Evolution and Outlook of Resource Allocation Mechanism in the Age of Internet

In today's society, the Internet, big data and artificial intelligence are being integrated and the mechanisms of resource allocations are also evolving, mainly because of the changes in background factors, means, and processes that influence resource allocation. To analyze and study this evolution, we need to combine resource allocation, industrial organization, and industrial regulation theories to determine the driving and restricting factors new technologies bring to business-to-business and business-to-consumer interactions and how the combination of internet, big data and AI will impact productivity and pricing. We must also analyze the differences between today's supply-demand and pricing processes and those of the industrial age to discover whether there are special resource allocation mechanisms in this era and how to summarize them theoretically. This paper reviews the evolved resource allocation mechanisms at the present stage of the integration of the Internet, big data and AI based on resource allocation theories from classical Marxian, neoclassical, and modern western economics.

Contract theory based incentive mechanism design for buffer resource in wireless caching networks

Evidences indicate that,due to the limited caching capacity or inaccurate estimation on users’preferences,the requested files may not be fully cached in the network edge.The transmissions of the un-cached files will also lead to duplicated transmissions on backhaul channels.Buffer-aided relay has been proposed to improve the transmission performance of the un-cached files.Because of the limited buffer capacity and the information asymmetric environment,how to allocate the limited buffer capacity and how to incentivize users in participating buffer-aided relay have become critical issues.In this work,an incentive scheme based on the contract theory is proposed.Specifically,the backlog violation probability,i.e.,the buffer overflow probability,is provided based on the martingale theory.Next,based on the backlog violation probability,the utility functions of the relay node and users are constructed.With the purpose to maximize the utility of the relay node,the optimal contract problem is formulated.Then,the feasibility of the contract is also demonstrated,and the optimal solution can be obtained by the interior point method.Finally,numerical results are presented to demonstrate effectiveness of the proposed contract theory scheme.

Two-Step Resource Block Allocation Algorithm for Data Rate Maximization in LTE Downlink Systems

This study focuses on resource block allocation issue in the downlink transmission systems of the Long Term Evolution (LTE). In existing LTE standards, all Allocation Units (AUs) allocated to any user must adopt the same Modulation and Coding Scheme (MCS), which is determined by the AU with the worst channel condition. Despite its simplicity, this strategy incurs significant performance degradation since the achievable system throughput is limited by the AUs having the worst channel quality. To address this issue, a two-step resource block allocation algorithm is proposed in this paper. The algorithm first allocates AUs to each user according to the users' priorities and the number of their required AUs. Then, a re-allocation mechanism is introduced. Specifically, for any given user, the AUs with the worst channel condition are removed. In this manner, the users may adopt a higher MCS level, and the achievable data rate can be increased. Finally, all the unallocated AUs are assigned among users without changing the chosen MCSs, and the total throughput of the system is further enhanced. Simulation results show that thanks to the proposed algorithm, the system gains higher throughput without adding too many?complexities.

Adaptive computational resource allocation for sensor networks

To efficiently utilize the limited computational resource in real-time sensor networks, this paper focuses on the challenge of computational resource allocation in sensor networks and provides a solution with the method of economics. It designs a microeconomic system in which the applications distribute their computational resource consumption across sensor networks by virtue of mobile agent. Further, it proposes the market-based computational resource allocation policy named MCRA which satisfies the uniform consumption of computational energy in network and the optimal division of the single computational capacity for multiple tasks. The simulation in the scenario of target tracing demonstrates that MCRA realizes an efficient allocation of computational resources according to the priority of tasks, achieves the superior allocation performance and equilibrium performance compared to traditional allocation policies, and ultimately prolongs the system lifetime.

Establish the Long-effective Mechanism of Food Security in China

In despite of fluctuation in recent years, the grain yield in China has been increasing, which relieves the conflict between supply and demand and turns the situation of food security good. However, because of the rapid increase in food consumption, the conflicts of food quality and structure in the supply and demand equilibrium has become more and more obvious and the long-effective mechanism of food security has not been estab-lished yet. It is found that the factors affecting food security in China include the scarcity and dissipation of resources, farmers’ low enthusiasm in planting grain crops and the inappropriateness of the emphasis and measures of macro-economic regulation and control. Therefore, the authors advance to optimize resources allocation, strengthen macro-economic regulation and control and policy stimulation and establish the mechanism of allocating grain production cost, to set up the long-effective mechanism of China food security and keep it stable in the long term.

