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.

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.

Directed Acyclic Graph Blockchain for Secure Spectrum Sharing and Energy Trading in Power IoT

Peer-to-peer(P2P)spectrum sharing and energy trading are promising solutions to locally satisfy spectrum and energy demands in power Internet of Things(IoT).However,implementation of largescale P2P spectrum sharing and energy trading confronts security and privacy challenges.In this paper,we exploit consortium blockchain and Directed Acyclic Graph(DAG)to propose a new secure and distributed spectrum sharing and energy trading framework in power IoT,named spectrum-energy chain,where a set of local aggregators(LAGs)cooperatively confirm the identity of the power devices by utilizing consortium blockchain,so as to form a main chain.Then,the local power devices verify spectrum and energy micro-transactions simultaneously but asynchronously to form local spectrum tangle and local energy tangle,respectively.Moreover,an iterative double auction based micro transactions scheme is designed to solve the spectrum and energy pricing and the amount of shared spectrum and energy among power devices.Security analysis and numerical results illustrate that the developed spectrum-energy chain and the designed iterative double auction based microtransactions scheme are secure and efficient for spectrum sharing and energy trading in power IoT.

Electricity-Heat-Based Integrated Demand Response Considering Double Auction Energy Market with Multi-Energy Storage for Interconnected Areas

With development of integrated energy systems and energy markets,transactive energy has received increasing attention from society and academia,and realization of energy distribution and integrated demand response through market transactions has become a current research hotspot.Research on optimized operation of a distributed energy station as a regional energy supply center is of great significance for improving flexibility and reliability of the system.Based on retail-side energy trading market,this study first establishes a framework of combined electric and heating energy markets and analyses a double auction market mechanism model of interconnected distributed energy stations.This study establishes a mechanism model of energy market participants,and establishes the electric heating combined market-clearing model to maximize global surplus considering multi-energy storage.Finally,in the case study,a typical user energy consumption scenario in winter is selected,showing market-clearing results and demand response effects on a typical day.Impact of transmission line constraints,energy supply equipment capacity,and other factors on clearing results and global surplus are compared and analyzed,verifying the effects of the proposed method on improving global surplus,enhancing interests of market participants and realizing coordination and optimal allocation of both supply and demand resources through energy complementarity between regions.

A Consortium Blockchain-enabled Double Auction Mechanism for Peer-to-peer Energy Trading among Prosumers

This paper investigates a double auction-based peer-to-peer(P2P)energy trading market for a community of renewable prosumers with private information on reservation price and quantity of energy to be traded.A novel competition padding auction(CPA)mechanism for P2P energy trading is proposed to address the budget deficit problem while holding the advantages of the widely-used Vickrey-Clarke-Groves mechanism.To illustrate the theoretical properties of the CPA mechanism,the sufficient conditions are identified for a truth-telling equilibrium with a budget surplus to exist,while further proving its asymptotical economic efficiency.In addition,the CPA mechanism is implemented through consortium blockchain smart contracts to create safer,faster,and larger P2P energy trading markets.The proposed mechanism is embedded into blockchain consensus protocols for high consensus efficiency,and the budget surplus of the CPA mechanism motivates the prosumers to manage the blockchain.Case studies are carried out to show the effectiveness of the proposed method.

Effect of Trader Composition on Stock Market

In this study, we build a double auction market model, which contains two types of agent traders, i.e., the noise traders and fundamentalists, to investigate the effect of the trader composition on the stock market. It is found that, the non-trivial Hurst exponent and the fat-tailed distribution of transaction prices can be observed at any ratio of the noise traders. Analyses on the price variation properties, including the Hurst exponent and the price variation region, show that these properties are stable when the ratio is moderate. However, the non-price variation properties, including the trading volume and the profitability of the two kinds of agents, do not keep stable untrivially in any interval of the ratio of noise traders.

