The Internet is a multicellular organism.  Computers collaborate in the Internet/Web much the way cells collaborate in multicellular organisms.  But cells do it better!  What can we learn from them?

Single cell organisms evolved into multicellular organisms long ago.  In the process, they had to evolve ways to collaborate rather than compete with each other. Today we are seeing a similar transition in computing. Twenty years ago few computers ever communicated directly with others.  Now hundreds of millions of computers exchange information at Internet speeds. The digital world inexorably becomes more complex.  Bigger groups of computers collaborate in more complicated and less transparent ways. In doing so, they encounter problems common to all complex systems -- problems already solved in the evolution of living systems.

The way computing is evolving is similar to the way other complex systems -- biological, social, ecological, and economic systems -- evolve. In all of these domains, the elements become more specialized and they interact with each other in more, and more complex, ways.  In other words, the parallels between biology and computing are fundamental, not accidental. So, understanding the principles of multicellular biological systems can suggest architectural principles that multicellular computing can mimic to tame the spiraling problems of complexity and out-of-control interactions.

• Specialization - There are, for example, about 250 different types of cells in humans.  Unspecialized cells don't "play well with others," hence are dangerous to any multicellular organism.  Similarly, overly generalized computers are increasingly dangerous to multicellular computing systems.
  
• Messaging - Cells communicate with each other via messenger molecules, never DNA,  The “meaning” of cell-to-cell messages is determined by the receiving cell, not the sender. Similarly, communication between computers in multicellular systems relies increasingly upon messaging. The meaning of the messages is determined by the receiver of the message not the sender. Transferring code between machines is increasingly recognized as problematic.
  
• Stigmergy - Groups of cells build extracellular structures (e.g., bones or connective tissue) which, in turn, dramatically affect the behavior of the very cells that built them.  The behavior of the whole organism is determined as much by interaction with the extracellular matrix as by direct interaction between the cells. Similarly, the external data, e.g., in databases, and network connectivity structures increasingly define multicellular computing systems, especially in the cooperative computing in the Internet.
  
• Programmed cell death (apoptosis) - Every healthy cell is prepared to commit suicide in the interest of the organism as a whole.  Cells that are infected by viruses kill themselves. Similarly, we are learning the importance of sacrificing individual compromised computers for the health of the whole multicellular computing system.
  

These four principles are not at all independent; they are deeply intertwined both in life and in computing.

The short history of the ideas

In 2000, I published some of these ideas in "The Tao of E-business Services" which introduces Service Oriented Architectures (SOA) and discusses my view of the underlying philosophy of SOA.  But, as Sam Ruby correctly pointed out in his 2002 blog, the discussion of multicellular computing ideas in the Tao paper was too cryptic.

The next public airing of the ideas was at a panel discussion on Metaphors for Peer-to-Peer computing at the 2001 O'Reilly Peer-to-peer conference, I argued there that distributed networked computing is evolving toward organizational and architectural structures analogous to those found in multicellular biological organisms.  Put most simply -- perhaps overly so -- the central idea is that:

A small group of people were receptive to the multicellular computing ideas as a way to get a handle on the problem of ever increasing complexity.  One of them, Clay Shirky, invited me to give a talk on the ideas at the TII/Vanguard conference on The Challenge of Complexity, (2004, in Los Angeles).  That led to a presentation and a paper in which I explain the ideas more clearly (I hope) and in much greater detail.

The most recent turn of events was a long interview with Jon Udell, published as a podcast April 14, 2006 and the creation of the "webified" version of the ideas that you are currently reading.

Where to next?

Some Recommended Background Reading on Complexity

• Out of Control : The New Biology of Machines, Social Systems and the Economic World, Kevin Kelly, Perseus Pr; ISBN: 0201483408, 1996    See its page at  Amazon.com
  
• The Origins of Order : Self-Organization and Selection in Evolution, Stuart A. Kaufman,  Oxford Univ Press; ISBN: 0195079515, 1993    See its page at  Amazon.com
  
• At Home in the Universe : The Search for Laws of Self-Organization and Complexity, Stuart A. Kaufman, Oxford Univ Pr (Trade); ISBN: 0195111303, 1996    See its page at  Amazon.com
  
• Hidden Order : How Adaptation Builds Complexity, John H. Holland, Perseus Pr; ISBN: 0201442302, 1996    See its page at  Amazon.com
  
• Synergy and Self-Organization in The Evolution of Complex Systems, Peter A. Corning, Systems Research 12(2):89-121 (1995)

Contact:  sburbeck at mindspring.com