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of Service Requirements. Create Code 39 Full ASCII In . Users may or may not have quality of service requirements with espect to throughput. They do for real-time information retrieval sessions, where it is important for documents to appear rapidly on the user's screen. They do not for e-mail or le transfers where deferred delivery, within a loose time limit, is perfectly acceptable. The essential characteristics of elastic traf c are the arrival process of transfer requests and the distribution of object sizes. Observations on Web traf c provide useful pointers to the nature of these characteristics [2, 5]. The average arrival intensity of transfer requests varies depending on underlying user activity patterns. As for stream traf c, it should be possible to identify representative busy periods, where the arrival process can be considered to be stationary. Measurements on Web sites reported by Arlitt and Williamson [2] suggest the possibility of modeling the arrivals as a Poisson process. A Poisson process indeed results naturally when members of a very large population of users independently make relatively widely spaced demands. Note, however, that more recent and thorough measurements suggest that the Poisson assumption may be too optimistic (see 15). Statistics on the size of Web documents reveal that they are extremely variable, exhibiting a heavy-tailed probability distribution. Most objects are very small: measurements on Web document sizes reported by Arlitt and Williamson reveal that some 70% are less than 1 kbyte and only around 5% exceed 10 kbytes. The presence of a few extremely long documents has a signi cant impact on the overall traf c volume, however. Barcode Creator In .NET Using Barcode encoder for .NET .Related: 

There are three aphorisms concerning optimization that everyone should know They are perhaps beginning to suffer from overexposure, but in case you aren't yet familiar with them, here they are: More computing sins are committed in the name of efficiency (without necessarily achieving it) than for any other single reason including blind stupidity William A Wulf [Wulf72] We should forget about small efficiencies, say about 97% of the time: premature optimization is the root of all evil Donald E Knuth [Knuth74] We follow two rules in the matter of optimization: Rule 1 Don't do it Rule 2 (for experts only) Don't do it yet that is, not until you have a perfectly clear and unoptimized solution M A Jackson [Jackson75] All of these aphorisms predate the Java programming language by two decades They tell a deep truth about optimization: It is easy to do more harm than good, especially if you optimize prematurely In the process, you may produce software that is neither fast nor correct and cannot easily be fixed Don't sacrifice sound architectural principles for performance Strive to write good programs rather than fast ones If a good program is not fast enough, its architecture will allow it to be optimized Good programs embody the principle of information hiding: Where possible, they localize design decisions within individual modules, so individual decisions can be changed without affecting the remainder of the system (Item 12) This does not mean that you can ignore performance concerns until your program is complete Implementation problems can be fixed by later optimization, but pervasive architectural flaws that limit performance can be nearly impossible to fix without rewriting the system Changing a fundamental facet of your design after the fact can result in an ill-structured system that is difficult to maintain and evolve Therefore you should think about performance during the design process Strive to avoid design decisions that limit performance The components of a design that are most difficult to change after the fact are those specifying interactions between modules and with the outside world Chief among these design components are APIs, wire-level protocols, and persistent data formats Not only are these design components difficult or impossible to change after the fact, but all of them can place significant limitations on the performance that a ystem can ever achieve.

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An alien method invoked outside of a synchronized region is known as an open call [Lea00, 2413] Besides preventing deadlocks, open calls can greatly increase concurrency An alien method might run for an arbitrarily long period, during which time other threads would unnecessarily be denied access to the shared object if the alien method were invoked inside the synchronized region As a rule, you should do as little work as possible inside synchronized regions Obtain the lock, examine the shared data, transform the data as necessary, and drop the lock If you must perform some time-consuming activity, find a way to move the activity out of the synchronized region Invoking an alien method from within a synchronized region can cause failures more severe than deadlocks if the alien method is invoked while the invariants protected by the synchronized region are temporarily invalid (This cannot happen in the broken work queue example because the queue is in a consistent state when processItem is invoked) Such failures do not involve the creation of a new thread from within the alien method; they occur when the alien method itself calls back in to the faulty class Because locks in the Java programming language are recursive, such calls won't deadlock as they would if they were made by another thread The calling thread already holds the lock, so the thread will succeed when it tries to acquire the lock a second time, even though there is another conceptually unrelated operation in progress on the data protected by the lock The consequences of such a failure can be catastrophic; in essence, the lock has failed to do its job Recursive locks simplify the construction of multithreaded object-oriented programs, but they can turn liveness failures into safety failures The first part of this item was about concurrency problems Now we turn our attention to performance While the cost of synchronization has plummeted since the early days of the Java platform, it will never vanish entirely If a frequently used operation is synchronized unnecessarily, it can have significant impact on performance For example, consider the classes StringBuffer and BufferedInputStream These classes are thread-safe (Item 52) but are almost always used by a single thread, so the locking they do is usually unnecessary They support fine-grained methods, operating at the individual character or byte level, so not only do these classes tend to do unnecessary locking, but they tend to do a lot of it This can result in significant performance loss One paper reported a loss close to 20 percent in a realworld application [Heydon99] You are unlikely to see performance losses this ramatic caused by unnecessary synchronization, but 5 to 10 percent is within the realm of possibility Arguably this belongs to the small efficiencies that Knuth says we should forget about (Item 37) If, however, you are writing a low-level abstraction that will generally be used by a single thread or as a component in a larger synchronized object, you should consider refraining from synchronizing the class internally Whether or not you decide to synchronize a class, it is critical that you document its thread-safety properties (Item 52) It is not always clear whether a given class should perform internal synchronization In the nomenclature of Item 52, it is not always clear whether a class should be made thread-safe or thread-compatible Here are a few guidelines to help you make this choice If you're writing a class that will be used heavily in circumstances requiring synchronization and also in circumstances where synchronization is not required, a reasonable approach is to provide both synchronized (thread-safe) and unsynchronized (thread-compatible) variants.

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NET Control to generate, create Code 39 Full ASCII image n VS .NET applications. Equipment and intercity cabling run by others (such as Internet service providers or hone communications providers) can be represented with a cloud figure. The other drawings (discussed later) will flush out in greater detail the picture of the infrastructure and computing equipment at each specific location. Diagramming Hierarchical Infrastructure. Barcode Encoder In Java Using .Related: 

Suppose the computation in the body of the loop contains a bug that results in an out-ofbounds access to some unrelated array If a reasonable loop idiom were used, the bug would generate an uncaught exception, resulting in immediate thread termination with an appropriate error message If the evil exception-based looping idiom were used, the bug-related exception would be caught and misinterpreted as a normal loop termination The moral of this story is simple: Exceptions are, as their name implies, to be used only for exceptional conditions; they should never be used for ordinary control flow More generally, you should use standard, easily recognizable idioms in preference to overly clever ones that are purported to offer better performance Even if the performance advantage is eal, it may not remain in the face of steadily improving JVM implementations The subtle bugs and maintenance headaches that come from overly clever idioms, however, are sure to remain This principle also has implications for API design A well-designed API must not force its client to use exceptions for ordinary control flow A class with a state-dependent method that can be invoked only under certain unpredictable conditions should generally have a separate state-testing method indicating whether it is appropriate to invoke the first method For example, the Iterator class has the state-dependent next method, which returns the next element in the iteration, and the corresponding state-testing method hasNext This enables the standard idiom for iterating over a collection:. Make Code 9/3 In Java Using Barcode printer for .Related: 

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