Investment Rating - The report does not explicitly provide an investment rating for the industry Core Insights - The new calling service integrates media, data interaction, and application functions into traditional audio and video calls, providing innovative real-time communication services that are fun, intelligent, and diverse, becoming a key focus for operators' transformation and industry empowerment [2][3] - The introduction of interactive data channels and mini-program-based service models increases the complexity of security risk prevention in network, operation, and business management [2][3] - The report evaluates potential security risks associated with new calling services, including anti-fraud security and capability opening security, and proposes strategies for developing a comprehensive and efficient business security capability system [3][44] Summary by Sections 1. Development Trends of New Calling Services - The new calling service is an upgrade of traditional audio and video calls, providing multimedia calling and deep integration with data applications to meet diverse communication needs [6][7] - The commercial use of new calling services is divided into two phases: the first phase focuses on video calling enhancements, while the second phase introduces data channel-based services [8][9] 2. Security Risks and Protection Strategies - The report identifies various security risks, including network-side security, mini-program security, terminal-side security, data security, and intercommunication security [22] - Specific risks include control plane security, media plane security, and the need for compliance and security audits for mini-programs [22][29] 3. Future Business Security of New Calling - The report anticipates that the integration of new calling services with industry digital transformation will lead to the evolution from audio-video communication to multimodal communication, blurring the boundaries of network security [44][45] - It emphasizes the importance of building a robust security capability system to support the healthy and sustainable development of new calling services [45] 4. Security Development Strategy Recommendations - The report suggests enhancing internal security risk management through standardization, integrating dynamic risk identification into daily operations, and learning from internet business practices for rapid iteration of risk management measures [52][53][55]

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Industry Overview - Edge computing is becoming a new direction in the computing system, a new format in the information field, and a new platform for industrial transformation, serving as a critical infrastructure for the digital and intelligent transformation of vertical industries [2] - The global digital wave is driving the rapid development of edge computing, which provides key capabilities such as computing, networking, and intelligence to accelerate economic transformation and upgrading [2] - China has issued several policies to promote the development of edge computing, including the "High-Quality Development Action Plan for Computing Infrastructure" and the "14th Five-Year Plan for Digital Economy Development" [9][11] Edge Computing Concept and Characteristics - Edge computing refers to the deployment of computing resources closer to data sources and users, reducing data transmission latency and improving response speed [16] - Edge computing is characterized by resource heterogeneity, network heterogeneity, ubiquitous distribution, low latency, low cost, and high privacy [19] - Edge computing is not just about new facilities or architectures but a new ecosystem that integrates network, computing, storage, application, and intelligence resources at the network edge [17] Key Technologies in Edge Computing - Edge computing infrastructure includes hardware resources (CPU, GPU, storage, network) and resource virtualization, which abstracts physical hardware into logical resources for unified management and scheduling [21][22][27] - Edge computing networks focus on distributed computing resource perception, measurement, scheduling, and control, enabling efficient resource allocation and task execution [33][34][39] - Edge intelligence involves deploying AI models at the edge for real-time decision-making, with key technologies including model optimization, edge training, and edge inference [42][51][60] Edge Computing Applications in Industrial Internet - Edge computing addresses the challenges of high latency, bandwidth pressure, and data security risks in traditional industrial internet applications by bringing computing resources closer to the data source [73] - In industrial internet scenarios, edge computing enables real-time control, fault prediction, and dynamic deployment of applications, improving production efficiency and flexibility [74][77] - A cloud-edge collaborative architecture, supported by 5G networks and edge computing, allows for rapid deployment and dynamic scheduling of industrial applications, enhancing operational efficiency [76][77] Edge Computing Security - Edge computing faces security risks such as node attacks, data privacy breaches, and network vulnerabilities, requiring comprehensive security measures across infrastructure, data, and network layers [65][66][69] - Security technologies for edge computing include lightweight data encryption, secure storage, and privacy-preserving computation, ensuring data integrity, confidentiality, and availability throughout its lifecycle [67][68] - Blockchain technology is being explored to ensure secure and trustworthy transactions in edge computing services, enabling distributed and trusted management of computing resources [72]

