(I'll paste this here as it's already being shared online)
"For instance, if you're in line waiting to get into a popular nightspot, you might figure out how long you'll have to wait by standing there for a while and trying to estimate the rate at which people are entering. With Little's Law, though, you could reason, `This place holds about 60 people, and the average Joe will be in there about 3 hours, so we're entering at the rate of about 20 people an hour. The line has 20 people in it, so that means we'll wait about an hour."
Bentley also cites the following, attributing them to Peter Denning:
"The average number of objects in a queue is the product of the entry rate and the average holding time."
"I have 150 cases of wine in my basement and I consume (and purchase) 25 cases per year. How long do I hold each case? Little's Law tells me to divide 150 cases by 25 cases/year, which gives 6 years per case."
"The response-time formula for a multi-user system can be proved using Little's Law and flow balance. Assume n users of average think time z are connected to an arbitrary system with response time r. Each user cycles between thinking and waiting-for-response, so the total number of jobs in the meta-system (consisting of users and the computer system) is fixed at n. If you cut the path from the system's output to the users, you see a meta-system with average load n, average response time z+r, and throughput x (measured in jobs per time unit). Little's Law says n = x*(z+r), and solving for r gives r = n/x - z."
http://www.eecs.harvard.edu/~margo/cs261/background/p176-ben...
And a different presentation of some of the same material, on consequences of Little's Law, from his book Programming Pearls, quoted here: http://www.cs.fsu.edu/~baker/opsys/notes/queueing.html
(I'll paste this here as it's already being shared online)
"For instance, if you're in line waiting to get into a popular nightspot, you might figure out how long you'll have to wait by standing there for a while and trying to estimate the rate at which people are entering. With Little's Law, though, you could reason, `This place holds about 60 people, and the average Joe will be in there about 3 hours, so we're entering at the rate of about 20 people an hour. The line has 20 people in it, so that means we'll wait about an hour."
Bentley also cites the following, attributing them to Peter Denning:
"The average number of objects in a queue is the product of the entry rate and the average holding time."
"I have 150 cases of wine in my basement and I consume (and purchase) 25 cases per year. How long do I hold each case? Little's Law tells me to divide 150 cases by 25 cases/year, which gives 6 years per case."
"The response-time formula for a multi-user system can be proved using Little's Law and flow balance. Assume n users of average think time z are connected to an arbitrary system with response time r. Each user cycles between thinking and waiting-for-response, so the total number of jobs in the meta-system (consisting of users and the computer system) is fixed at n. If you cut the path from the system's output to the users, you see a meta-system with average load n, average response time z+r, and throughput x (measured in jobs per time unit). Little's Law says n = x*(z+r), and solving for r gives r = n/x - z."