Efficient information gathering on the Internet

The Internet offers unprecedented access to information. At present most of this information is free, but information providers ore likely to start charging for their services in the near future. With that in mind this paper introduces the following information access problem: given a collection of n information sources, each of which has a known time delay, dollar cost and probability of providing the needed information, find an optimal schedule for querying the information sources. We study several variants of the problem which differ in the definition of an optimal schedule. We first consider a cost model in which the problem is to minimize the expected total cost (monetary and time) of the schedule, subject to the requirement that the schedule may terminate only when the query has been answered or all sources have been queried unsuccessfully. We develop an approximation algorithm for this problem and for an extension of the problem in which more than a single item of information is being sought. We then develop approximation algorithms for a reward model in which a constant reward is earned if the information is successfully provided, and we seek the schedule with the maximum expected difference between the reward and a measure of cost. The monetary and time costs may either appear in the cost measure or be constrained not to exceed a fixed upper bound; these options give rise to four different variants of the reward model