中国信息 信息通 中国信息通信研究 | --- | --- | --- | --- | --- | --- | --- | --- | |----------|-------|-------|-------|-------|-------|-------|-------| | 中国信息 | | | | | | | | | | | | | | | | | 信息通 通信研究院 国信息通信 X 中国 工业网络进入发展新阶段 高息通信研究院 息通信研究院 究院 口工业网络是企业用于研发、生产、办公、经营等活动的网络， 涵盖工业控制网络和工业信息网络两个层次，是 连接生产各环节人、机、料、法、环、测的重要基础设施。 第一次工业革命 第二次工业革命 第三次工业革命 第四次工业革命 （机械化） (电气化） （自动化） （智能化） S 蒸汽机 铁路/钢铁 电力电气石油/汽车 互联网、计算机 工业互联网 人工智能 中国信 国信息通 信研 工业网络1.0（模拟电路） 工业网络2.0（数字网络） 工业总线工业以太网 新型工业网络 点到点通信， 功能单 工业5GITSN\AI开放自动化边缘计算 局部互联， 中国信息通信 支撑自动化 ...

CAICT 中国信通院 信息无障碍动态 （2024 年 第 7 期） 中国信息通信研究院 本期导读 1. 中共中央关于进一步全面深化改革推进中国式现代化的 决定 . 二、 部委动态 1. 工信部发布 2024年第二季度电信服务质量通告 ............. 1 2. 民政部发布《养老机构设施设备配置》等8项推荐性行业 1. 上海市印发《上海市推进养老科技创新发展行动方案 （2024-2027年）》 2. 云南、宁夏等地出台措施促进银发经济发展增进老年人 一、 中央动态 标准 . 三、地方进展 . 福祉 . 四、 企业及社会团体行动 . 1. 首届中国老龄事业发展基金会数智助老大会在京召开 .... 3 2. "AI 时代的人机关系展望"论坛在深圳成功举办 ...................... 5 3. 《中国健康老龄化发展蓝皮书(2023-2024)》发布 ................. 一、中央动态 1. 中共中央关于进一步全面深化改革推进中国式现代化的 决定 7 月 14 日，党的二十届三中全会审议通过《中共中央 关于进一步全面深化改革、推进中国式现代化的决定》 （以下简称《决定》）。 ...

CAICT 中国信通院 信息无障碍动态 （2024 年 第 9 期） 中国信息通信研究院 本期导读 一、 国际动态.............................................................................1 1. 中国代表在联合国人权理事会第 57 届会议上分享中国在 消除不平等和经社文权利等领域取得历史性成就................. 1 二、 中央动态.............................................................................2 1. 中共中央政治局召开会议分析研究当前经济形势和经济 工作..............................................................................................2 三、 部委动态.............................................................................2 1. 工业和 ...

