The benefits of any truly transformative technology are at first exaggerated, but their long-term effects surprise everyone. At the moment, mesh networks are experiencing such misvaluation. Their promoters (and they are many) now describe them with hyperbolic enthusiasm; but in the end they will be the mechanism by which machine intelligence becomes like electricity – that is, invisible and ubiquitous.
Mesh networks are not so very new: their conceptual lineage dates back to packet radio, a kind of digital data transmission used by amateur radio hackers in the 1970s. But investments in more reliable and intelligent networks made during the 1990s by the U.S. Department of Defense renewed interest in meshes; and within the last five years, academic institutions like MIT’s Media Lab and startups like Aeria, BelAir Networks, Ember, MeshNetworks (now owned by Motorola), and Tropos Networks have rapidly advanced the technology. (Disclosure: Ember’s chairman and acting chief executive, Bob Metcalfe, also serves on Technology Review’s board.)
Meshies believe that mesh networks will overthrow traditional networking and communications and create entirely new kinds of distributed software. For the purposes of this column, mesh networks (sometimes called mobile ad hoc networks, or MANETs) are local-area networks whose nodes communicate directly with each other through wireless connections. It is the lack of a hub-and-spoke structure that distinguishes a mesh network. Meshes do not need designated routers: instead, nodes serve as routers for each other. Thus, data packets are forwarded from node to node in a process that network technologists term “hopping.”
Before dismissing mesh networks as being of interest only to specialists, consider their advantages over existing hub-and-spoke networks. Mesh networks are self-healing: if any node fails, another will take its place. They are anonymous: nodes can come and go as they will. They are pervasive: a mobile node rarely encounters dead spots, because other nodes route around objects that hinder communication. Meshes are cheap, efficient, and simple.
But they are still in development. The chief technical challenge for meshes is the inherent unreliability of wireless links. Because the unreliability compounds with each hop, the size of meshes is now limited. A related problem with hopping is that, for now, moving nodes seldom establish new connections “seamlessly”: when a network’s topology changes, some transmission paths can be temporarily disrupted. Therefore, voice and video sit unhappily on meshes.
Meshes lack standards, too: low-bit-rate mesh networking has a standard called ZigBee that is supported by around 100 companies, including Motorola, Mitsubishi, Phillips, and Samsung, but high-bit-rate communications have no such standard (although the 802.11 committee of the Institute of Electrical and Electronics Engineers hopes to create one by next May).
What does all this mean? A few, early applications of mesh networks are already emerging. Meshes will allow municipalities to create cheap or free urban Wi-Fi networks (we will be writing about Philadelphia’s effort in our November issue). Meshes have obvious advantages for military and security personnel who want networks that are unbreakable and “horizontal” (see “Instant Networks,” June 2005).
Environmental scientists like meshes because they can provide continuous data from large geographical areas over many years (see “Casting the Wireless Sensor Net,” July/August 2003). But the most important application of meshes will be in what technologists once called “pervasive computing”: embedding sensors and processors in things like clothes, electronics, and buildings and connecting them into smart networks.
Mesh networks will be big business. There are billions of networked devices and embedded processors in the world; many more will be built. The best way to connect all of them will be through mesh networks. But the most disruptive business impact of meshes will be this: telecommunications companies do not own them. Meshes profoundly diminish the organizations that own and manage communications backbones.
But I believe that the most intriguing aspect of mesh networks is their cybernetic qualities. That is, mesh networks are adaptive systems that resemble biological systems (we recently wrote about MIT mathematics professor Norbert Wiener, the founder of cybernetics: see “Cybernought,” June 2005). Many meshies like to say that they draw their inspiration from the behavior of swarming bees or ants.
Some go even further. In “AntHocNet: An Adaptive Nature-Inspired Algorithm for Routing in Mobile Ad-Hoc Networks,” published this year by the Dalle Molle Institute for Artificial Intelligence in Manno, Switzerland, Gianni di Caro and colleagues describe how ants from the same colony will converge to discover the shortest path from their nest to food; he proposes an algorithm for routing on mesh networks that explicitly imitates ant behavior. Ant colonies suggest how apparently intelligent behavior can emerge from a few fairly simple rules. Maybe mesh networks will promote new technologies that possess some of the properties of emergent intelligence? Write and tell me at email@example.com.