Optimal social welfare:A many-to-many data transaction mechanism based on double auctions

With the development of Big Data and the Internet of Things(IoT),the data value is more significant in both academia and industry.Trading can achieve maximal data value and prepare data for smart city services.Due to data's unique characteristics,such as dispersion,heterogeneity and distributed storage,an unbiased platform is necessary for the data trading market with rational trading entities.Meanwhile,there are multiple buyers and sellers in a practical data trading market,and this makes it challenging to maximize social welfare.To solve these problems,this paper proposes a Social-Welfare-Oriented Many-to-Many Trading Mechanism(SOMTM),which integrates three entities,a trading process and an algorithm named Many-to-Many Trading Algorithm(MMTA).Based on the market scale,market dominated-side and market fixed-side,simulations verify the convergency,economic properties and efficiency of SOMTM.

A New Protocol for Multi-Item Electronic Auctions

The authors propose a new protocol for muhizzitem electronic auctions. It has the following advantages： first, the protocol is more applicable and flexible than the previous protocols, in this protocol, each bidder can decide how many items to buy according to diiferent bidding prices, which are set by the seller at the beginning of the auction; second, privacy is well preserved, no third parties are needed in the protocol and the auction outcome is jointly computed by the bidders on their own without uncovering any additional information.

Multi-Dimensional Customer Data Analysis in Online Auctions

In this paper, we designed a customer-centered data warehouse system with five subjects： listing, bidding, transaction, accounts, and customer contact based on the business process of online auction companies. For each subject, we analyzed its fact indexes and dimensions. Then take transaction subject as example, analyzed the data warehouse model in detail, and got the multi-dimensional analysis structure of transaction subject. At last, using data mining to do customer segmentation, we divided customers into four types： impulse customer, prudent customer, potential customer, and ordinary customer. By the result of multi-dimensional customer data analysis, online auction companies can do more target marketing and increase customer loyalty.

Electronic Auction Scheme Based on Smart Contract and IPFS

Sealed-bid auctions are a vital transaction tool in the e-commerce field.Traditional centralized auction schemes typically result in severe threats to data integrity,information transparency,and traceability owing to their excessive reliance on third parties,and blockchain-based auction schemes generally suffer from high storage costs and are deficient in functional and architectural design.To solve these problems,this study presents a sealed-bid auction scheme that removes the third-party based on an Ethereum smart contract,ensuring data integrity,openness,and transparency in the execution process.The commitment mechanism and distributed storage system help to significantly reduce the user’s storage cost and protect the privacy of user bids.For the functional design,this study introduces a fulltext-retrieval and dispute-processing module for commodities,which reduces the defects existing in the functional module design of existing auction systems.Furthermore,a prototype auction system on the Ethereum test chain is built to validate the proposed scheme.Experiments show that compared with traditional storage methods,indirect storage based on a distributed storage system of texts and images can reduce the storage cost by at least 50%while ensuring data integrity.Finally,the gas cost at each stage of the auction scheme and the time required for the full-text retrieval of products are recorded to evaluate the scheme performance and analyze the test results.

Evolutionary Techniques for Reverse Auctions

Winner determination is one of the main challenges in combinatorial auctions. However, not much work has been done to solve this problem in the case of reverse auctions using evolutionary techniques. This has motivated us to propose an improvement of a genetic algorithm based method, we have previously proposed, to address two important issues in the context of combinatorial reverse auctions: determining the winner(s) in a reasonable processing time, and reducing the procurement cost. In order to evaluate the performance of our proposed method in practice, we conduct several experiments on combinatorial reverse auctions instances. The results we report in this paper clearly demonstrate the efficiency of our new method in terms of processing time and procurement cost.

