DocumentCode
3559047
Title
Constrained Sequential Resource Allocation and Guessing Games
Author
Chang, Nicholas B. ; Liu, Mingyan
Author_Institution
Michigan Univ., Ann Arbor, MI
Volume
54
Issue
11
fYear
2008
Firstpage
4946
Lastpage
4965
Abstract
In this paper, we consider a constrained sequential resource allocation problem where an individual needs to accomplish a task by repeatedly guessing/investing a sufficient level of effort/input. If the investment falls short of a minimum required level that is unknown to the individual, she fails; with each unsuccessful attempt, the individual then increases the input and tries again until she succeeds. The objective is to complete the task with as little resources/cost as possible subject to a delay constraint. The optimal strategy lies in the proper balance between 1) selecting a level (far) below the minimum required and therefore having to try again, thus wasting resources, and 2) selecting a level (far) above the minimum required, and therefore, overshooting and wasting resources. A number of motivating applications arising from communication networks are provided. Assuming that the individual has no knowledge on the distribution of the minimum effort required to complete the task, we adopt a worst-case cost measure and a worst-case delay measure to formulate the above constrained optimization problem. We derive a class of optimal strategies, shown to be randomized, and obtain their performance as a function of the constraint.
Keywords
game theory; optimisation; resource allocation; telecommunication networks; communication networks; constrained sequential resource allocation; guessing games; optimization problem; worst-case cost measure; worst-case delay measure; Algorithm design and analysis; Collaborative work; Communication networks; Constraint optimization; Delay; Investments; Laboratories; Radio transmitters; Receivers; Resource management; Competitive analysis; constrained optimization; data query and search; exponential functions; minimax problems; online algorithms; randomized algorithms; stochastic analysis;
fLanguage
English
Journal_Title
Information Theory, IEEE Transactions on
Publisher
ieee
ISSN
0018-9448
Type
jour
DOI
10.1109/TIT.2008.929946
Filename
4655439
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