“The Exploit” was an interesting extension to last week’s read and discussion on “Connected” reading.

One of the key items that I thought the authors surfaced in discussing ‘nodes’ was that one of the failings of mathematical network theory is that it fails to capture the fact that the network has life!

As the authors state:

Thus, not only do existing network theories exclude the element that makes a network a network (it’s dynamic quality), but they also require that networks exist in relation to fixed, abstract configurations or patterns (either centralized or decentralized, either technical or political), and to specific anthropomorphic actors.

In other words, these networks only really exist in snapshots – moments frozen in time – where the network can be examined in a frozen state.

The nature of the network is that it’s fluid, dynamic, and ever-changing.  This applies to both computer networks and human networks, especially with the proliferation of network-enabled devices and the ubiquity of WiFi and open networks.  My device can ‘attach’ to the network anywhere at any time and thus alter the topology of the network.

At my work, we are creating a product that, as one of its core features, captures a network’s topology.  In using this product, though, I’ve observed what the authors talk about here.  When I view my home network topology, I don’t just get the active view of the network, I also see artifacts of devices that were once part of my network.  Since this product is a network monitor, this is considered a feature of the device – it tracks devices’ entrance and exit from your network.  But, this includes things like friend’s iPods and iPhones and test systems I work with.  It becomes a chore to keep my network topology in a ‘clean’ state, because it’s always being polluted by devices whose presence on the network is intermittent and fleeting.

Expanding this problem out further, imagine how something like this would look to a mobile phone carrier, for example.  Thousands of devices cleanly register or deregister at any time on their mobile networks., and millions are in an active, useful state — but auto switch from physical tower to tower, and may even go completely off the grid at times only to pop up later.  It would be impossible for an at&t or Verizon to map all of its users in any kind of visualized topology, because the rate of change to that topology certainly exceeds any supercomputer’s capability to re-render the topology in any human-understandable format.

Considering this phenomenon reminds me of an atomic law that I remember studying in my undergraduate – one that I can’t recall the name of – but which states that you can never truly know where in the ‘electron cloud’ an electron is at a particular time because you can never slow down the orbit enough to get a glimpse of it without changing the orbit itself (or changing the atom itself).

It also goes back to a more general scientific theory that it is impossible to study something without impacting or influencing the environment the thing you are studying is in.

In other words, there is no real way to freeze time and nature to really capture any of the living ecosystems or networks that surround us, whether they be social or technical.

One other thing that stuck in my craw as I read this book was a brief but mind-bending allegation the authors made on page 22 that some “antiweb” might one day come into existence that could eradicate or reorganize the networks as we currently understand them.  They sounded like they would get to this point later, but I seemed to have missed their point.

Last thing I want to point out is that I think their discussion on protocols is fascinating.  Being a student of the TCP/IP protocol, I think it is an incredibly fascinating protocol in that packet switched networks rarely take the most efficient path through the network.  TCP/IP is not known for efficiency, but it IS known for resiliency.  A TCP packet is rarely truly ‘lost’ in the network because the protocol is a very resilient protocol.  If the packet fails to reach its destination, it will scale back along its path to find a new route to the destination.  I don’t really have a lot to say about it, or what the authors pointed out, except to say it’s always fascinated me!

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