15,603 research outputs found
Cloud/fog computing resource management and pricing for blockchain networks
The mining process in blockchain requires solving a proof-of-work puzzle,
which is resource expensive to implement in mobile devices due to the high
computing power and energy needed. In this paper, we, for the first time,
consider edge computing as an enabler for mobile blockchain. In particular, we
study edge computing resource management and pricing to support mobile
blockchain applications in which the mining process of miners can be offloaded
to an edge computing service provider. We formulate a two-stage Stackelberg
game to jointly maximize the profit of the edge computing service provider and
the individual utilities of the miners. In the first stage, the service
provider sets the price of edge computing nodes. In the second stage, the
miners decide on the service demand to purchase based on the observed prices.
We apply the backward induction to analyze the sub-game perfect equilibrium in
each stage for both uniform and discriminatory pricing schemes. For the uniform
pricing where the same price is applied to all miners, the existence and
uniqueness of Stackelberg equilibrium are validated by identifying the best
response strategies of the miners. For the discriminatory pricing where the
different prices are applied to different miners, the Stackelberg equilibrium
is proved to exist and be unique by capitalizing on the Variational Inequality
theory. Further, the real experimental results are employed to justify our
proposed model.Comment: 16 pages, double-column version, accepted by IEEE Internet of Things
Journa
Optimal Posted Prices for Online Cloud Resource Allocation
We study online resource allocation in a cloud computing platform, through a
posted pricing mechanism: The cloud provider publishes a unit price for each
resource type, which may vary over time; upon arrival at the cloud system, a
cloud user either takes the current prices, renting resources to execute its
job, or refuses the prices without running its job there. We design pricing
functions based on the current resource utilization ratios, in a wide array of
demand-supply relationships and resource occupation durations, and prove
worst-case competitive ratios of the pricing functions in terms of social
welfare. In the basic case of a single-type, non-recycled resource (i.e.,
allocated resources are not later released for reuse), we prove that our
pricing function design is optimal, in that any other pricing function can only
lead to a worse competitive ratio. Insights obtained from the basic cases are
then used to generalize the pricing functions to more realistic cloud systems
with multiple types of resources, where a job occupies allocated resources for
a number of time slots till completion, upon which time the resources are
returned back to the cloud resource pool
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