'Jeff Dean':http://research.google.com/people/jeff/ , a famous Google engineer, popularized a list of latency 'numbers everyone should know':http://highscalability.com/numbers-everyone-should-know. The list is a great resource for designing large scale infrastructure systems.

*sidenote* 'Jeff Dean':http://research.google.com/people/jeff/ , a famous Google engineer, popularized a list of latency 'numbers everyone should know':http://highscalability.com/numbers-everyone-should-know. The list is a great resource for designing large scale infrastructure systems.

Algorithms and their complexity often occur in critical parts of computer systems, but I find that few engineers have a good understanding of how a O(n!) algorithm compares to a O(n^5^) one.

| #directed edges | 42 199 587 | 47 244 849 | 58 213 192 |
| #road categories | 13 | 13 | 4 |

Since we chose half a second to be our execution time and the size of our problem to be about 20 million edges it's clear from our table that m log n is too slow. So pure Dijkstra won't do. We need to look at how other algorithms like A star search or one based on 'Highway hierarchies':http://algo2.iti.kit.edu/schultes/hwy/esa06HwyHierarchies.pdf behave for this problem.

Since we chose half a second to be our execution time and the size of our problem to be about 40 million edges it's clear from our table that m log n is too slow. So pure Dijkstra won't do. We need to look at how other algorithms like A star search or one based on 'Highway hierarchies':http://algo2.iti.kit.edu/schultes/hwy/esa06HwyHierarchies.pdf behave for this problem.

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