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.

A self-adaptive Model based on Multi-Objective Programming for Grid Resource Management

The growing computational power requirements of grand challenge applications have positioned computational grid as promising next generation computing platform. However, resource management and application with varied requirements in grid environment continue to be a complex undertaking. In order to address complex resource management issues, we provide a self-adaptive model, which is based on multi-objective programming. The model make use of virtues of market mechanism efficiently, meanwhile, the shortcomings of market mechanism, such as too frequent fluctuations of price, are avoided by means of the method of changing prices after trading. Through using atom allocation of resource group, the cooperating allocation is improved, and some problems, such as deadlock of resource and inefficiently occupying resource, are solved. What's more important, efficiently using various resources in grid system is guaranteed through importing multi-objective programming mechanism in our resource management solution. A frame of resource allocation is given at first, then, the mathematical model of the method is constructed. An algorithm is proposed to get the approximate solution in this paper.

黑龙江省农业科研院所协同发展背景下农机农艺融合机制研究

通过对黑龙江省农业科研院所协同发展的农机农艺融合研究,分析了农机农艺融合的理论和农机农艺融合的重要性,阐述了农机农艺融合机制的现状。通过查阅资料和调查研究方法,详细提出黑龙江省农业科研院所协同发展中,农机农艺融合机制有待加强,资源配置能力不够高,优秀人才紧缺、管理机制不完善政策扶持不足和缺乏长期规划的问题。并提出加强完善合作机制,提高资源配置能力,加强人才培养,建立灵活的管理机制的对策和建议,有助于实现农业生产的高效、优质、可持续发展。

“十五五”时期充分发挥市场在资源配置中的决定性作用研究

面向“十五五”时期,充分发挥市场在资源配置中的决定性作用,应围绕社会经济活动、要素配置层次、社会主义经济制度三个维度,以及竞争性效率和帕累托效率两个效率视角,来理解其理论逻辑。要从“十五五”我国处于加快推进基本实现社会主义现代化的关键期,加快构建新发展格局着力推动高质量发展的攻坚期,推进国家治理体系和治理能力现代化的突破期,工业化、城镇化、信息化和农业现代化“四化同步”的加速期以及全面实施高水平制度型开放的窗口期几个层面,来把握充分发挥市场在资源配置中的决定性作用的重大意义。应通过重大改革举措和体制机制创新,充分发挥市场在资源配置中的决定性作用:以实现中国特色社会主义市场经济体制更加成熟更加定型为重点,加快优化市场经济基础制度;以破除传统要素自由流动堵点和建立新型要素市场规则为重点,全面推动要素市场化配置改革;以服务国家重大战略和破除发展的突出矛盾和明显短板为重点,积极健全重点领域的市场机制;以全面推进实现国家治理体系和治理能力现代化为重点,持续完善国家宏观经济治理体系;以对接高标准国际经贸规则和“边境后”规则适应性调整为重点,强化与制度型开放联动推进市场化改革。

基于5G技术的舰船电力调度自动化系统研究

考虑舰船电力系统线路复杂、设备多样,调度数据冗杂且规模巨大,在此情况下为实现舰船电力系统快速、有效自动化调度,设计基于5G技术的舰船电力调度自动化系统。系统使用由RTU远动终端设备采集电力系统的线路、设备运行信息后,由5G通信网关发送至调度器;调度器结合目前电力系统运行信息,使用基于线性求解器的电力系统自动化调度模型,构建以快速实现断电负载故障合理恢复为调度目标的目标函数,由线性求解器自动化求解满足目标函数条件的电力系统开关动作方案,以故障重构的方式实现舰船电力调度自动化管理。实验中该系统调度下,舰船电力系统失电负荷为0 kW,5G通信网络的整体效用值不受调度数据业务数据包数量的约束,高达0.9,能够稳定、高效地支持大规模调度数据的传输。

智慧校园学习环境信息服务资源配置与共享机制研究

随着信息技术的快速进步,智慧校园的构建已成为推进教育现代化的重要途径。本文的主要目标在于研究智慧校园学习环境中信息服务资源的合理配置和共享机制,以提升学习效率、优化教育资源的利用,同时推动学生综合素质的全面提升。通过对智慧校园的背景和发展现状进行深入研究,结合信息技术和教育理论,本文提出了有效的资源配置策略和共享机制,旨在为智慧校园的建设提供有益的指导和启示。

