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There is no single optimal strategy However, several techniques and patterns can be used to provide better balance among such forces This section describes strategies for removing unnecessary synchronization, splitting synchronization to match functionality, exporting read nly operations via adapters, isolating state representations to reduce access costs or improve potential parallelism, and grouping objects to use common locks so as to mirror layered designs While any of these could be used during the initial design of classes, several of them rely on technical manipulations that are difficult (and sometimes unwise) to exploit during early design efforts. 39 In Java Using Barcode maker for Java .When locking presents liveness or performance problems for a given class or program, usually the best solution is to refactor the design to use one or more of the other approaches presented in this chapter However, there are cases where the basic logic of a synchronization-based design can be maintained even when some of the synchronized method qualifiers or blocks are removed, although sometimes at the expense of weakened semantic guarantees 2411 Accessors Synchronizing a field accessor method ometimes (but by no means always) adds noticeable overhead to programs Two considerations enter into any decision about whether synchronization of an accessor method can be removed: Legality The value of the underlying field never assumes an illegal value; that is, you can ensure that the field never, even momentarily, breaks invariants (This by definition excludes fields of type long and double) Staleness Clients do not necessarily require the most recently updated value of a field, but can live with possibly stale values (see 227) If a field is not always legal, then the choices are:.Related: Interleaved 2 of 5 Creating Excel , Create Code 128 ASP.NET , Creating ITF-14 Excel

detection and tracking Barcode 128 barcode library for We now discuss the approaches to writing ATaG macroprograms for the object detection and tracking functionality t the high level, the program should determine the presence of objects of interest in the sensor field at all times We simplify the use case by assuming that identity maintenance and tracking is not a concern in this example In other words, if one or more objects of interest are in the sensor field, the application should only generate periodic reports that indicate the presence and the approximate location of each object The program is not required to be intelligent enough to detect if an object at some location X' at time T' is the same object as was detected at location X at an earlier time T As mentioned briefly in Section 2.

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5, a simple algorithm for object tracking [55] requires each node to periodically sample its sensing interface and compare it against a predefined threshold A reading that exceeds the threshold is indicative of the presence of a target in the sensing range The nodes that detect the target elect a leader node, which is the node with the maximum reading among all nodes involved in the election The leader node then performs some processing of the set of sensor readings and transmits the resultant estimate of target location to a base station As in the previous example of temperature gradient monitoring, there are various approaches toward formulating this functionality in terms of an ATaG program While the sampling task and the supervisor task are quite straightforward in terms of their logic, the implementation of the distributed leader election can be realized in multiple ways Figure 5.

4 is an exampleATaG program for this behavior The SampleAndThreshold task is executed periodically on each node As indicated by the task name, it samples the acoustic sensor in each invocation and produces a TargetAlert notification when the reading is above some threshold that is indicative of the presence of an object of interest within the sensing range of the node All nodes that have a given target in range at any given time produce these notifications To perform leader election, it is important for each node that has detected the target to receive notifications from every other node that has also detected the target The TargetAlert notification contains some measure of the distance of the target from the node as indicated by the sensor reading, or some other mechanism that can be used to determine the criteria for the leader election.

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Figure 22-4: Clients requesting objects through a Web cache Note that a cache is both a server and a client at the same time When it receives requests from and sends responses to a browser, it is a server When it sends requests to and receives responses from an origin server it is a client So why bother with a Web cache What advantages does it have Web caches are enjoying wide-scale deployment in the Internet for at least three reasons First, a Web cache can substantially reduce the response time for a client request, particularly if the bottleneck bandwidth between the client and the origin server is much less than the bottleneck bandwidth between the client and the cache If there is a high-speed connection between the client and the cache, as there often is, and if the cache has the requested object, then the cache will be able to rapidly deliver the object to the client Second, as we will soon illustrate with an example, Web caches can substantially reduce traffic on an institution's access link to the Internet By reducing traffic, the institution (eg, a company or a university) does not have to upgrade bandwidth as quickly, thereby reducing costs Furthermore, Web caches can substantially reduce Web traffic in the Internet as a whole, thereby improving performance for all pplications In 1998, over 75% of Internet traffic was Web traffic, so a significant reduction in Web traffic can translate into a significant improvement in Internet performance [Claffy 1998] Third, an Internet dense with Web caches -- eg, at institutional, regional and national levels -- provides an infrastructure for rapid distribution of content, even for content providers who run their sites on low-speed servers behind low-speed access links If such a "resouce-poor" content provider suddenly has popular content to distribute, this popular content will quickly be copied into the Internet caches, and high user demand will be satisfied To gain a deeper understanding of the benefits of caches, let us consider an example in the context of Figure 22-5 In this figure, there are two networks - the institutional network and the Internet The institutional network is a high-speed LAN A router in the institutional network and a router in the Internet are connected by a 15 Mbps link The institutional network consists of a high-speed LAN which is connected to the Internet through a 15 Mbps access link The origin servers are attached to the Internet, but located all over the globe Suppose that the average object size is 100 Kbits and that the average request rate from the institution's browsers to the origin servers is 15 requests per second Also suppose that amount of time it takes from when the router on the Internet side of the access link in Figure 22-5 forwards an HTTP request (within an IP datagram) until it receives the IP datagram (typically, many IP datagrams) containing the corresponding response is two seconds on average Informally, we refer to this last delay as the "Internet delay" The total response time -- that is the time from when a browser requests an object until the browser receives the object -- is the sum of the LAN delay, the access delay (ie, the delay between the two routers) and the Internet delay Let us now do a very crude calculation to estimate this delay The traffic intensity on the LAN (see Section 16) is (15 requests/sec)*(100 Kbits/request)/(10Mbps) = 15 whereas the traffic intensity on access link (from Internet router to institution router) is (15 requests/sec)*(100 Kbits/request)/(15 Mbps) = 1.

Suppose that each node sends its sensor reading as partRelated: UPC-A Printing ASPNET , UPC-E Generator NET WinForms , UPC-E Generator NET.

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The difference in performance is dramatic If numItems returns 100 and lineForItem returns a constant 80-character string, the second method is ninety times faster on my machine than the first Because the first method is quadratic in the number of items and the second is linear, the performance difference is even more dramatic for larger numbers of items Note that the second method preallocates a StringBuffer large enough to hold the result Even if it is detuned to use a default-sized StringBuffer, it is still forty-five times faster than the first The moral is simple: Don't use the string concatenation operator to combine more than a few strings unless performance is irrelevant se StringBuffer's append method instead Alternatively, use a character array, or process the strings one at a time instead of combining them. Vector subscribers = new Vector(); Encode European Article Number 13 In Java Using Barcode creator for .Related: Creating Data Matrix .NET WinForms , Code 128 Generation VB.NET , .NET WinForms Intelligent Mail Generation

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