A Few Notes on Auctions:The Boom in the Asymmetric Art Auction Market

The art market,following the example of financial markets,is divided into a primary market,where works are traded directly from artists,and a secondary market that is mainly the auction market.COVID-19 and galloping inflation have influenced the creation of a bull market in artwork.The high incomes of some buyers and inflation have influenced the emergence of the so-called“glittery”art market.Works by neglected artists have“very much taken on a life of their own”:fantasy art,works by young poster artists,casting“nightmares”-have been selling well for more than a year.People terrified of inflation are putting their money“in works of art”.The auction market dominates the primary market because anonymity makes it easier to enter the art market.The gallery market does not guarantee this anonymity.Very often,the auction market for works of art is used for money laundering.The purpose of this paper is to show that auction mechanisms are a good tool for the efficient allocation of goods and money in an era of galloping inflation,including non-standard objects such as works of art.These mechanisms,due to the information asymmetry,often lead to the generation of all kinds of pathologies and the increasing incidence of the phenomenon known as the winner’s curse.

Strategic Analysis of High-tech Auctions

This paper deals with the security voting structure in an auction mechanism used to sell an item Of high-tech. The design of security voting structure allows the seller to choose between two objectives that are not mutually consistent. However, if the seller wants to maximize his revenue, he should retain some shares to benefit from the future dividends generated by the acquirer. In addition, if he wants to sell his high-tech to the most efficient candidate, he should sell all the shares.

Cooperative management of an emission trading system:a private governance and learned auction for a blockchain approach

Although blockchain technology has received a significant amount of cutting-edge research on constructing a novel carbon trade market in theory,there is little research on using blockchain in carbon emission trading schemes(ETS).This study intends to address existing gaps in the literature by creating and simulating an ETS system based on blockchain technology.Using the ciphertext-policy attributed-based encryption algorithm and the Fabric network to build a platform may optimize the amount of data available while maintaining privacy security.Considering the augmentation of information interaction during the auction process brought about by blockchain,the learning behavior of bidding firms is introduced to investigate the impact of blockchain on ETS auction.In particular,implementing smart contracts can provide a swift and automatic settlement.The simulation results of the proposed system demonstrate the following:(1)fine-grained access is possible with a second delay;(2)the average annual compliance levels increase by 2%when bidders’learning behavior is considered;and(3)the blockchain network can process more than 350 reading operations or 7 writing operations in a second.Novel cooperative management of an ETS platform based on blockchain is proposed.The data access control policy based on CP-ABE is used to solve the contradiction between data privacy on the firm chain and government supervision.A learned auction strategy is proposed to suit the enhancement of information interaction caused by blockchain technology.This study provides a new method for climate change policymakers to consider the blockchain application of the carbon market.

Auction-based profit maximization offloading in mobile edge computing

Offloading Mobile Devices(MDs)computation tasks to Edge Nodes(ENs)is a promising solution to overcome computation and energy resources limitations of MDs.However,there exists an unreasonable profit allocation problem between MDs and ENs caused by the excessive concern on MD profit.In this paper,we propose an auction-based computation offloading algorithm,inspiring ENs to provide high-quality service by maximizing the profit of ENs.Firstly,a novel cooperation auction framework is designed to avoid overall profit damage of ENs,which is derived from the high computation delay at the overloaded ENs.Thereafter,the bidding willingness of each MD in every round of auction is determined to ensure MD rationality.Furthermore,we put forward a payment rule for the pre-selected winner to effectively guarantee auction truthfulness.Finally,the auction-based profit maximization offloading algorithm is proposed,and the MD is allowed to occupy the computation and spectrum resources of the EN for offloading if it wins the auction.Numerical results verify the performance of the proposed algorithm.Compared with the VA algorithm,the ENs profit is increased by 23.8%,and the task discard ratio is decreased by 7.5%.

Cotton Reserves Auctions Touch 57% of Release Plan but Prices Rally

With manufacturing slowly recovering amid improving economic conditions, cotton demand has increased prompting more orders among mills. However, with a deficient supply of cotton in the market, prices extend gains since Oct. 2009.

