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The above procedure de nes a source code. To analyze the probability of error for this code, we will now divide the X n sequences into two types, typical sequences and nontypical sequences. If the source sequence is typical, the bin corresponding to this source sequence will contain at least one typical sequence (the source sequence itself). Hence there will be an error only if there is more than one typical sequence in this bin. If the source sequence is nontypical, there will always be an error. But if the number of bins is much larger than the number of typical sequences, the probability that there is more than one typical sequence in a bin is very small, and hence the probability that a typical sequence will result in an error is very small. Formally, let f (X n ) be the bin index corresponding to X n . Call the decoding function g. The probability of error (averaged over the random choice ofcodes f ) is P (g(f (X)) = X) P (X A(n) ) + /

avec ( B X e lSi A) ( , a \' =U$ISiI\qrISiIp)C ISiB vec(A)]. vec(, )'

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Now, zoom in to layer 4, the transport layer. While unicast transports such as TCP [16] and UDP [17] are indispensable building blocks, the foundation of scalable content distribution is ef cient one-to-many data transport, namely, multicast. Broadly speaking, the term multicast simply refers to moving a piece of data to multiple endpoints. For example, a satellite beaming live Superbowl video feed to millions of Direct TV settop boxes is a form of multicast. The CBS.com Web server delivering video clips of the Survivor show to millions of Web surfers via repeated TCP is also a form of multicast, although repeated unicast is not nearly as ef cient as a satellite beam. IP unicast delivers data to one receiver a time, while IP multicast delivers data to multiple receivers simultaneously. For example, repeated unicast of one megabit of data to 1000 sites would use one gigabit network bandwidth, while a single IP multicast stream can reach all 1000 sites simultaneously, using only one megabit bandwidth. This chapter focuses on ef cient one-to-many content transport and, speci cally, three avors of it: IP multicast, application layer multicast, and on-demand proxy caching. Section 4.3 talks about IP multicast and how to provide it reliably, such as, for real-time live streaming. Section 4.4 introduces application layer multicast, typically to preposition of bulk data, compares it with IP multicast, and describes the various algorithms in building application layer multicast. Section 4.5 describes Web proxy caching, which provides the same one-to-many content delivery, but in an end-user-driven and on-demand fashion. A combination of both proactive multicast and on-demand caching enables the most scalable blend of one-to-many content delivery on the Web.

appropriate colors, red, green, and blue, and suggested there were three such color receptors in the eye Helmholtz elaborated and quanti ed Young s idea into the Young-Helmholtz trichromatic theory Helmholtz, incidentally, studied with M ller and Du Bois-Reymond He received his MD in 1842 and published two extraordinary works, the three-volume Treatis on Physiological Optics (1856 1866/1924) and On the Sensations of Tone (1863/1954) He was one of the leading scientists in the nineteenth century and had a profound impact on early developments in psychology, particularly biological psychology The basic idea in the trichomatic theory is that the three receptors accounted for sensations of red, green, and blue Yellow was said to derive from stimulation of both red and green receptors, and white was derived from yellow and the blue receptor But there were problems The most common form of color blindness is red-green.

But if yellow is derived from red and green, how is it that a person with red-green color blindness can see yellow In the twentieth century, it was found that there are four types of receptors in the human retina: red, green, blue (cones), and light-dark (rods) But what about yellow Hering (1878) developed an alternative view termed the opponent-process theory He actually studied with Weber and with Fechner and received his MD just two years after Wundt in Heidelberg Interestingly, Hering disagreed with Fechner about the psychophysical law, arguing that the relationship should be a power function, thus anticipating Stevens Hering proposed that red-green and blue-yellow acted as opposites, along with white-black In modern times, Dorothea Jameson and Leo Hurvich (1955) provided an elegant mathematical formulation of Herring s theory that accounted very well for the phenomena of color vision.

the services that she needs The goal of recommendation-based service discovery is to make it easier to nd and activate the services that are relevant in the current situation Ideally, the user interface should display only a brief list of relevant services from which she can pick up the ones that she needs However, the relevance of a given service depends on both the particular user and the current situation Thus, to be able to recommend relevant services, a user model that captures the interests of each user is needed To construct the user models, an assumption is made that the recent behaviour of a user in a similar context re ects the user s current needs Therefore, in recommendation-based service discovery, the generic framework of context-dependent user modelling, as described in Section 433, is used.

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