Multi-objective resource optimization scheduling based on iterative double auction in cloud manufacturing

Cloud manufacturing is a new kind of networked manufacturing model.In this model,manufacturing resources are organized and used on demand as marketoriented services.These services are highly uncertain and focus on users.The information between service demanders and service providers is usually incomplete.These challenges make the resource scheduling more difficult.In this study,an iterative double auction mechanism is proposed based on game theory to balance the individual benefits.Resource demanders and providers act as buyers and sellers in the auction.Resource demanders offer a price according to the budget,the delivery time,preference,and the process of auction.Meanwhile,resource providers ask for a price according to the cost,maximum expected profit,optimal reservation price,and the process of auction.A honest quotation strategy is dominant for a participant in the auction.The mechanism is capable of guaranteeing the economic benefits among different participants in the market with incomplete information.Furthermore,the mechanism is helpful for preventing harmful market behaviors such as speculation,cheating,etc.Based on the iterative double auction mechanism,manufacturing resources are optimally allocated to users with consideration of multiple objectives.The auction mechanism is also incentive compatibility.

MARSHALLIAN DEVIATION:NEW OBSERVABLE CRITERION TO MEASURE TRANSACTION PATHS IN DOUBLE AUCTION MARKETS

In measuring the trade process in a double auction (DA) market, there is not any observable criterion that is able to describe the matching pairs and their transaction order dynamically. In this paper, we propose a new observable criterion called Marshallian deviation. It can be used to measure the distance of a transaction path deviating from the Marshallian path mathematically, and to answer the question why buyers with high values will trade with sellers with low costs in advance in some types of DA but not in others. Furthermore, three factors influencing the Marshallian deviations both in the CDA and in the PDA are also studied. They are respectively the strategic algorithm, the transaction duration and the number of traders. A few interesting findings are presented.

Pricing in combinatorial double auction-based grid allocation model

This article proposes a novel grid resource allocation model, in which the users and the grid service providers participate in the combinatorial double auction for the resource allocation. To obtain the detailed resource allocation status and the price information, a novel pricing algorithm is designed for the allocation model. Simulation results demonstrate that the proposed algorithm completes the resource allocation and pricing efficiently, and exhibits incentive compatible characteristic. Moreover, users with the higher average price and providers with the lower average price get compensation during the pricing process.

Agents learned,but do we?Knowledge discovery using the agent-based double auction markets

This paper demonstrates the potential role of autonomous agents in economic theory.We first dispatch autonomous agents,built by genetic programming,to double auction markets.We then study the bargaining strategies,discovered by them,and from there,an autonomous-agent-inspired economic theory with regard to the optimal procrastination is derived.

Analysis of Trading Volume Behavior Under Continuous Double Auction Mechanism in Limit Order Markets

In this paper, we develop a theoretical model to describe the dynamics of the trading volume under continuous double auction mechanism in limit order markets. We examine the formation process and statistical properties （including the mean, wriance, and realized value） of the buy side cumulative trading volume, sell side cumulative trading volume and total cumulative volume under continuous double auction mechanism by means of mathematical modeling based on Poisson process of order flows, and do some corresponding numerical simulations and comparative statics on the factors that would influence these three volumes aforementioned. The results indicate that these three volumes are all influenced by the factors including the arrival rate of orders, demands of each order, proportional structure between buy and sell orders, executed probability and time interval we examined. And our established theoretical model can well capture the dynamics of these three volumes under continuous double auction mechanism in limit order markets when all these factors interact.

Strategic Peer-to-peer Energy Trading Framework Considering Distribution Network Constraints

With the development of smart home energy management technology,prosumers are endowed with increased initiative in peer-to-peer(P2P)transactions,bringing new potential for cost savings.In this study,a novel strategic P2P energy trading framework is proposed considering the impact of network constraints on personal transaction strategies.Prosumers can estimate the allowed power injection before engaging in the P2P energy trading,which is solved in a distributed manner based on the sharing form alternating direction method of multipliers(ADMM)algorithm.To quantify the network usage cost for each prosumer and promote local transactions among prosumers at the same bus,a modified continuous double auction(CDA)matching algorithm is proposed including a transaction fee.An adaptive aggressiveness-based bidding strategy is generated considering the risk of uncertainty in real-time energy delivery amount under the limitations of the distribution network.The proposed strategic P2P energy trading framework is tested with the IEEE 37-bus distribution network and it is effective in creating profits for prosumers and supporting distribution network operations.