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<li class="toctree-l1"><a class="reference internal" href="../preface.html">Preface</a></li>

<li class="toctree-l1"><a class="reference internal" href="../foundation.html">Chapter 1: Foundation</a></li>

<li class="toctree-l1"><a class="reference internal" href="../direct.html">Chapter 2: Direct Links</a></li>

<li class="toctree-l1"><a class="reference internal" href="../internetworking.html">Chapter 3: Internetworking</a></li>

<li class="toctree-l1"><a class="reference internal" href="../scaling.html">Chapter 4: Advanced Internetworking</a></li>

<li class="toctree-l1"><a class="reference internal" href="../e2e.html">Chapter 5: End-to-End Protocols</a></li>

<li class="toctree-l1"><a class="reference internal" href="../congestion.html">Chapter 6: Congestion Control</a></li>

<li class="toctree-l1 current"><a class="reference internal" href="../data.html">Chapter 7: End-to-End Data</a><ul class="current">

<li class="toctree-l2 current"><a class="current reference internal" href="#">Problem: What Do We Do with the Data?</a></li>

<li class="toctree-l2"><a class="reference internal" href="presentation.html">7.1 Presentation Formatting</a></li>

<li class="toctree-l2"><a class="reference internal" href="multimedia.html">7.2 Multimedia Data</a></li>

<li class="toctree-l2"><a class="reference internal" href="trend.html">Perspective: Big Data and Analytics</a></li>

<li class="toctree-l1"><a class="reference internal" href="../security.html">Chapter 8: Network Security</a></li>

<li class="toctree-l1"><a class="reference internal" href="../applications.html">Chapter 9: Applications</a></li>

<li class="toctree-l1"><a class="reference internal" href="../supplements.html">Emerging Topics</a></li>

<li class="toctree-l1"><a class="reference internal" href="../README.html">About This Book</a></li>

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<h1>Problem: What Do We Do with the Data?<a class="headerlink" href="#problem-what-do-we-do-with-the-data" title="Permalink to this headline">¶</a></h1>

<p>From the network’s perspective, application programs send messages to

each other. Each of these messages is just an uninterpreted string of

bytes. From the application’s perspective, however, these messages

contain various kinds of <em>data</em>—arrays of integers, video frames, lines

of text, digital images, and so on. In other words, these bytes have

meaning. We now consider the problem of how best to encode the different

kinds of data that application programs want to exchange into byte

strings. In many respects, this is similar to the problem of encoding

byte strings into electromagnetic signals that we saw in an earlier

chapter.</p>

<p>Thinking back to our discussion of encoding, there are essentially two

concerns. The first is that the receiver be able to extract the same

message from the signal as the transmitter sent; this is the framing

problem. The second is making the encoding as efficient as possible.

Both of these concerns are also present when encoding application data

into network messages.</p>

<p>In order for the receiver to extract the message sent by the

transmitter, the two sides need to agree to a message format, often

called the <em>presentation format</em>. If the sender wants to send the

receiver an array of integers, for example, then the two sides have to

agree what each integer looks like (how many bits long it is, what order

the bytes are arranged in, and whether the most significant bit comes

first or last, for example) and how many elements are in the array. The

first section describes various encodings of traditional computer data,

such as integers, floating-point numbers, character strings, arrays, and

structures. Well-established formats also exist for multimedia data:

Video, for example, is typically transmitted in one of the formats

created by the Moving Picture Experts Group (MPEG), and still images are

usually transmitted in Joint Photographic Experts Group (JPEG) format.

The particular issues that arise in the encoding of multimedia data are

discussed in the next section.</p>

<p>Multimedia data types require us to think about both presentation and

<em>compression</em>. The well-known formats for the transmission and storage

of audio and video deal with both these issues: making sure that what

was recorded, photographed, or heard at the sender can be interpreted

correctly by the receiver, and doing so in a way that does not overwhelm

the network with massive amounts of multimedia data.</p>

<p>Compression and, more generally, the efficiency of encoding have a rich

history, dating back to Shannon’s pioneering work on information theory

in the 1940s. In effect, there are two opposing forces at work here. In

one direction, you would like as much redundancy in the data as possible

so that the receiver is able to extract the right data even if errors

are introduced into the message. The error detection and correcting

codes we saw in an earlier chapter add redundant information to messages

for exactly this purpose. In the other direction, we would like to

remove as much redundancy from the data as possible so that we may

encode it in as few bits as possible. It turns out the multimedia data

offers a wealth of opportunities for compression because of the way our

senses and brains process visual and auditory signals. We don’t hear

high frequencies as well as lower ones, and we don’t notice fine detail

as much as the bigger picture in an image, especially if the image is

moving.</p>

<p>Compression is important to the designers of networks for many reasons,

not just because we rarely find ourselves with an abundance of bandwidth

everywhere in the network. For example, the way we design a compression

algorithm affects our sensitivity to lost or delayed data and thus may

influence the design of resource allocation mechanisms and end-to-end

protocols. Conversely, if the underlying network is unable to guarantee

a fixed amount of bandwidth for the duration of a videoconference, we

may choose to design compression algorithms that can adapt to changing

network conditions.</p>

<p>Finally, an important aspect of both presentation formatting and data

compression is that they require the sending and receiving hosts to

process every byte of data in the message. It is for this reason that

presentation formatting and compression are sometimes called <em>data

manipulation</em> functions. This is in contrast to most of the protocols we

have seen up to this point, which process a message without ever looking

at its contents. Because of this need to read, compute on, and write

every byte of data in a message, data manipulations affect end-to-end

throughput over the network. In some cases, these manipulations can be

the limiting factor.</p>

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