18,439 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
Random Access Game and Medium Access Control Design
Motivated partially by a control-theoretic viewpoint, we propose a game-theoretic model, called random access game, for contention control. We characterize Nash equilibria of random access games, study their dynamics, and propose distributed algorithms (strategy evolutions) to achieve Nash equilibria. This provides a general analytical framework that is capable of modeling a large class of system-wide quality-of-service (QoS) models via the specification of per-node utility functions, in which system-wide fairness or service differentiation can be achieved in a distributed manner as long as each node executes a contention resolution algorithm that is designed to achieve the Nash equilibrium. We thus propose a novel medium access method derived from carrier sense multiple access/collision avoidance (CSMA/CA) according to distributed strategy update mechanism achieving the Nash equilibrium of random access game. We present a concrete medium access method that adapts to a continuous contention measure called conditional collision probability, stabilizes the network into a steady state that achieves optimal throughput with targeted fairness (or service differentiation), and can decouple contention control from handling failed transmissions. In addition to guiding medium access control design, the random access game model also provides an analytical framework to understand equilibrium and dynamic properties of different medium access protocols
Game Theoretic Approaches to Massive Data Processing in Wireless Networks
Wireless communication networks are becoming highly virtualized with
two-layer hierarchies, in which controllers at the upper layer with tasks to
achieve can ask a large number of agents at the lower layer to help realize
computation, storage, and transmission functions. Through offloading data
processing to the agents, the controllers can accomplish otherwise prohibitive
big data processing. Incentive mechanisms are needed for the agents to perform
the controllers' tasks in order to satisfy the corresponding objectives of
controllers and agents. In this article, a hierarchical game framework with
fast convergence and scalability is proposed to meet the demand for real-time
processing for such situations. Possible future research directions in this
emerging area are also discussed
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