Online combinatorial based mechanism for MEC network resource allocation

In this paper, the resource allocation problem for mobile edge computing (MEC) network is discussed. We focus on the design of online resource allocation strategy by considering the time‐varying demands of the combinatorial resources for the mobile users. To handle this issue, at first, a time splitting‐based online allocation mechanism is introduced. Then, for a given resource allocation period of the time splitting, a combinatorial auction mechanism for the combination resources allocation is proposed. We further prove that the proposed combinatorial auction is both individual rational and incentive‐compatible, and which can bring a higher revenue to the service provider. In order to verify the performance of the proposed mechanism, a variable‐relaxed‐based performance‐bound algorithm and a greedy optimization‐based suboptimal algorithm are presented for comparison purpose. Finally, the performance of these proposed algorithms are testified by numerical simulations, which confirm the analysis results.     

多接入移动边缘计算技术在移动网络的部署实践与思考

多接入移动边缘计算(MEC)技术是当前兴起的一项新技术。通过把计算、存储、带宽和应用等资源放在网络的边缘侧,以减小传输延迟和带宽消耗。MEC可以广泛应用于运营商的4G/5G等移动网络以及Wi-Fi无线网络,并将会成为未来工业自动化和信息化应用的新一代解决方案。本文介绍了多接入移动边缘计算技术如何与4G/5G移动网络结合并在行业场景中的实际尝试和探索,并对主要研究进展和需解决的关键问题进行了介绍。     

5G在工业互联网领域的应用进展

"5G+工业互联网"已成为产业界探索的重要方向,但仍存在工业企业对5G能发挥的作用、与工业融合落地方式及发展趋势认识不足的问题。首先剖析了5G技术赋能工业企业数字化转型的作用,其次从建网模式、5G+MEC、融合终端、融合应用等方面总结了"5G+工业互联网"阶段性发展经验,最后展望5G技术及标准化趋势,并提出5G与工业互联网融合创新是产业发展的必然趋势,需要产业界持续探索和推进。     

数字孪生使能的智能超表面边缘计算网络任务卸载

针对新兴的计算密集型应用对移动用户高计算性能需求问题,该文提出一种数字孪生(DT)结合智能反射面(RIS)辅助的移动边缘计算(MEC)任务卸载方案。首先,在满足用户传输功率、用户和资源设备能耗、计算资源限制条件下,通过联合优化用户卸载决策、用户传输功率、RIS 相移、波束成形矢量、计算资源分配,建立一个系统能耗最小化问题;其次,将该非凸组合优化问题分解为3个子问题,使用深度双Q网络(DDQN)方法确定用户卸载策略;然后对每个训练时间步进行一次求解,基于交替迭代方法得到问题的优化解。仿真结果表明,基于DDQN的算法训练速度较快,有效降低了系统总能耗。     

无人机辅助反向散射通信计算任务卸载与资源分配

针对边缘计算网络中用户能量短缺问题,该文提出一种无人机(UAV)辅助的反向散射通信网络计算任务卸载和资源分配方案。首先,通过联合考虑飞行轨迹、用户的计算频率、任务卸载比例、无人机及用户的发射功率、反向散射时间分配以及主动通信时间分配,构建最小化无人机总能耗优化问题。其次,利用交替优化算法,将原非凸问题分解为两个子问题,并通过连续凸逼近方法将原问题转化为凸问题进行求解。仿真结果表明,所提算法使得无人机能耗显著减少,且具有良好的收敛性。     

面向云网融合的细粒度多接入边缘计算架构

随着智能终端设备的爆发式增长,多接入边缘计算(multi-access edge computing, MEC)成为支持多服务、多租户生态系统的关键技术之一.多接入边缘计算通过结合云端的移动计算技术和接入网的无线通信技术,实现了云端和网络的高效融合.然而,目前的边缘计算技术对于所有可能的资源(例如计算、通信、缓存)并没有细粒度的控制能力,因此并不能对延迟敏感的实时服务提供很好的支持.为了解决这个关键问题,设计了一种基于软件定义(software defined)的细粒度多接入边缘计算架构,可以对网络资源和计算资源进行细粒度的控制并进行协同管理,并设计了一种基于深度强化学习Q-Learning的两级资源分配策略,从而提供更有效的计算卸载和服务增强.大量的仿真实验证明了该架构的有效性.     