智能电网中基于二分图匹配的网络切片资源分配算法

为了解决智能电网中多类业务的服务质量需求难以同时得到满足的问题并兼顾电力终端和网络侧经济效用,提出了一种基于二分图匹配的网络切片资源分配算法。针对智能电网场景中的控制类和采集类业务,为电力终端分别制定相应的投标信息,并据此计算支付价格和效用矩阵;将网络切片与电力终端之间的资源分配建模为二分图匹配问题,根据不同业务的时延、传输速率或能耗需求,向终端分配不同的切片资源以最大化系统效用。仿真结果表明,相较于已有的双向拍卖算法和贪心算法,所提算法能够提高10%~20%的系统效用。

考虑绿色氢能证书和水电制氢的综合能源系统优化运行

利用清洁能源发电富余电力电解水制氢,绿色氢能实现了生产源头的二氧化碳零排放,在全球能源转型中扮演着重要角色。针对绿色氢能证书市场机制不健全等问题,该文提出一种考虑绿色氢能证书组合双向拍卖和水电制氢的综合能源系统优化运行方法。首先,为解决园区内绿色氢能证书价格和数量匹配不均衡的问题,提出绿色氢能证书组合双向拍卖(combinatorial double auction,CDA)交易机制竞价模型;其次,建立含水电制氢的综合能源系统优化模型,并将绿色氢能证书组合双向拍卖机制引入其中;最后,以某省含水电制氢的综合能源系统为例进行仿真分析,结果表明所提模型不仅能有效提高综合能源系统(integrated energy system,IES)的运行经济性,也能提升可再生能源的消纳量。

基于非齐次泊松过程的网上持久型一口价拍卖研究

为了刻画网上拍卖中的投标者到达过程中存在的末尾抢标机制,本文引入时间变量,建立了基于投标者到达的非齐次泊松过程的持久型一口价拍卖模型。通过令投标人与拍卖商的收益最大化,本文分析了投标人的均衡策略,拍卖商的最优一口价以及拍卖平台的最优佣金率,得到拍卖平台为了获取更多的佣金,一口价拍卖中佣金率的设定应小于普通拍卖中的佣金率。通过数值分析得到,投标人应在持续时间较短的一口价拍卖中积极选择一口价,在持续时间较长的一口价拍卖中更倾向于选择进行竞价,而拍卖商应尽可能地设置更长的拍卖持续时间以此获得更大的期望收益。

基于组合拍卖的广义共享储能运营机制设计

共享储能已经成为缓解可再生能源大规模并网带来的一系列问题的有效途径,但现有共享储能机制未充分考虑用户对于储能的互补性和替代性需求,严重影响用户购买意愿。此外,当前共享机制也未考虑储能的电量约束、充放电功率约束和荷电状态的影响,不利于运营商的投标策略设计,使其面临经济损失风险。因此,该文设计基于组合拍卖的广义共享储能运营机制。首先,考虑基站备用储能、空调、电动汽车充电站等资源具有储能特性而运行行为迥异的特性,利用广义储能模型对其进行统一聚合封装,降低多种需求侧资源的调度难度;其次,对储能使用权进行划分,设计广义储能功率使用权和容量使用权两种交易品种,并为卖方设计计及储能荷电状态的投标曲线,为买方设计不同时段、不同品种耦合需求的组合形式,以满足用户对储能的多种需求,提高用户满意度;然后,基于组合拍卖理论,设计包含投标、竞胜标决定、资源定价与资金结算等环节的共享储能运营机制,以实现广义共享储能资源的高效利用和社会福利的公平分配;最后,算例仿真结果表明,所述运营机制可满足用户灵活性需求,降低储能服务成本。

基于角色的区块链拍卖合约抽象建模及其时间安全性与公平性验证

为提升拍卖合约时间安全性验证效率及验证公平性,提出基于角色的拍卖合约抽象建模及其验证方法。首先,对合约源代码进行基于账户角色的抽象建模,转换为时间自动机网络模型,并对时间安全性进行形式化描述,用UPPAAL工具验证。其次,提取合约源代码机制,建立智能合约机制模型,同样转换为时间自动机网络模型,并对4种公平性进行形式化描述,再用UPPAAL验证。最后,通过2个经典案例证明了所提方法的可行性和有效性。

