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The rst indication that the Weibull distribution might be a good model is obtained by plotting the standardized skewness versus the coef cient of variation for both models and datasets and observing that the points of the datasets are clustered around the Weibull distribution. Figure 15.5(a) demonstrates this for eight complete datasets, Fig. 15.5(b) for eight hour periods of the external AT&T dataset from 18 November to 8 December 1995, and Fig. 15.5(c) for one hour periods of all Web requests of the external AT&T dataset from 18 November to 8 December 1995. The arrival processes are by no means stationary. Indeed, Fig. 15.6(a) shows how the number of Web connections changes over time for the CMU trace from 29 June. Each point represents the number of Web connections that arrived within a 15 minute interval. For the longer external AT&T trace from 18 November, Fig. 15.6(b) shows how many Web connections arrived within each four hour time period. These graphs show clear time of day and day of week dependencies. Nevertheless, we will show in this section that the Weibull distribution provides a good t for the connection interarrival times of TCP connections over all different measurement periods. We start by rst examining the distribution of all connection

Rather than servicing access requests in the order they are made, it is faster on average to sweep the head across the cylinders, accessing cylinders in ascending order and then resetting the head position back to the beginning after each sweep (Depending in part on the type of disk, it may be even better to arrange requests in both ascending and descending sweeps, but we will stick to this version) This policy would be tricky to implement without some kind of auxiliary data structure The enabling condition for a request to execute is:

Fig. 15.6 (a) Time of day effects for Web traf c in June 1995 CMU dataset. (b) Time of day and day of week effects for Web traf c in external AT&T dataset.

well-de ned driver-speci c API. We use the term channel to refer to a single connection between a user-side client and the kernel-side driver. Since hardware interfaces vary across platforms, an LDD is usually designed to perform generic functionality, using a PDD to implement the device-speci c code. LDDs are dynamically loaded from user-side code but may perform some initialization at boot time if they are con gured to do so. I ll explain how this is achieved when I discuss the use of extensions. Symbian provides standard LDDs for a range of peripheral types (such as media drivers, the USB controller and serial communications devices). However, phone manufacturers will often develop their own interfaces for custom hardware.

requests, then distinguishing between the application types, next considering application-speci c arrivals over time periods of various length, and nally we present time-dependent models for only a subset of the sources. While one might argue that we are planning to present the most useful models last (after all, arrivals are dependent on the time of day), we choose this order to familiarize the reader with the data and some graphical tools. 15.5.3 All Interarrival Times

Wait until the current request cylinder number is the least greater cylinder number relative to that of the current disk head of all of those currently waiting, or is the least numbered cylinder if the head cylinder number is greater than that of all requests This condition is too awkward, inefficient, and possibly even deadlock-prone to try to coordinate across a set of otherwise independent clients But it can be implemented fairly easily with the help of an ordered queue employed by a single worker thread Tasks can be added to the queue in cylinderbased order, then executed when their turns arrive This "elevator algorithm" is easiest to arrange by using a two-part queue, one for the current sweep and one for the next sweep The resulting framework combines Future-like constructs with the worker thread designs from 414 To set this up, we can define a Runnable class to include the extra bookkeeping associated with DiskTasks The queue class uses the semaphore-based approach discussed in 341, but here applied to ordered linked lists The server class constructs a worker thread that runs tasks from the queue The public service methods create tasks, place them on the queue, and then wait them out before returning to clients