数字经济对乡村医疗资源配置效率的影响

数字经济的蓬勃发展为传统产业创新发展注入了强大动力,数字医疗便是其中之一。从数字产业化和产业数字化两个维度构建了数字经济发展综合指数,采用DEA-Malmquist指数分别测算乡镇卫生院和村卫生室医疗资源配置效率,基于2011—2021年中国29个省份的面板数据,实证分析了数字经济对乡村医疗资源配置效率的影响。研究发现:数字经济显著促进了乡镇卫生院医疗资源配置效率的提升,但对村卫生室医疗资源配置效率的提升不显著;数字经济对城镇化发展水平高和医疗财政投入高的地区的乡镇卫生院医疗资源配置效率的提升作用更大;就机制而言,产业结构升级和技术创新是数字经济影响乡镇卫生院医疗资源配置效率的两个渠道。研究结论为乡村医疗资源配置效率的提升提供了一个新视角。

中国式现代化视域下基础教育综合改革的时代特征、现实挑战与未来路向

基础教育综合改革是全面深化改革、推进中国式现代化的关键环节。在党的二十届三中全会精神指引下,基础教育综合改革在中国式现代化的战略布局中凸显出系统性与整体性、质量导向与内涵发展、均衡性与公平性、数智性与开放性、创新性与自主性的时代特征。随着中国式现代化的加速推进和社会对教育需求的多元化演变,基础教育综合改革面临着一系列现实挑战,主要包括教育资源配置的均衡、教育评价机制的创新、教师队伍建设的优化、教育管理体系的完善以及数智化与教育的深度融合。面向未来,中国式现代化视域下的基础教育综合改革应坚定不移地以立德树人为根本任务,优化教育资源配置,革新教育评价体系,强化师资队伍建设,构建科学高效的现代治理体系,不断完善数智教育支撑体系,为培养具备社会责任感、卓越创新精神与实践能力的高素质人才奠定坚实的基础。

高师院校与地方基础教育合作困境及改进

高师院校与地方基础教育的合作模式对于提高教育质量、培养人才具有重要意义。双方合作模式多样,取得了较大的成绩和进步,但依然存在资源分配不均、教育理念与实践差异较大、沟通与协调困难、教学模式与需求脱节等现实困境。这就需要高师院校与地方基础教育进一步加强合作,建立长期稳定的合作机制,共同开展师资培训、课程设计和教学研究等活动,并逐步优化地方基础教育的资源配置,进而提升地方基础教育的整体水平。

中国水资源配置“两手发力”的实现路径——再论“三权分置”水权制度改革

推动政府和市场两手协同发力,是新时期治水面临的重大课题。在水资源配置中引入市场机制存在多种途径和形式,其中建立水权市场需要满足一系列精细苛刻的条件,加之中国独特的国情因素,在我国建立一套有效运行的水权市场成本很高。回顾2000年以来的实践,我国水权市场改革面临过程曲折、市场规模较小、市场收益有限、制度问题凸显等困境,一定程度上印证了有关理论认识。我国未来可以继续推进水权市场改革,但不宜将一套系统完整的水权市场作为改革目标。为了解决我国水权市场改革面临的困境,更好地利用水权政策工具服务“两手发力”,借鉴我国农村土地“三权分置”改革经验,提出“三权分置”的水权制度设计,将水资源的所有权、取水权和使用权三项权利分置,并阐述了具体改革思路及其价值。

新质生产力发展与土地资源配置:历史逻辑、理论逻辑与现实逻辑

研究目的:系统阐释新质生产力发展与土地资源配置的历史逻辑、理论逻辑与现实逻辑,为新形势下土地资源优化配置提供有益参考。研究方法:逻辑推理法与归纳总结法。研究结果:(1)土地资源是构成生产力的基本要素,其性质作用顺应文明演进日益拓展,土地资源配置与生产力发展存在与时俱进的历史逻辑,并与生产关系变革密切相关。(2)着眼学理基础,土地资源配置可通过高效竞争、有序管制、均衡协同、公平分配和智能决策等途径助力新质生产力的发展,并可归纳为市场、政府、统筹、共享、涌现5项理论逻辑。(3)立足现实问题,新质生产力发展与土地资源配置既具有双向赋能的共促逻辑,也需遵循因地制宜的差别逻辑、动态推演的前瞻逻辑和筑牢底线的安全逻辑。研究结论:土地资源配置与新质生产力发展是一对相互促进的孪生体,二者的历史、理论和实践逻辑会随着生产力发展而发生转换,未来仍需持续优化土地资源配置、深化土地制度改革,以更好服务于新质生产力的价值取向。