Investment Rating - The report does not explicitly state an investment rating for the industry Core Insights - The report emphasizes the growing demand for computing power resources driven by the digital transformation of industries and households, highlighting the importance of all-optical capacity as a foundational support for connecting users and computing resources [3][4] - It identifies key application scenarios in various sectors such as smart transportation, industrial simulation, digital cultural tourism, and smart home entertainment, while also exploring distributed model training scenarios [3][4] - The report outlines critical technologies required to meet the quality computing needs of enterprises and users, including ultra-large bandwidth, determinism, high reliability, business awareness, and collaborative computing [3][4] Summary by Sections Overview - The report discusses the emergence of various computing applications that create new demands and challenges for networks, driven by the growth of consumer internet and industrial internet applications [7][8] - It notes that the construction of all-optical networks has made significant progress, with China having the largest optical fiber communication network globally, and highlights the rapid increase in the number of users with gigabit and above internet access [7][8] All-Optical Capacity Application Demand - **Smart Transportation**: The report details the upgrade of traffic cameras to smart cameras, which necessitates increased bandwidth from 9 Mbps for traditional cameras to 103 Mbps for high-definition smart cameras [9][10] - **Industrial Simulation**: It highlights the integration of cloud technology and AI in industrial simulation, emphasizing the need for high-performance computing and the ability to dynamically adjust bandwidth for data transmission [16][20] - **Digital Cultural Tourism**: The report discusses the trend of internet cafes moving to cloud services, with expectations of cloud adoption increasing from 6% in 2023 to 15% in 2024, requiring stable and high bandwidth for seamless user experience [22][26] - **Smart Home Entertainment**: It outlines the requirements for cloud gaming and VR applications, emphasizing the need for low latency and high bandwidth to ensure a smooth user experience [38][40] Key Technologies for All-Optical Capacity - The report identifies essential technologies such as ultra-large bandwidth, deterministic carrying, high reliability, business awareness scheduling, and collaborative computing control as critical for supporting industry applications [3][4] Industry Application Cases - The report presents various innovative application cases across sectors, including smart transportation, digital cloud internet cafes, smart home computers, and remote computing [3][4] Conclusion and Outlook - The report concludes by emphasizing the need for collaborative efforts in advancing all-optical capacity technologies and applications to support the digital economy's high-quality development [3][4]

Investment Rating - The report does not explicitly state an investment rating for the industry Core Insights - The report emphasizes the growing demand for computing power driven by the digital transformation and AI advancements, highlighting the importance of all-optical networks as a foundational infrastructure to support this demand [3][7] - It identifies four key demands for the all-optical network in the computing era: high-quality cloud access, urban computing interconnectivity, interconnectivity between hubs, and intelligent network scheduling [3][9] - The report outlines the target architecture and key technology systems for the all-optical network, aiming to provide flexible and high-quality access to computing resources [30][31] Summary by Sections 1. High-Quality Innovation Development in the Computing Era - The report discusses the increasing requirements for computing and network integration services due to AI advancements and the need for high-quality communication networks to support distributed computing clusters [7][8] - It highlights global initiatives to enhance optical network infrastructure as a foundation for digital economy development [7][8] 2. Four Key Demand Characteristics of the All-Optical Network - The report identifies four characteristics: stable high bandwidth, high reliability and security, deterministic low latency, and intelligent services [9][10] - It emphasizes the need for the all-optical network to evolve towards ultra-large bandwidth and ultra-low latency to meet the demands of various applications [9][10] 3. Target Architecture and Key Technologies of the All-Optical Network - The target architecture consists of four components: computing access network (DCA), interconnect network (DCI), data center network (DCN), and unified scheduling system [30][31] - The report outlines the importance of high-quality access and interconnectivity to enhance the efficiency of computing resource utilization [30][31] 4. High-Quality Cloud Access - The report discusses the global shift towards 10Gbps optical access networks, with various countries implementing plans to enhance broadband connectivity [11][12] - It highlights the increasing demand for high-bandwidth home networks driven by diverse applications and devices [12][16] 5. Urban Computing Interconnectivity - The report emphasizes the critical need for low-latency networks in sectors like finance, where microsecond-level latency savings are significant [22][23] - It discusses the requirements for cloud service providers to maintain low latency between availability zones [22][23] 6. Interconnectivity Between Hubs - The report notes the surge in demand for distributed computing clusters due to the training of large AI models, necessitating high-capacity interconnects between data centers [24][25] - It highlights the need for high reliability in data center interconnect networks to minimize downtime during model training [27] 7. Intelligent Network Scheduling - The report discusses the integration of AI and big data technologies to enhance the efficiency of network operations and resource management [28][29] - It emphasizes the importance of intelligent scheduling for optimizing computing resource allocation and service delivery [28][29]

