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.

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.

An Auction-Based Recommender System for Over-The-Top Platform

In this era of digital domination,it is fit to say that individuals are more inclined towards viewership on online platforms due to the wide variety and the scope of individual preferences it provides.In the past few years,there has been a massive growth in the popularity of Over-The-Top platforms,with an increasing number of consumers adapting to them.The Covid-19 pandemic has also caused the proliferation of these services as people are restricted to their homes.Consumers are often in a dilemma about which subscription plan to choose,and this iswhere a recommendation systemmakes their task easy.The Subscription recommendation system allows potential users to pick the most suitable and convenient plan for their daily consumption from diverse OTT platforms.The economic equilibrium behind allocating these resources follows a unique voting and bidding system propped by us in this paper.The systemis dependent on two types of individuals,type 1 seeking the recommendation plan,and type 2 suggesting it.In our study,the system collaborates with the latterwho participate in voting and invest/bid in the available options,keeping in mind the user preferences.This architecture runs on an interface where the candidates can login to participate at their convenience.As a result,selective participants are awarded monetary gains considering the rules of the suggested mechanism,and the most voted subscription plan gets recommended to the user.

CRAB—CombinatoRial Auction Body Software System

Auctions are important market mechanisms for the allocation of goods and services. Combinatorial auctions are those auctions in which buyers can place bids on combinations of items. Combinatorial auctions have many applications. The paper presents the CRAB software system. CRAB is a non-commercial software system for generating, solving, and testing of combinatorial auction problems. The system solves problems by Balas’ method or by the primal-dual algo-rithm. CRAB is implemented in Ruby and it is distributed as the file crab.rb. The system is freely available on web pag-es for all interested

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.

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%.

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。

AUCTIONING METHOD FOR AIRSPACE CONGESTING RESOURCE ALLOCATION AND GAME EQUILIBRIUM ANALYSIS

The airspace congestion is becoming more and more severe.Although there are traffic flow management（TFM）initiatives based on CDM widely applied,how to reschedule these disrupted flights of different airlines integrating TFM initiatives and allocate the limited airspace resources to these airlines equitably and efficiently is still a problem.The air traffic management（ATM）authority aims to minimizing the systemic costs of congested airspaces.And the airlines are self-interested and profit-oriented.Being incorporated into the collaborative decision making（CDM）process,the airlines can influence the rescheduling decisions to profit themselves.The airlines maybe hide the flight information that is disadvantageous to them,but is necessary to the optimal system decision.To realize the coincidence goal between the ATM authority and airlines for the efficient,and equitable allocation of airspace resources,this paper provides an auction-based market method to solve the congestion airspace problem under the pre-tactic and tactic stage of air traffic flow management.Through a simulation experiment,the rationing results show that the auction method can decrease the total delay costs of flights in the congested airspace compared with both the first schedule first service（FSFS）tactic and the ration by schedule（RBS）tactic.Finally,the analysis results indicate that if reallocate the charges from the auction to the airlines according to the proportion of their disrupted flights,the auction mechanism can allocate the airspace resource in economy equitably and decrease the delay losses of the airlines compared with the results of the FSFS tactic.

基于拍卖理论的动态多代理同类机调度算法

This paper addresses a multi-agent scheduling problem with uniform parallel machines owned by a resource agent and competing jobs with dynamic arrival times that belong to different consumer agents.All agents are self-interested and rational with the aim of maximizing their own objectives,resulting in intense resource competition among consumer agents and strategic behaviors of unwillingness to disclose private information.Within the context,a centralized scheduling approach is unfeasible,and a decentralized approach is considered to deal with the targeted problem.This study aims to generate a stable and collaborative solution with high social welfare while simultaneously accommodating consumer agents’preferences under incomplete information.For this purpose,a dynamic iterative auction-based approach based on a decentralized decision-making procedure is developed.In the proposed approach,a dynamic auction procedure is established for dynamic jobs participating in a realtime auction,and a straightforward and easy-to-implement bidding strategy without price is presented to reduce the complexity of bid determination.In addition,an adaptive Hungarian algorithm is applied to solve the winner determination problem efficiently.A theoretical analysis is conducted to prove that the proposed approach is individually rational and that the myopic bidding strategy is a weakly dominant strategy for consumer agents submitting bids.Extensive computational experiments demonstrate that the developed approach achieves high-quality solutions and exhibits considerable stability on largescale problems with numerous consumer agents and jobs.A further multi-agent scheduling problem considering multiple resource agents will be studied in future work.

