Mark Cuban at Blog Maverick

At Blog Maverick, in a post titled "Metcalfe's Law and Video," Mark Cuban discusses a different perspective on network value, specifically with a view towards the intensity over time of connectivity. He comments that "the more people that see content when it is originally "broadcast," regardless of the distribution medium, the more valuable the content." Although that can be demonstrated by simple net present value calculations, he is talking about emergent effects, such as emotional attachment and the social value from real or virtual simultaneous participation.

He also hypothesizes that not only is there greater value from simultaneous delivery, but also that there is greater cost. His argument is that networks that are designed for large scale simultaneous delivery of content cost more than those that are less ambitious.

To me, this is arguable. For example, there are inherent economies in using a broadcast, content distribution network, or IP multicast to distribute content simultaneously, than to keep redelivering it on demand and sequentially. If the capital expenditure for a scalable and feature-rich network has been made, broadcast and multicast technologies and architectures actually reduce cost per bit delivered per person.

If you combine his viewpoint on the value add of "live" and simultaneous events, with my observation that such events can actually cost less, that means that there is a sweet spot, if the network is engineered properly, in delivering live simultaneous content versus delayed and on-demand content.

This conclusion is actually not surprising, since traditional broadcast TV and movie theaters were only economically viable (in their day) due to the cost reductions inherent in broadcasting program content to a large simultaneous audience rather than unicasting it asynchronously. Of course, today's technology has now reduced the marginal cost of unicasting to be an infinitesimal fraction of a customers willingness to pay for such content.

Or so it would seem. In reality though, for the foreseeable future there will be content that is too bandwidth-hungry for widespread acceptance. Maybe YouTube videos don't have that property right now, but what about HDTV to your laptop screen? How many people are willing to pay for mobile bandwidth sufficient to deliver it in real time, say for 1080p video conferencing? If not that, how about digital cinema quality images?

For the next 5 to 10 years, there will always be that dilemma. After that, perhaps not, because we will have the ability to deliver enough bandwidth to each user, whether fixed or mobile, to equal or exceed the limits of human perception. At that point, until we evolve or bio-engineer our visual cortex and other sensory modalities to become Human 2.0, any additional bandwidth will be overkill, at least for the purposes of entertainment.

Linked by Albert-Laszlo Barabasi

Dr. Barabasi's book "Linked" is very readable overview of the math underlying a variety of network architectures, with many real-world examples in a variety of contexts. Briefly, three main types of networks are addressed. One, a random network, where links between nodes are created at random. Secondly, a "small-world" network, where most nodes are linked to nearby "neighbors," and a few links span across clusters. As studies by Watts and Strogatz, these types of networks lead to six degrees of separation types of architectures, where any node can reach any other node in a small number of hops.

However, he points out that neither type of network represents the type of structure one might find in, say, a telecommunications network or the World-Wide Web. Therefore a third type of network, a "scale-free" network, comprising a few larger hubs and many smaller hubs and endpoints is introduced. His research indicates that the node degree distribution matches the power-law distribution of many real-world structures, including neural networks and the World-Wide Web.

These real-world networks arise when two phenomena are present: one, growth, and two, preferential attachment for these growing networks. Also, implicit in the model is that each new node links to a fixed number k of existing nodes. Based on these assumptions, where a new node will tend to prefer to connect to existing nodes with more connections, a scale-free architecture emerges.

Interestingly, if we define the value of a link as a constant when it exists and as zero when it doesn't exist, the overall connectivity value of any of these networks is provably linear, based on the assumptions.