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.

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

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。

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.

Secure Power and Subcarrier Auction in Uplink FullDuplex Cellular Networks

We consider a cellular network with a full-duplex base station, multiple uplink users and an eavesdropper. The full-duplex base station transmits jamming signals to degrade the eavesdropper channel when receiving secure multi-user signals. To maximize the secrecy rate of uplink communications, we propose a distributed ascending-clock auction(ACA) algorithm to allocate subcarriers and jamming power. Specifically, the impact of the self-interference of the full-duplex base station on the secrecy rate is considered. The proposed algorithm consists of two parts. Firstly, subcarriers and the jamming power are respectively priced by the base station. Secondly, users select the subcarrier and the jamming power based on the price. Moreover, the convergence of the proposed auction algorithm is mathematically proved. Simulation results show that the proposed auction algorithm is more beneficial to improve the uplink secrecy performance compared to traditional auction algorithms.

UNIFORM-PRICE AUCTION FOR BANDWIDTH ALLOCATION IN THE INTERNET

It has been widely accepted that auctioning which is the pricing approach with minimal information requirement is a proper tool to manage scare network resources. Previous works focus on Vickrey auction which is incentive compatible in classic auction theory. In the beginning of this letter, the faults of the most representative auction-based mechanisms are discussed. And then a new method called Uniform-Price Auction (UPA), which has the simplest auction rule is proposed and its incentive compatibility in the network environment is also proved. Finally, the basic mode is extended to support applications which require minimum bandwidth guarantees for a given time period by introducing derivative market, and a market mechanism for network resource allocation which is predictable, riskless, and simple for end-users is completed.

Genetic Algorithm Based Combinatorial Auction Method for Multi-Robot Task Allocation

An improved genetic algorithm is proposed to solve the problem of bad real-time performance or inability to get a global optimal/better solution when applying single-item auction （SIA） method or combinatorial auction method to multi-robot task allocation. The genetic algorithm based combinatorial auction （GACA） method which combines the basic-genetic algorithm with a new concept of ringed chromosome is used to solve the winner determination problem （WDP） of combinatorial auction. The simulation experiments are conducted in OpenSim, a multi-robot simulator. The results show that GACA can get a satisfying solution in a reasonable shot time, and compared with SIA or parthenogenesis algorithm combinatorial auction （PGACA） method, it is the simplest and has higher search efficiency, also, GACA can get a global better/optimal solution and satisfy the high real-time requirement of multi-robot task allocation.

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.

Negotiation Based Combinatorial Double Auction Mechanism in Cloud Computing

Cloud computing is a demanding business platform for services related to the field of IT.The goal of cloud customers is to access resources at a sustainable price,while the goal of cloud suppliers is to maximize their services utilization.Previously,the customers would bid for every single resource type,which was a limitation of cloud resources allocation.To solve these issues,researchers have focused on a combinatorial auction in which the resources are offered by the providers in bundles so that the user bids for their required bundle.Still,in this allocation mechanism,some drawbacks need to be tackled,such as due to the lower average bid price the users are dropped from the auction process.To solve this problem,we proposed a“Negotiation based Combinatorial Double Auction Mechanism for Resource Allocation(N-CDARA)in cloud computing”.The proposed method negotiates with dropped users.Lower average bid price users are asked by our proposed mechanism to increase their bids,as by the quoted bids they will be dropped by the auctioneer.Most of the users that are close to winning accept the proposal and increase their bid prices.The proposed mechanism is implemented in a CloudSim simulation toolkit.Results are compared with the latest model and performance study shows that in our proposed scheme more users win and get their requested services and the utilization of offered services is increased up to 18.4%than the existing schemes.

Auction mechanism design of the Chinese national carbon market for carbon neutralization

The carbon market auction mechanism is an important policy tool for carbon pricing and a key mechanism that supports carbon emission neutralization,especially for China.A few systematic studies exist on China’s carbon market auction mechanism.This article focuses on the five auction mechanisms in Chinese pilot emission trading schemes(ETS),reviews the structures and bidding situation of the five-pilot auction mechanism,extracts the similarities,and analyzes their different features,such as auction mode,bidding scale,participants,pricing mode,auction frequency,and so on.This study conducts an in-depth analysis of the carbon allowance auction mechanism in the Guangdong pilot ETS of China,including its development and the evolution of the key elements,its operational effects,and related disputes.Finally,this study puts forward the trend forecast and suggestions for the Chinese allowance auction mechanism,such as the time window of launching national allowance auctions,the most likely auction mode,carbon pricing,and bidding revenue management.Carbon pricing by auction is the most powerful policy tool for addressing carbon emissions reduction and implementing the Glasgow Climate Pact.

Real-time Business Network Selection Based on Auction Mechanism

In the framework of heterogeneous wireless networks,it is difficult for every user to obtain QoS-based services anywhere at any time.Due to heterogeneous networks,the dynamic network selection scheme needs to achieve seamless mobility,and also supports the optimization of service quality and load balancing.According to different business characteristics,this paper describes different real-time businesses in utility functions,and solves network selection problems for real-time businesses.Based on auction mechanism,it introduces the upset price in order to maximize online profits.Meanwhile,the network selection scheme is also helpful to control network congestion.The study of real-time business network selection based on auction mechanism can not only meet the demands of service quality of multiple realtime applications,but also achieves load balancing between different networks.

Improving the secrecy rate by turning foes to allies:An auction scheme

Security against eavesdroppers is a critical issue in cognitive radio networks（CRNs）. In this paper, a scenario consisting of one primary pair and multiple secondary pairs is considered. The secondary transmitters（STs） work in half-duplex mode and they are potential eavesdroppers on the primary transmission unless they are allowed to simultaneously transmit with the primary transmitter（PT）. A modified second-price sealed-bid auction scheme is employed to model the interaction between the PT and STs. With the proposed auction scheme, the hostile relationship between the PT and STs is transformed into a cooperative relationship. An iterative algorithm based on the max–min criteria is proposed to find the optimal bidding power of the STs for an access chance in the presence of multiple eavesdroppers. Numerical results show that the proposed auction scheme not only improves the PT＇s security but also increases the access opportunities of the STs.