基于碳绿证市场机制的多区域电力系统低碳调度模型

传统能源资源的有限性和供应安全问题促使人们转向能源互联和低碳电力的研究方向。综合能源系统(IES)逐渐成为实现能源协调和节能减排的关键手段。为了管理碳排放和促进可持续能源的利用,文章提出了一种基于碳绿色证书联合市场的多区域综合能源系统调度模型。监管部门对碳排放量进行分配调整,可分别在碳交易系统和绿证市场系统两个渠道进行交换。评估了在IES中引入碳绿色证书市场机制的可行性,并提出了绿色证书联合市场框架。采用组合双拍卖(CDA)机制进行竞价,确定绿色证书的最佳价格,建立了供热网络和天然气网络的优化模型,并将其与IES的约束相结合,确保系统的稳定运行。该模型分析了碳交易系统、绿证市场系统以及天然气价格的变化对系统运行成本的影响。仿真实验结果表明,该模型能够显著提高IES效益并降低碳排放。

基于CPN模型Auction智能合约的形式化验证

区块链智能合约是运行在区块链网络中的代码,它能够根据外部环境条件自动执行相应的规则,完成对应的交易和数字资产的转移.Auction合约是一个公开拍卖的智能合约,广泛应用到竞拍、游戏和博彩等行业,吸引了众多用户参与.近年来,该合约暴露出了拒绝服务攻击漏洞,导致很多参与者无法竞拍成功.为此,本文基于CPN模型对Auction合约进行形式化验证,检测漏洞并确定漏洞位置.首先使用CPN中的建模工具分别对Auction合约整体、无攻击操作和有攻击操作进行建模,然后使用CPN中的仿真工具对合约的执行过程进行仿真.结果表明,通过该方法,不仅可以发现和定位Auction合约的逻辑漏洞,而且也可以发现Auction合约语言的局限性.

最短路径Auction算法及其在路径诱导中的应用

通过采用C#语言程序,对比传统路径算法,并在实际道路网络和随机网络中进行了试验,测试了算法在求解网络"一对一"最短路径问题时的运算性能.结果表明,Auction算法在求解此类问题时,体现算法自身原理的优势,虽然整体性能表现不及经典的路径算法,即迭代步骤略多,但仍有改进的余地.

最短路问题的Auction算法在无圈网络中的改进

提出了Auction算法在无圈网络中的一种改进。在改进的新算法中,采取了新的推进(extension)方式,从而成功地降低了算法的复杂性。改进后算法的复杂性为O(m),此处m是图的弧数。

绿氢标准、融资体系及中欧氢能合作路径分析

欧美国家相继出台绿氢定义标准和草案,但全球范围内绿氢定义、范围要求、标准要求尚未达成共识,对未来开展跨国绿氢项目投融资和贸易带来一定阻力。欧盟是该领域的先行者,2023年率先成立了欧洲氢能银行,以刺激和支持本土氢能产业发展。其设立初衷是帮助欧盟更好应对氢能项目发展初期的投资缺口,设计了4项功能机制:释放欧盟及第三国对氢能的投资(拍卖即服务)、扩大氢能进口、整合氢能融资政策、提升融资工具的协调性和效率。绿氢的碳属性和交易属性是支撑欧洲开展绿氢交易的关键依据和重要基础。全球碳中和大势下,氢能已日渐成为未来国际经济合作的重要领域,有望成为打造中欧能源绿色合作伙伴关系的新增长点。为此建议,加强绿氢标准合作和协调,推动国际互认和互用;多形式参与欧洲氢能银行合作,推动项目合作共建;加速建立全球氢能市场,开辟新型能源贸易关系;建立中国特色的氢能投资银行,整合现有金融资源。

Commission Strategy of the Auction House

In a SIPV model, when the commission proportion is not certain, but related with bargain price, generally, it is a linear function of the bargain price, this paper gives bidders＇ equilibrium bidding strategies in the first-and secondprice auctions. We find that the equilibrium strategies in second-price auction are dominant strategies. For seller or auction house, whether the fixed proportion or the unfixed proportion is good is not only related with constant item and the linear coefficient of the linear function, the size of the fixed commission proportion, but also related with the value of the item auctioned. So, in the practical auctions, the seller and the auction house negotiated with each other to decide the commission rules for their own advantage.

