (of the order B) occur at approximately the same time. Since successive arrivals are independent this event is of the order l B k 1 =B k 1 a 1 . The detailed proof of this result can be found in Jelenkovic [32]. REMARK 10.3.8. (i) This result is related to Proposition 1 in Resnick and Samorodnitsky [50], where, under conditions similar to our theorem, a rough bound for the queue length increment during an activity period of the M =GI =I arrival process was derived. (ii) Note that h0 d is explicitly given by h0 d 1 1 da 1 : a 1 da 1 10:8