我国养老服务资源配置机制研究

本文基于整合照料理论,从需求侧和供给侧出发,以老年群体对养老服务资源配置的主观意愿为出发点,结合近年来社会养老服务体系的政策走向和各地对机构、社区、居家养老服务协调发展的创新实践,尝试构建本土化的养老服务资源配置机制模型。在政策上,养老服务资源配置发展思路从“板块式”转向“协调式”;在实践上,北京、上海等地探索出养老服务资源机制协调与服务协调的实践经验。该模型包括资源供给层、资源配置层和资源接收层,资源供给层强调将政府、市场、社会养老服务资源下沉至家庭“最后一公里”;资源配置层包括资源配置模式和资源配置载体两大维度;资源接收层以老年群体为核心,共同为老年人提供综合连续、方便可及的服务。

基于DRL的边缘监控任务卸载与资源分配算法

为解决边缘计算环境下密集型监控任务资源受限的问题,提出一种基于DRL的监控任务卸载与资源分配算法。以监控任务时延和识别精度为优化目标,将监控系统中的任务卸载、无线信道分配和图像压缩率的联合决策目标优化求解建模为马尔可夫决策过程;针对无线信道动态性和监控任务随机性引起的训练样本波动性较大,导致算法收敛速度慢和不稳定,采用Transformer注意力机制对多时隙序列的信道状态和监控任务信息进行联合编码。编码后的状态信息能够捕捉多时隙状态序列之间的依赖关系,提升网络状态的表征能力,并以此提高算法鲁棒性。实验结果表明:与传统强化学习算法和启发式算法相比,该算法在降低任务计算时延的同时能够有效提高识别精度。

基于NUMA云计算架构的多资源分配可信拍卖机制

随着互联网不断发展,云计算和虚拟化等技术广泛投入使用,设计可信拍卖机制为云服务商进行社会福利最大化的虚拟资源分配,是当前云计算领域的研究重点之一。同时,随着服务器规模不断扩展,诸多主流数据中心的服务器正在升级为非统一性内存访问NUMA架构,其主要特征为,每台服务器可由多个计算节点构成,每个节点包含若干处理器和存储器,既可作为独立计算单元,也可以相互连通访问。但是,当前的研究主要着眼于传统的统一性内存访问架构,无法适应NUMA架构下的应用场景。因此,提出了一种适用于NUMA架构下的多资源可信拍卖机制,以虚拟机的形式进行多种资源的组合分配。具体而言,在资源分配问题中,提出一种单调启发式分配算法,考虑了NUMA架构下的部署约束和资源优势密度等因素,有效提升了社会福利。在价格支付问题中,使用二分法设计一种符合关键价格理论的定价支付算法,从而保证机制的可信特征。经过实验测试,该机制在社会福利、用户支付费用和资源利用率等方面,整体性能达到最优解的96%左右。

面向非完全电磁信息的智能频谱分配技术研究

针对电磁对抗过程中环境动态变化,多节点自主用频决策频谱利用率低的问题,该文开展面向非完全电磁信息的智能协同频谱分配技术研究,通过多节点智能协同提升频谱利用率。首先将复杂电磁环境频谱分配问题建模为最大化用频设备的优化问题,其次提出一种基于多节点协同分流经验回放机制的资源决策算法(CoDDQN),算法基于协同分流函数对历史经验数据进行评估,并通过分级经验池进行训练,使各智能体在仅观测自身状态信息条件下形成轻量级协同决策能力,解决低视度条件下多节点决策优化方向与整体优化目标不一致的问题,提升频谱利用率;设计了一种基于置信分配的混合奖励函数,各节点决策兼顾个体的奖励,能够减少惰性节点的出现,探索更优的整体动作策略,进一步提升系统效益。仿真结果表明:当节点数为20时,所提算法的可接入设备数优于全局贪婪算法与遗传算法,并与信息完全共享的集中式频谱分配算法的差距在5%内,更适用于低视度节点的协同频谱分配。