8,822 research outputs found
Q-Strategy: A Bidding Strategy for Market-Based Allocation of Grid Services
The application of autonomous agents by the provisioning and usage of computational services is an attractive research field. Various methods and technologies in the area of artificial intelligence, statistics and economics are playing together to achieve i) autonomic service provisioning and usage of Grid services, to invent ii) competitive bidding strategies for widely used market mechanisms and to iii) incentivize consumers and providers to use such market-based systems.
The contributions of the paper are threefold. First, we present a bidding agent framework for implementing artificial bidding agents, supporting consumers and providers in technical and economic preference elicitation as well as automated bid generation by the requesting and provisioning of Grid services. Secondly, we introduce a novel consumer-side bidding strategy, which enables a goal-oriented and strategic behavior by the generation and submission of consumer service requests and selection of provider offers. Thirdly, we evaluate and compare the Q-strategy, implemented within the presented framework, against the Truth-Telling bidding strategy in three mechanisms – a centralized CDA, a decentralized on-line machine scheduling and a FIFO-scheduling mechanisms
Rational bidding using reinforcement learning: an application in automated resource allocation
The application of autonomous agents by the provisioning and usage of computational resources is an attractive research field. Various methods and technologies in the area of artificial intelligence, statistics and economics are playing together to achieve i) autonomic resource provisioning and usage of computational resources, to invent ii) competitive bidding strategies for widely used market mechanisms and to iii) incentivize consumers and providers to use such market-based systems.
The contributions of the paper are threefold. First, we present a framework for supporting consumers and providers in technical and economic preference elicitation and the generation of bids. Secondly, we introduce a consumer-side reinforcement learning bidding strategy which enables rational behavior by the generation and selection of bids. Thirdly, we evaluate and compare this bidding strategy against a truth-telling bidding strategy for two kinds of market mechanisms – one centralized and one decentralized
Bid-Centric Cloud Service Provisioning
Bid-centric service descriptions have the potential to offer a new cloud
service provisioning model that promotes portability, diversity of choice and
differentiation between providers. A bid matching model based on requirements
and capabilities is presented that provides the basis for such an approach. In
order to facilitate the bidding process, tenders should be specified as
abstractly as possible so that the solution space is not needlessly restricted.
To this end, we describe how partial TOSCA service descriptions allow for a
range of diverse solutions to be proposed by multiple providers in response to
tenders. Rather than adopting a lowest common denominator approach, true
portability should allow for the relative strengths and differentiating
features of cloud service providers to be applied to bids. With this in mind,
we describe how TOSCA service descriptions could be augmented with additional
information in order to facilitate heterogeneity in proposed solutions, such as
the use of coprocessors and provider-specific services
Integration of Blockchain and Auction Models: A Survey, Some Applications, and Challenges
In recent years, blockchain has gained widespread attention as an emerging
technology for decentralization, transparency, and immutability in advancing
online activities over public networks. As an essential market process,
auctions have been well studied and applied in many business fields due to
their efficiency and contributions to fair trade. Complementary features
between blockchain and auction models trigger a great potential for research
and innovation. On the one hand, the decentralized nature of blockchain can
provide a trustworthy, secure, and cost-effective mechanism to manage the
auction process; on the other hand, auction models can be utilized to design
incentive and consensus protocols in blockchain architectures. These
opportunities have attracted enormous research and innovation activities in
both academia and industry; however, there is a lack of an in-depth review of
existing solutions and achievements. In this paper, we conduct a comprehensive
state-of-the-art survey of these two research topics. We review the existing
solutions for integrating blockchain and auction models, with some
application-oriented taxonomies generated. Additionally, we highlight some open
research challenges and future directions towards integrated blockchain-auction
models
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