| Burbeck on Computing |
Multicellular Life as a Metaphor for the
Future of Computing |
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| Paper on Multicellularity (pdf) | Presentation (pdf) | Jon Udell's podcast | About the author |
Site Map |
![]() The Four Principles Summary table Specialization in computing Polymorphic Messaging in computing Loading code Interpreted code in biology Stigmergy and self in computing in the Internet Cell Suicide (Apoptosis) in computing Intertwined principles Complexity The problem Out of control Characterizing complexity Dynamic complexity Why the Biology Metaphor Parallels with computing Information processing Encapsulation Emergence Example emergent systems Multi-level emergence in computing in biology Scale and emergence Evolution of computing of multicellularity Conclusions Discussion & Comments Background Info |
Computers collaborate in the Internet much the way cells collaborate in multicellular organisms. But cells do it better! What are the parallels and what can we learn from them?As recently as 1990, most computers operated independently
from each other. True, some periodically exchanged email or used ftp to
transfer files. Some collaborated in client-server relationships with
internal corporate networks, banking systems or airline reservation
systems. And in 1992 a tiny number -- mostly in universities -- could
connect to the nascent Web. Nonetheless, for the most part, computing happened inside
single computers. Today an isolated computer is something of an oddity. At least
a billion computers exchange information at Internet
speeds. Google, Amazon, Yahoo and Baidu (China's Google equivalent)
require tens or even hundreds of thousands of computers to provide
services we take for granted and would be lost without. As more
computers
collaborate in more complicated and less transparent ways, the digital
world
inexorably becomes complex beyond our comprehension. But there is
no going back. Long ago single cell organisms evolved into
multicellular organisms. Groups of cells evolved ways to
collaborate with each other to
provide advantages not available to the individual cells. The cost of
increased complexity was repaid by the increased capabilities of the
collaborative multicellular organisms. However, collaboration requires a collaborative architecture -- a set of conventions that support useful cooperative behavior and help to suppress runaway complexity and external attempts to exploit or hijack a system. Both biological and computing systems suffer from unexpected consequences of complexity. Examples include autoimmune disorders in biological systems and buffer overflow vulnerabilities in computing. And it is no coincidence that viruses hijack both cells and computers. The parallels between biology and computing are fundamental. Multicellular biological systems organize themselves using architectural principles that multicellular computing can mimic (and already has begun to mimic) to tame the spiraling problems of complexity and out-of-control interactions. This website explores the four most central architectural principles that enabled the transition from single-cell life to multicellular life and are now enabling the emergence of multicellular computing. They are:
These
four principles are not
independent. They are deeply
intertwined both in life and in computing. If you are impatient, you might want to skip right to the end of the story and read the conclusions. However, as with many a mystery novel, reading the last few pages will tell you who-done-it without telling you the most interesting part...why. The conclusions may well not make much sense without seeing how we get there. The site map or the link panels on the left of each page can help navigate to the various pages in an order that helps make sense of the story. |
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Contact: sburbeck at mindspring.com |
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