14,925 research outputs found
Social Welfare Maximization Auction in Edge Computing Resource Allocation for Mobile Blockchain
Blockchain, an emerging decentralized security system, has been applied in
many applications, such as bitcoin, smart grid, and Internet-of-Things.
However, running the mining process may cost too much energy consumption and
computing resource usage on handheld devices, which restricts the use of
blockchain in mobile environments. In this paper, we consider deploying edge
computing service to support the mobile blockchain. We propose an auction-based
edge computing resource market of the edge computing service provider. Since
there is competition among miners, the allocative externalities (positive and
negative) are taken into account in the model. In our auction mechanism, we
maximize the social welfare while guaranteeing the truthfulness, individual
rationality and computational efficiency. Based on blockchain mining experiment
results, we define a hash power function that characterizes the probability of
successfully mining a block. Through extensive simulations, we evaluate the
performance of our auction mechanism which shows that our edge computing
resources market model can efficiently solve the social welfare maximization
problem for the edge computing service provider
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
Blockchain Solutions for Multi-Agent Robotic Systems: Related Work and Open Questions
The possibilities of decentralization and immutability make blockchain
probably one of the most breakthrough and promising technological innovations
in recent years. This paper presents an overview, analysis, and classification
of possible blockchain solutions for practical tasks facing multi-agent robotic
systems. The paper discusses blockchain-based applications that demonstrate how
distributed ledger can be used to extend the existing number of research
platforms and libraries for multi-agent robotic systems.Comment: 5 pages, FRUCT-2019 conference pape
Optimal Pricing-Based Edge Computing Resource Management in Mobile Blockchain
As the core issue of blockchain, the mining requires solving a proof-of-work
puzzle, which is resource expensive to implement in mobile devices due to high
computing power needed. Thus, the development of blockchain in mobile
applications is restricted. In this paper, we consider the edge computing as
the network enabler for mobile blockchain. In particular, we study optimal
pricing-based edge computing resource management to support mobile blockchain
applications where the mining process can be offloaded to an Edge computing
Service Provider (ESP). We adopt a two-stage Stackelberg game to jointly
maximize the profit of the ESP and the individual utilities of different
miners. In Stage I, the ESP sets the price of edge computing services. In Stage
II, 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 uniform and discriminatory pricing schemes.
Further, the existence and uniqueness of Stackelberg game are validated for
both pricing schemes. At last, the performance evaluation shows that the ESP
intends to set the maximum possible value as the optimal price for profit
maximization under uniform pricing. In addition, the discriminatory pricing
helps the ESP encourage higher total service demand from miners and achieve
greater profit correspondingly.Comment: 7 pages, submitted to one conference. arXiv admin note: substantial
text overlap with arXiv:1710.0156
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