预算约束下多任务联邦学习激励机制

联邦学习是一种实现数据隐私保护的分布式机器学习范式,性能取决于数据源的质量和数据规模。客户端是理性个体,参与联邦学习将耗费计算、通信和隐私等成本,需要通过激励提高客户端的参与意愿。因此联邦学习能成功应用的关键之一是尽可能多地激励高质量数据客户端参与训练。多任务联邦学习环境下客户端拥有面向不同任务且质量不同的数据,并具有执行能力的约束。为提高多个学习任务的整体性能,在预算受限的条件下设计一种面向任务的客户选择和报酬机制。通过分析影响模型精度的重要因素,提出一种基于客户端数据样本分布特征的质量评估标准,并结合客户端成本信息,设计一种逆向拍卖的激励机制(EMD-MQMFL),实现客户端的任务指派和支付策略。从理论上分析和证明了该机制具有诚实性、个人理性以及预算可行性,并通过大量实验验证了该方法在联邦学习性能上的有效性。在MNIST、Fashion-MNIST、Cifar-10数据集上的实验结果表明,EMD-MQMFL在数据不平衡的情况下,平均模型精度比已有的机制至少提高5.6个百分点。

基于改进互补品序贯拍卖模型的建设用地指标定价机制

在引入用地指标与土地间相互依存特征前提下,本文改进了传统的互补品序贯拍卖模型,以期提出具有针对性的用地指标定价方法。研究表明,建设用地指标的成交价格受竞标人数和土地闲置费用的影响。竞标人指标报价随竞标人数递增而降低,但随土地闲置费递增而递增。进一步分析表明,适当提高土地闲置费用及资质审核要求可最大程度显化指标核心价值,激发农民退出闲置宅基地的积极性,提高农村用地的使用效率。研究为盘活农村闲置土地资产,实现可持续化发展给予了一定的理论参考。

面向多弹拦截的分布式非均衡一致性目标分配算法

针对自组网导弹集群协同拦截多无人机的不确定多对一目标分配问题,提出了一种分布式非均衡目标分配算法。考虑到自组网导弹在有限邻域范围内双向通信和任务分配的去中心化特点,设计了适合于分布式无中心的目标分配模型和基于动态态势感知的多步一致性拍卖算法,通过将目标剩余价值进行多步分解实现多弹对单一目标的非均衡拍卖选择;此外通过改进一致性包算法的共识规则设计了扩展多步一致性冲突消解规则,实现了分布式非均衡拍卖结果的一致性冲突消解。最终仿真结果表明,该方法可适用于分布式弹群在线非均衡目标分配调整,提高对空中多机动目标的拦截效率,并且相较于集中式分配算法在兼顾优化时间条件下可获得全局次优求解。

电力集合竞价交易环境下用户隐私保护方案研究

在电力集合竞价交易中,用户竞价信息存在被窃听或篡改等风险,这会导致用户隐私泄露,造成经济损失,影响交易系统的公平性和透明性,甚至会对电力系统的稳定运行造成影响。因此,确保用户安全地参与电力集合竞价交易成为亟待解决的问题。为此,提出了一种基于联盟链和无证书聚合签密的隐私保护方案。使用了假名技术,防止用户参与电力集合竞价交易市场时真实身份信息被泄露;使用了改进的无证书聚合签密和时释性加密算法,竞价信息通过加密后上传至联盟链,确保了竞价信息的安全;通过联盟链和智能合约实现了电力集合竞价交易市场的公平性和透明性,交易匹配结果通过共识后上传到联盟链,确保数据安全存储。性能分析和实验结果表明,本方案计算开销较低,同时满足交易系统所需的安全特性,适用于电力集合竞价交易环境。

连续竞价拍卖中羊群行为的驱动机理与逆向选择——基于阿里司法拍卖样本的实证研究

本文聚焦于在线拍卖的竞价行为,通过引入关联价值定义,深入研究了在线拍卖市场中理性与非理性羊群行为的微观发生机制,并运用变量加总的循环推导分析方法,构造出拍品在网络拍卖中的市场需求曲线,分解出羊群行为在资源配置中的规模效应与结构效应。研究发现,羊群行为不仅会提高拍品成交价格,更会对高质量买家产生一定的挤出效应。依据理论分析结果,以阿里司法拍卖实际竞价数据为样本的实证研究表明,连续竞价拍卖中的羊群行为具有一定的内生性,难以完全规避,而且羊群行为会导致在线拍卖市场出现一定的逆向选择问题。因此,要想做大做强中国在线拍卖市场,必须加大对羊群行为的监测、评估和治理,相关部门积极引导网拍平台发挥大数据优势,通过完善信用机制提高在线拍卖市场的有效竞争水平。