Reporting Standard Errors for USL Coefficients

In a recent Guerrilla CaP Group discussion, Baron S. wrote:

....
BS> Using gnuplot against the dataset I gave, I get 
BS>    sigma   0.0207163 +/- 0.001323 (6.385%) 
BS>    kappa   0.000861226 +/- 5.414e-05 (6.287%) 

The Gnuplot output includes the errors for each of the universal scalability law (USL) coefficients. A question about the magnitude of these errors also arose in a recent talk I gave. Typically, this question doesn't come up because there's more focus on assessing the residual errors as a measure of fit for the USL against the data set. Also, statistical accuracy can be a bigger issue when there are only a small number of samples. Barron reported 32 data points, so that's not an problem in this case.

Efficient Elevators: Algorithms, Cars and Queues

The latest PBS NOVA episode entitled "Trapped in an Elevator" is based on an actual event that occurred in 1999. Watching it reminded me that elevators (or lift in British english) can be regarded as a queueing system, viz., priority queues, which are also the basis for scheduling algorithms in operating systems and storage devices. A lot of this background can be found in Don Knuth's erudite volumes:

• Vol 1, p.280: elevator simulator program based on doubly-linked lists
  
• Vol 3, p.150: elevator scheduling as priority queues
  
• Vol 3, p.357: tape sorting reformulated as single elevator problem
  
• Vol 3, p.374: disk seeks treated as single elevator problem

[Best wishes for Randall's fiancée]

Cooking Up Some Hotsos for 2011

Just got word that my proposed presentation "Brooks, Cooks and Response Time Scalability" has been accepted for the Hotsos Symposium, March 2011 in Dallas, Texas.

Hotsos is a great conference that is Oracle-related but not Oracle-sponsored. As the name implies, the focus is on the performance of Oracle databases and applications, but it's been my experience that attendees are very keen to know about performance techniques, not matter what their context.

Hotsos 2011 will give me an opportunity to expand on my Nov 2007 observation that the USL contains a representation of the mythical man-month. In other presentations I've always talked about characterizing throughput scalability, but this time I'll extend the USL to quantifying response-time scalability.