Evolution Toward Artificial Intelligence of Things Under 6G Ubiquitous-X

基于6G Ubiquitous-X的智能物联网演进

张平¹,许晓东²,秦晓琦¹,刘宜明¹,马楠¹,韩书君²

（1．北京邮电大学 网络与交换技术国家重点实验室,北京100876;

2．北京邮电大学 移动互联网安全技术国家工程实验室,北京100876）

中文说明：

随着蜂窝网络的演进,第六代移动通信系统（6G）通过为“人-机-物-灵”提供泛在的通信、计算、控制与意识能力,构建泛在智能化信息社会。“灵”作为6G用户的智能助手可以满足用户的智能需求,是6G实现从现实世界业务向虚拟世界体系业务延伸的关键部分。在6G的支撑下,物联网将迈入智能物联网（AIoT）时代,AIoT将具有智慧感知、智慧分析和智慧控制的能力。本文介绍了6G网络基础架构Ubiquitous-X的概念,及该架构下AIoT的定义与框架。指出了新型AIoT应用的业务需求所面临的技术挑战,包括大规模智能连接、高效计算、安全、隐私及身份验证、高扩展性和高效率等。进一步给出了实现AIoT的潜在使能技术,以支持跨终端的无缝服务体验。

关键词：智能物联网,6G,泛在性,人工智能,移动边缘计算,区块链,物理层安全

     

Enhanced hydrogen production from waste activated sludge by cascade utilization of organic matter in microbial electrolysis cells

Fermentative hydrogen production from waste activated sludge (WAS) has low H₂ yield because WAS contains limited amounts of carbohydrate suitable for use by hydrogen-producing bacteria. Here, augmentation of hydrogen production from WAS by microbial electrolysis cells (MECs) was implemented. H₂ yields of 3.89 ± 0.39 mg-H₂/g-DS (5.67 ± 0.61 mg-H₂/g-VSS) from raw WAS and 6.78 ± 0.94 mg-H₂/g-DS (15.08 ± 1.41 mg-H₂/g-VSS) from alkaline-pretreated WAS were obtained in the two-chamber MECs (TMECs). This was several times higher than yields obtained previously by fermentation. Single-chamber MECs (SMECs) with low internal resistance showed a H₂ production rate that 13 times that of TMECs with similar H₂ yield when alkaline-pretreated WAS was used. However, methanogenesis was detected after several batch cycles. A yield balance calculation revealed that carbohydrates were not the only substrates for electrohydrogenesis. Protein and its acidification products, such as volatile fatty acids are also responsible for a portion of H₂ generation in MEC. Characterization of WAS in TMECs by three-dimensional excitation-emission matrix (EEM) fluorescence spectroscopy with parallel factor analysis indicated that electrohydrogenesis reacted on the extracellular polymeric substances and intracellular substances of WAS. Cascade utilization of organic matter in MECs increased hydrogen production from WAS. MECs showed high hydrogen yield from WAS, fewer H₂ sinks, and insensitivity to temperature. Optimizing MEC configurations and operation conditions and improving the pretreatment processes of WAS are necessary before practical application can take place on a large scale.     

Hydrogen production with nickel powder cathode catalysts in microbial electrolysis cells

Although platinum is commonly used as catalyst on the cathode in microbial electrolysis cells (MEC), non-precious metal alternatives are needed to reduce costs. Cathodes were constructed using a nickel powder (0.5–1 μm) and their performance was compared to conventional electrodes containing Pt (0.002 μm) in MECs and electrochemical tests. The MEC performance in terms of coulombic efficiency, cathodic, hydrogen and energy recoveries were similar using Ni or Pt cathodes, although the maximum hydrogen production rate (Q) was slightly lower for Ni (Q = 1.2–1.3 m³ H₂/m³/d; 0.6 V applied) than Pt (1.6 m³ H₂/m³/d). Nickel dissolution was minimized by replacing medium in the reactor under anoxic conditions. The stability of the Ni particles was confirmed by examining the cathodes after 12 MEC cycles using scanning electron microscopy and linear sweep voltammetry. Analysis of the anodic communities in these reactors revealed dominant populations of Geobacter sulfurreduces and Pelobacter propionicus. These results demonstrate that nickel powder can be used as a viable alternative to Pt in MECs, allowing large scale production of cathodes with similar performance to systems that use precious metal catalysts.     

Distance control strategy for deploying content replica servers in an edge cloud

To reduce fetching cost from a remote source,it is natural to cache information near the users who may access the information later.However,with development of 5 G ultra-dense cellular networks andmobile edge computing(MEC),a reasonable selection among edge servers for content delivery becomes a problem when the mobile edge obtaining sufficient replica servers.In order to minimize the total cost accounting for both caching and fetching process,we study the optimal resource allocation for the content replica servers’ deployment.We decompose the total cost as the superposition of cost in several coverages.Particularly,we consider the criterion for determining the coverage of a replica server and formulate the coverage as a tradeoff between caching cost and fetching cost.According to the criterion,a coverage isolation(CI) algorithm is proposed to solve the deployment problem.The numerical results show that the proposed CI algorithm can reduce the cost and obtain a higher tolerance for different centrality indices.