 
Summary: Reducing Truthtelling Online Mechanisms to Online Optimization
Baruch Awerbuch Yossi Azar y Adam Meyerson z
Abstract
We describe a general technique for converting an online algorithm B to a truthtelling mechanism. We require that the
original online competitive algorithm has certain ``niceness'' properties in that actions on future requests are independent
of the actual value of requests which were accepted (though these actions will of course depend upon the set of accepted
requests). Under these conditions, we are able to give an online truth telling mechanism (where the values of requests
are given by bids which may not accurately represent the valuation of the requesters) such that our total profit is within
O( + log ) of the optimum offline profit obtained by an omniscient algorithm (one which knows the true valuations
of the users). Here is the competitive ratio of B for the optimization version of the problem, and is the ratio of the
maximum to minimum valuation for a request. In general there is
an
32 ) lower bound on the ratio of worstcase profit
for a truth telling mechanism when compared to the profit obtained by an omniscient algorithm, so this result is in some
sense best possible. In addition, we prove that our construction is resilient against many forms of ``cheating'' attempts,
such as forming coalitions.
We demonstrate applications of this result to several problems. We develop online truthtelling mechanisms for online
routing and admission control of path or multicast requests, assuming large network capacities. Assuming the existance
of an algorithm B for the optimization version of the problem, our techniques provide truthtelling mechanisms for general
combinatorial auctions. However, designing optimization algorithms may be difficult in general because of online or
