Rent, Lease or Buy: Randomized Algorithms for Multislope Ski Rental
In the Multislope Ski Rental problem, the user needs a certain
resource for some unknown period of time. To use the resource, the
user must subscribe to one of several options, each of which
consists of a one-time setup cost (``buying price''), and cost
proportional to the duration of the usage (``rental rate''). The
larger the price, the smaller the rent. The actual usage time is
determined by an adversary, and the goal of an algorithm is to
minimize the cost by choosing the best option at any point in time.
Multislope Ski Rental is a natural generalization of the classical
Ski Rental problem (where the only options are pure rent and pure
buy), which is one of the fundamental problems of online
computation. The Multislope Ski Rental problem is an abstraction
of many problems where online decisions cannot be modeled by just
two options, e.g., power management in systems which can be shut
down in parts. In this paper we study randomized algorithms for
Multislope Ski Rental. Our results include the best possible
online randomized strategy for any additive instance, where the
cost of switching from one option to another is the difference in
their buying prices; and an algorithm that produces an
$e$-competitive randomized strategy for any (non-additive)
instance.
Competitive analysis
ski rental
randomized algorithms
503-514
Regular Paper
Zvi
Lotker
Zvi Lotker
Boaz
Patt-Shamir
Boaz Patt-Shamir
Dror
Rawitz
Dror Rawitz
10.4230/LIPIcs.STACS.2008.1331
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