Quantum Secure Direct Communication and Quantum Sealed-Bid Auction with EPR Pairs

I present a new protocol for three-party quantum secure direct communication （QSDC） with a set of ordered M Einstein-Podolsky-Rosen （EPR） pairs. In the scheme, by performing two unitary operations and Bell state measurements, it is shown that the three legitimate parties can exchange their respective secret message simultaneously. Then I modify it for an experimentally feasible and secure quantum sealed-bid auction （QSBD） protocol. Furthermore, I also analyze th^ecurity of the protocol, and the scheme is proven to be secure against the intercept-and-resend attack, the disturbancb attack and the entangled-and-measure attack.

Multi-band spectrum auction framework based on location information in cognitive radio networks

Cognitive radio（CR） technology is considered to be an effective solution to allocate spectrum resources,whereas the primary users of a network do not fully utilize available frequency bands.Spectrum auction framework has been recognized as an effective way to achieve dynamic spectrum access.From the perspective of spectrum auction,multi-band multi-user auction provides a new challenge for spectrum management.This paper proposes an auction framework based on location information for multi-band multi-user spectrum allocation.The performance of the proposed framework is compared with that of traditional auction framework based on a binary interference model as a benchmark.Simulation results show that primary users will obtain more total system revenue by selling their idle frequency bands to secondary users and the spectrum utilization of the proposed framework is more effective and fairer.

Joint wireless and cloud resource allocation based on parallel auction for mobile edge computing

A joint resource allocation algorithm based on parallel auction(JRAPA)is proposed for mobile edge computing(MEC).In JRAPA,the joint allocation of wireless and cloud resources is modeled as an auction process,aiming at maximizing the utilities of service providers(SPs)and satisfying the delay requirements of mobile terminals(MTs).The auction process consists of the bidding submission,winner determination and pricing stages.At the bidding submission stage,the MTs take available resources from SPs and distance factors into account to decide the bidding priority,thereby reducing the processing delay and improving the successful trades rate.A resource constrained utility ranking(RCUR)algorithm is put forward at the winner determination stage to determine the winners and losers so as to maximize the utilities of SPs.At the pricing stage,the sealed second-price rule is adopted to ensure the independence between the price paid by the buyer and its own bid.The simulation results show that the proposed JRAPA algorithm outperforms other existing algorithms in terms of the convergence rate and the number of successful trades rate.Moreover,it can not only achieve a larger average utility of SPs but also significantly reduce the average delay of MTs.

A secure spectrum auction scheme without the trusted party based on the smart contract

With the development of communication 5G networks and technologies,spectrum resources are increasingly scarce.The scarcity of the spectrum resource makes market-driven spectrum auction become an important means of spectrum allocation,and due to the complexity of the network environment,the security of spectrum auctions can not be ignored.Most existing secure spectrum auction schemes introduce a semi-honest agent to complete spectrum auction.However,the hypothetical semi-honest model does not guarantee the security of spectnim auction in the actual application scenario,which may lead to potential security threats:the agent may reveal the privacy of bidders,agent or auctioneer may collude with the bidder to manipulate the spectrum auction,and so on.In this paper,a secure spectrum auction scheme without a trusted party is proposed based on the smart contract technology,and the smart contract written into the blockchain replaces the traditional semi-honest agent to cooperate with the auctioneer server to complete the auction.In order to ensure the security of our scheme,a secure spectrum auction protocol is designed,in which the Software Guard Extensions(SGX)technology and Paillier cryptosystem are used to protect the privacy of bidders.Public verification is provided in our protocol by using extensive Pedersen commitment,which prevents the auctioneer server and the bidder from colluding with each other and verifies group bid sum values.Finally,the security analysis is given to propose several types of attacks that can be defended.Besides,theoretical analysis and simulation experiments of our protocol are also provided.

基于线性波门改进拍卖算法的航迹关联算法研究

针对分布式探测系统中多源传感器航迹关联问题,常用的基于距离统计构建关联代价矩阵,拍卖算法求解关联结果的流程在面临探测区域中目标数量大,目标航迹分布密集的场景时,会出现关联准确率下降及关联时间长的问题。提出了一种基于线性波门改进的拍卖算法来改进现有关联算法在面临上述场景时的关联性能。考虑传感器的测量偏差对距传感器远的目标航迹数据影响大于距离近的目标,因此设计了与距离有关的线性波门对可能关联的目标航迹筛选。仿真数据结果表明,提出的线性波门能够对传统拍卖算法在大批次目标下提升关联准确率和降低关联时间,证明了线性波门的有效性,对实际多源传感器航迹关联问题具有重要意义。