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

Market-Based Scheduling in Distributed Computing Systems

In verteilten Rechensystemen (bspw. im Cluster und Grid Computing) kann eine Knappheit der zur Verfügung stehenden Ressourcen auftreten. Hier haben Marktmechanismen das Potenzial, Ressourcenbedarf und -angebot durch geeignete Anreizmechanismen zu koordinieren und somit die ökonomische Effizienz des Gesamtsystems zu steigern. Diese Arbeit beschäftigt sich anhand vier spezifischer Anwendungsszenarien mit der Frage, wie Marktmechanismen für verteilte Rechensysteme ausgestaltet sein sollten

Pricing the Cloud: An Auction Approach

Cloud computing has changed the processing and service modes of information communication technology and has affected the transformation, upgrading and innovation of the IT-related industry systems. The rapid development of cloud computing in business practice has spawned a whole new field of interdisciplinary, providing opportunities and challenges for business management research. One of the critical factors impacting cloud computing is how to price cloud services. An appropriate pricing strategy has important practical means to stakeholders, especially to providers and customers. This study addressed and discussed research findings on cloud computing pricing strategies, such as fixed pricing, bidding pricing, and dynamic pricing. Another key factor for cloud computing is Quality of Service (QoS), such as availability, reliability, latency, security, throughput, capacity, scalability, elasticity, etc. Cloud providers seek to improve QoS to attract more potential customers; while, customers intend to find QoS matching services that do not exceed their budget constraints. Based on the existing study, a hybrid QoS-based pricing mechanism, which consists of subscription and dynamic auction design, is proposed and illustrated to cloud services. The results indicate that our hybrid pricing mechanism has potential to better allocate available cloud resources, aiming at increasing revenues for providers and reducing expenses for customers in practice

Towards auction mechanisms for peer-to-peer energy trading in smart grids

The conventional energy grid is being replaced with the new emerging smart grid infras- tructure. This can be attributed to the fact that it only supports unidirectional energy ow, i.e., energy is transmitted from the producer to the consumer. Smart grid addresses issues such as grid reliability, blackouts, global warming, etc, by implementing various renewable energy sources readily available for consumer use. The clean electric power can be produced from local neighbourhoods, individual houses, to large industrial businesses. Therefore, with the im- plementation of alternative energy sources readily available, users connected to the smart grid can purchase electric power, enabling groups and individuals to generate a profitable income. However, challenges persist attributed to user cost, and power management, resulting in active work to investigate optimization techniques between users in P2P energy trading to enhance the performance of how users trade energy among each other. Among the various energy trading mechanisms, auction-based models have demonstrated excellent performance, targetting desir- able properties for P2P energy trading. In this work, we present three different auction-based models that can be utilized for practical energy trading. The prosumers (producers and con- sumers) of energy, play the role as sellers or buyers depending on the current supply and demand. Sellers with renewable energy sources participate to sell their excess of energy to generate a profit and satisfy the buyers' demand. We model the interaction with as single-sided and double-sided auctions, explicitly taking the dynamic nature of both the sellers and buyers into account. We further propose a profit maximization algorithm that considers power line cost, transmission capacity, and energy distribution. With theoretical analysis and simulations, we demonstrate that the proposed auctions are individually rational, truthful, computationally efficient, and budget-balanced