|
ABSTRACT
We consider the following problem, which arises in the context of distributed Web computations. An aggregator aims to combine specific data from n sources. The aggregator contacts all sources at once. The time for each source to return its data to the aggregator is independent and identically distributed according to a known distribution. The aggregator at some point stops waiting for data and returns an answer depending only on the data received so far. If the aggregator returns the aggregated information from k of the n sources at time t it obtains a reward Rk(t) that grows with k and decreases with t. The goal of the aggregator is to maximize its expected reward.We prove that for certain broad families of distributions and broad classes of reward functions, the optimal plan for the aggregator has a simple form and hence can be easily computed.
REFERENCES
Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.
| |
1
|
|
| |
2
|
|
 |
3
|
Baruch Awerbuch , Yossi Azar , Amos Fiat , Tom Leighton, Making commitments in the face of uncertainty: how to pick a winner almost every time (extended abstract), Proceedings of the twenty-eighth annual ACM symposium on Theory of computing, p.519-530, May 22-24, 1996, Philadelphia, Pennsylvania, United States
[doi> 10.1145/237814.238000]
|
| |
4
|
|
| |
5
|
|
| |
6
|
Y. S. Chow, H. Robbins, and D. Siegmund. Great Expectations: The Theory of Optimal Stopping, Houghton Mifflin Company, Boston, 1971.
|
| |
7
|
|
| |
8
|
E. B. Dynkin. Markov processes and related problems of analysis, Cambridge University Press, Cambridge, 1981.
|
| |
9
|
T. Ferguson. A Poisson Fishing Model. In Festschrift for Lucien Le Cam, pp. 234-244, Springer, 1997.
|
 |
10
|
|
| |
11
|
|
| |
12
|
K. C. Kapur and L. A. Lamberson. Reliability in Engineering Design. John Wiley and Sons, New York, 1977.
|
| |
13
|
|
| |
14
|
S. Ross. Infinitesimal Look-Ahead Stopping Rules. The Annals of Mathematical Statistics, 42(1):297-303, 1971.
|
| |
15
|
S. Ross. Stochastic Processes. John Wiley and Sons, New York, 1983.
|
| |
16
|
M. Shaked and J. G. Shanthikumar. Stochastic Orders and Their Applications. Academic Press, San Diego, 1994.
|
| |
17
|
N. Starr and M. Woodroofe. Gone fishin': Optimal stopping based on catch times. University of Michigan Technical Report, Department of Statistics, 1974.
|
| |
18
|
N. Starr, R. Wardrop, and M. Woodroofe. Estimating a mean from delayed observations. Zeitschrift fur Wahrscheinlichkeitstheorie und verwandte Gebeite, 35:103-116, 1976.
|
| |
19
|
D. Stoyan. Comparison Methods for Queues and Other Stochastic Models. John Wiley and Sons, Berlin, 1983.
|
CITED BY 3
|
|
|
|
|
Matt Lepinski , David Liben-Nowell , Seth Gilbert , April Rasala Lehman, Playing games in many possible worlds, Proceedings of the 7th ACM conference on Electronic commerce, p.150-159, June 11-15, 2006, Ann Arbor, Michigan, USA
|
|
|
|
|