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[9] B.K. Natarajan and B. Vasudev, A Fast Approximate Algorithm for Scaling Down Digital Images in the DCT Domain, Proc. of IEEE Int. Conf. Image Processing, vol. 2, Oct. 1995, pp. 241 243. [10] H. Sun, W. Kwok, and J.W. Zdepski, Architecture for MPEG Compressed Bitstream Scaling, IEEE Tran. of Circuits and Systems for Video Technology, vol. 6, no. 2, April 1996, pp. 191 199. [11] R. Rejaie, M. Handley, and D. Estrin, RAP: An End-to-End Rate-based Congestion Control Mechanism for Realtime Streams in the Internet, Proc. of IEEE INFOCOM, vol. 3, April 1999, pp. 1337 1345. [12] The network simulator ns-2. [Online]. Available: http://www.isi.edu/nsnam/ns/ [13] S. Floyd and V. Paxson, Dif culties in Simulating the Internet, IEEE/ACM Tran. of Networking, vol. 9, no. 4, August 2001, pp. 392 403. [14] S. Floyd and T. Henderson, The NewReno Modi cation to TCP s Fast Recovery Algorithm, RFC 2582, April 1999. [15] NLANR Measurement and Network Analysis Group. [Online]. Available: http://pma.nlanr.net/Traces/long/ bell1.html [16] BellLabs Internet Traf c Research. [Online]. Available: http://cm.bell-labs.com/cm/ms/departments/sia/ InternetTraf c/

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Clearly, many of the aforementioned failures will render a media server inoperable. To enable the system to survive a server failure, we will need to introduce hardware/capacity redundancy and fault-tolerant mechanisms into the system. The parallel server architectures in Part II of this book provide one approach to addressing the reliability as well as the scalability challenges.

class SmashingHello extends WP_Widget {

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Figure 1-9a shows a missile pursuing a target [19 22] The problem is scaled so that TMAX = 1, and distances are in 1000-foot units x and y are rectangular Cartesian coordinates of the missile center of gravity u and v are velocity components along and perpendicular to the torpedo longitudinal axis phi is the flight path angle, and rudder is the control-surface deflection The target proceeds on a straight course at constant velocity Our particular missile will be a guided torpedo In water, drag and side forces are approximately proportional to the square u2 of u The accelerations along and perpendicular to the torpedo s longitudinal axis are then approximated by

Case #1

2. Next you get the widget function:

(d/dt) u = (thrust drag)/mass = UT a2 * u2 (d/dt) v = b1 * u2 sin 2 + b2 * u * phidot + b3 * v * rudder

Case #2

function SmashingHello() { parent::WP_Widget(false, $name = 'Smashing Hello'); }

Case #3

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where c1 and c2 are hydrodynamic- and damping-moment coefficients, and c3 is the rudder steering-moment coefficient, all divided by the torpedo moment of inertia Weathercock stability ensures that the angle of attack g2 between longitudinal axis and velocity vector is so small that

In devising solutions to address the previous challenges, we often are faced with con icting design goals. Thus, for a given problem, there are often many possible solutions, each representing different engineering tradeoffs. In this section we attempt to illustrate this process of engineering tradeoffs by considering ve dimensions (Figure 1.14):

the next step, starting with widget():

(d/dt) u = UT a2 * u2 (d/dt) v = u * (b1 * v + b2 * phidot + b3 * rudder) (d/dt) phidot = u * (c1 * v + c2 * phidot + c3 * rudder) (d/dt) phi = phidot (d/dt) x = u * cos(phi) v * sin(phi) (d/dt) y = u * sin(phi) + v * cos(phi)

r Capacity such as disk I/O throughput and network bandwidth utilization; r Time such as start-up delay and response time; r Space such as storage requirement and buffer requirement; r Quality such as media quality and service quality; and r Complexity such as computational complexity and implementation complexity.

function widget($args, $instance) { extract( $args ); > < php echo $before_widget; > < php echo $before_title . $instance['title'] . $after_title; > Well hello there! Ain't that just Smashing < php echo $after_widget; > < php }

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These ve dimensions serve to illustrate the complexities and possibilities in engineering a media streaming system and thus are not meant to be exhaustive nor the most important. For illustrative purposes, we will consider the streaming of a media stream with time-varying playback bit-rates as shown in Figure 1.15. We assume that the media stream is divided into constant-duration segments of T seconds, i.e., the playback duration for each segment is the same. The size of each segment, however, is variable. Let ri be the rate at which segment i (0, 1, . . . ) is consumed in playback. Our goal is to deliver this media stream from a media server to a media client over the network.

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