  We consider Kleinberg's celebrated small world graph model (Kleinberg, 2000),
in which a D-dimensional grid {0,...,n-1}^D is augmented with a constant number
of additional unidirectional edges leaving each node. These long range edges
are determined at random according to a probability distribution (the
augmenting distribution), which is the same for each node. Kleinberg suggested
using the inverse D-th power distribution, in which node v is the long range
contact of node u with a probability proportional to ||u-v||^(-D). He showed
that such an augmenting distribution allows to route a message efficiently in
the resulting random graph: The greedy algorithm, where in each intermediate
node the message travels over a link that brings the message closest to the
target w.r.t. the Manhattan distance, finds a path of expected length O(log^2
n) between any two nodes. In this paper we prove that greedy routing does not
perform asymptotically better for any uniform and isotropic augmenting
distribution, i.e., the probability that node u has a particular long range
contact v is independent of the labels of u and v and only a function of
||u-v||.
  In order to obtain the result, we introduce a novel proof technique: We
define a budget game, in which a token travels over a game board, while the
player manages a "probability budget". In each round, the player bets part of
her remaining probability budget on step sizes. A step size is chosen at random
according to a probability distribution of the player's bet. The token then
makes progress as determined by the chosen step size, while some of the
player's bet is removed from her probability budget. We prove a tight lower
bound for such a budget game, and then obtain a lower bound for greedy routing
in the D-dimensional grid by a reduction.