CAICT 中国信通院 数据价值化与数据要素市场 数据价值化与数据要素市场 发展报告 发展报告 (2024 年) (2024 年) 中国信息通信研究院政策与经济研究所 中国信息通信研究院政策与经济研究所 2024年9月 2024年9月 D> | --- | --- | |----------------------------------------------------|-------| | 版权声明 | | | | | | 本报告版权属于中国信息通信研究院，并受法律保护。 | | | 转载、摘编或利用其它方式使用本报告文字或者观点的， | | | 应注明"来源：中国信息通信研究院"。违反上述声明者， | | 前 言 近年来，习近平总书记围绕"发挥数据的基础资源作用和创新 引擎作用"做出多项重要战略部署，党的二十届三中全会再一次对 加快全国一体化数据要素市场建设，完善数据要素市场制度规则等 提出新要求。去年 10 月，国家数据局正式挂牌成立，在数据要素市 场化配置改革、数据基础制度体系建设、数据创新应用等方面取得 了积极进展。 本报告围绕"新理论、新进展、新价值、新对策"，从经济学 角度出发分析数据要素市 ...

Global Quantum Computing Landscape - Quantum computing is entering a rapid development phase, with over 30 countries actively investing in quantum information technologies, including quantum computing [7] - The US has invested $39 39 billion in quantum information from 2019 to 2023, exceeding its initial $12 75 billion plan, with quantum computing receiving the highest share of $14 billion [8] - The EU has launched a new Quantum Flagship Program with short-term (2027) and mid-term (2030) goals to achieve leadership in quantum technology and industry [9] - China has integrated quantum computing into its national development strategy, with over 20 provinces including quantum computing in their local development plans [10] Technological Advancements and Challenges - Quantum computing research has seen a 4x increase in global publications over the past decade, with the US and China leading in both publication volume and patent applications [13][16] - Superconducting quantum computing remains the most prominent technology route, with 9380 patent applications and 3976 granted patents globally [18] - Quantum error correction research is advancing, with IBM achieving a 0 7% error threshold using 288 physical qubits to protect 12 logical qubits [30] - Multiple hardware routes (superconducting, ion trap, neutral atom, photonic, silicon-based) are competing, with no clear convergence in the near term [23][28] Industry Ecosystem and Investment Trends - Global quantum computing companies reached 329 by July 2024, with a significant slowdown in new company formation (only 1 new company in H1 2024) [19] - The US leads in quantum computing companies (93), followed by China (36), with superconducting technology being the most pursued route (25 companies) [20] - Quantum computing investments showed signs of recovery in H1 2024, with $1 2 billion raised, following a dip to $1 4 billion in 2023 from $2 billion in 2022 [21][22] - Venture capital remains the dominant funding source, accounting for over 60% of the 143 investment deals in 2023 [22] Application Exploration and Cloud Platforms - Quantum computing applications are being explored in finance, chemistry, biology, transportation, and AI, with potential market value estimated at $1 trillion by 2035 [40][41] - Quantum cloud platforms are emerging as a key service model, with IBM, IonQ, and Chinese companies like Origin Quantum offering access to various quantum processors [46][48] - China has launched several quantum cloud platforms, including Quafu (100+ qubits) and Tianyan (504 qubits), aiming to expand quantum computing applications [48][49] - Quantum-classical hybrid computing is gaining traction, with NVIDIA and Microsoft developing systems to integrate quantum and classical computing resources [56] Benchmarking and Standardization - Quantum computing benchmarking is evolving, with IBM introducing new metrics like EPLG and CLOPSh to better assess hardware performance [52] - The QED-C updated its application-oriented benchmarking suite in 2024, expanding evaluation criteria for quantum algorithms like HHL and VQE [53] - Standardization is becoming a focus area, with international efforts to establish evaluation systems and interoperability standards for quantum computing [54]