Learning-Based Auction for Matching Demand and Supply of Holographic Digital Twin Over Immersive Communications

计算机科学 强化学习 匹配(统计) 多媒体 分布式计算 人工智能 数学 统计
作者
XiuYu Zhang,Minrui Xu,Rui Tan,Dusit Niyato
出处
期刊:IEEE Transactions on Multimedia [Institute of Electrical and Electronics Engineers]
卷期号:26: 5884-5896
标识
DOI:10.1109/tmm.2023.3340548
摘要

Digital Twin (DT) technologies create digital models of physical entities frequently in multimedia forms, which are crucial for concurrent simulation and analysis of real-world systems. In displaying DTs, Holographic-Type Communication (HTC) provides immersive multimedia access for users to interact with Holographic DTs (HDTs) by transmitting holographic data such as Light Field (LF) and other multisensory information. HDT has applications in remote education, work, and social interactions. However, the effective matching of demand and supply between HDT users and providers remains a challenge. To address this issue, we propose a hierarchical architecture that integrates the DT and HTC paradigms. This architecture incorporates a marketplace for HDT services, leveraging a formulated Double Dutch Auction (DDA) mechanism to optimize matching and pricing based on user and provider valuation. Furthermore, We employ an actor-critic-based Deep Reinforcement Learning (DRL) algorithm to train a DDA auctioneer that dynamically adjusts auction clocks during the auction process. As an alternative to the Multi-layer Perceptron (MLP), we experiment with a Deep Simplistic Variational Quantum Circuit (DSVQC) to reduce the number of parameters and enhance performance stability. Our simulations reveal that the proposed learning-based auctioneer achieves 92% optimal social welfare at a 37% auction information exchange cost for an MLP-based actor and 99% optimal social welfare at a 77% auction information exchange cost for a DSVQC-based actor.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
更新
PDF的下载单位、IP信息已删除 (2025-6-4)

科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
Chem34完成签到,获得积分10
7秒前
9秒前
量子星尘发布了新的文献求助10
9秒前
hhh2018687完成签到,获得积分10
9秒前
9秒前
10秒前
10秒前
10秒前
10秒前
11秒前
11秒前
11秒前
11秒前
11秒前
11秒前
11秒前
嘒彼小星完成签到 ,获得积分10
11秒前
11秒前
12秒前
12秒前
12秒前
12秒前
13秒前
ri_290完成签到,获得积分10
13秒前
14秒前
nsc发布了新的文献求助30
16秒前
nsc发布了新的文献求助10
16秒前
nsc发布了新的文献求助10
16秒前
nsc发布了新的文献求助10
16秒前
nsc发布了新的文献求助10
16秒前
nsc发布了新的文献求助10
16秒前
nsc发布了新的文献求助10
16秒前
nsc发布了新的文献求助10
16秒前
nsc发布了新的文献求助10
16秒前
nsc发布了新的文献求助10
16秒前
nsc发布了新的文献求助10
16秒前
nsc发布了新的文献求助10
16秒前
nsc发布了新的文献求助30
16秒前
nsc发布了新的文献求助10
16秒前
nsc发布了新的文献求助10
16秒前
高分求助中
【提示信息,请勿应助】关于scihub 10000
Les Mantodea de Guyane: Insecta, Polyneoptera [The Mantids of French Guiana] 3000
徐淮辽南地区新元古代叠层石及生物地层 3000
The Mother of All Tableaux: Order, Equivalence, and Geometry in the Large-scale Structure of Optimality Theory 3000
Handbook of Industrial Diamonds.Vol2 1100
Global Eyelash Assessment scale (GEA) 1000
Picture Books with Same-sex Parented Families: Unintentional Censorship 550
热门求助领域 (近24小时)
化学 材料科学 医学 生物 工程类 有机化学 生物化学 物理 内科学 纳米技术 计算机科学 化学工程 复合材料 遗传学 基因 物理化学 催化作用 冶金 细胞生物学 免疫学
热门帖子
关注 科研通微信公众号,转发送积分 4038039
求助须知:如何正确求助?哪些是违规求助? 3575756
关于积分的说明 11373782
捐赠科研通 3305574
什么是DOI,文献DOI怎么找? 1819239
邀请新用户注册赠送积分活动 892655
科研通“疑难数据库(出版商)”最低求助积分说明 815022