What E2 might be all about (secretly) or its eventual logical conclusion:
Also known as ant colony optimization or swarm theory:
Field of study in communications and networking which seeks to optimize network services by emulating the behavioral and operating procedure of hive-mind insects like bees, wasps and ants as a method for accommodating future systems which will
likely have billions of nodes and users (...there are, after all, serious discussions about giving toasters their own IP address, thanks to the
heavily marketed ubiquitous computing drive; see Nicholas Negroponte et al.). Overtaxed systems might 'adapt' by themselves, given
small levels of artificial intelligence. In essence, messages and nodes themselves begin to 'act' like insects, by modeling and
programming the innate mechanisms of these hives and applying them to network design. Researchers have already developed an ant colony algorithm, called ABC, for routing and load balancing in circuit switched
telecommunications networks and routing in packet switched telecommunications networks.
(Want your very own Bio-net simulator? William S. Burroughs would want us all to have one : v. 2.2 (Gzip'd, 450KB. 3/7/2000.)
http://netresearch.ics.uci.edu/bionet/resources)
Further reading:
- Schoonderwoerd R. et al. (1997). Ant-based Load Balancing in Telecommunications Networks. Adaptive Behavior, 5(2):169-207.
- Di Caro G. and M. Dorigo (1997). AntNet: A Mobile Agents Approach to Adaptive Routing.
(ftp://iridia.ulb.ac.be/pub/mdorigo/tec.reps/TR.07.AntNet-TecRep-97-12.pdf)
- Navarro and Sinclair (1999). Ant Colony Optimisation for Virtual-Wavelength-Path Routing and Wavelength Allocation. July 1999. (http://esewww.essex.ac.uk/~mcs/ps/cec99_nav.ps.gz)