Block The Emergency Exit for Faster Evacuations

NewScientist reports that Japanese physicists timed a crowd of 50 women(?) as they exited as fast as possible through a door. They then repeated the experiment with a 20 cm (10 inch) wide pillar placed 65 cm (2 feet) in front of the exit to the left-hand side. The obstacle increased the exit throughput by an extra seven people per minute.

"Usually, the exit becomes clogged by people competing for the small space, and the crowd is slowed. The pillar blocks pedestrians arriving at the exit from the left so effectively that the number of people attempting to occupy the space just in front of the exit is reduced, says Yanagisawa. With reduced crowding there are fewer conflicts and the outflow rate increases."

How does this apply to computer performance? Think polling systems, where there are multiple waiting lines or buffers but only one service facility, like a grocery store with the usual checkout lanes but only one cashier running between them! Would you want to shop in that store? In the physics experiment, the exit is the single server and the lines are the streams of people (women?) approaching the exit from all angles. The asymmetric placement of the pillar effectively reduces the number of exit streams that can form (I'm guessing).

We already know from queueing theory that better performance is achieved with multiple servers processing a single waiting line. It follows that having less than one server—as is the case with polling systems—must be less efficient. But given that there is a necessity to adopt a polling system approach (e.g., an exit door), the fewer waiting lines or exit streams, the better. Knowing the potential performance impact, why would anyone ever implement polled queues in computer systems? Somewhat surprisingly, not only are polling systems used, they're used all over the place. Here are a few disparate examples:

• Bluetooth (PDF)
  
• Linux epoll
  
• Java
  
• Network switches
  
• Clusters (PDF)
  

In a nutshell, there are many situations in computer architectures where it is necessary to multiplex more streams of requests than there are resources to service them. It may not be optimal, but it may be necessary. Achieving best performance under the constraint of polling involves many subtle issues, which I discuss in my Perl PDQ book. Foremost among them is keeping the request sizes small (for some value of small). Returning to the physics experiments, there's a bit more to it.

"... the positioning of the pillar is crucial, says Yanagisawa. When the researchers moved the pillar so that it stood directly in front of the exit's centre, rather than to the left, the outflow rate dropped" (by approx. 5%)

Presumably, placing the pillar to one side (left) forces everybody to move in the same lateral direction (toward the right). Placing it in the middle means people will try to move either left or right (jostling), thus tending to impede the forward flow.