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市场调查报告书
商品编码
1914649
行动边缘运算市场 - 全球产业规模、份额、趋势、机会及预测(按组件、应用、组织规模、技术、垂直产业、地区和竞争格局划分),2021-2031年Mobile Edge Computing Market - Global Industry Size, Share, Trends, Opportunity, and Forecast, Segmented By Component, By Application, By Organization Size, By Technology, By Industry Vertical, By Region & Competition, 2021-2031F |
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全球行动边缘运算市场预计将从2025年的11.2372亿美元成长到2031年的48.9832亿美元,复合年增长率(CAGR)达27.81%。行动边缘运算(MEC)将储存和运算资源策略性地部署在网路边缘,更靠近终端用户,从而降低延迟并最大限度地提高频宽效率。这一市场成长的主要驱动力是扩增实境(AR)和自动驾驶汽车等资料密集型应用需求的不断增长,以及物联网(IoT)的快速发展,后者需要即时处理。 5G网路的广泛部署将进一步推动市场成长,为分散式云端架构提供所需的高速连线。根据GSMA的数据,到2025年,智慧城市和媒体将分别占私有5G网路部署的22%,凸显了特定产业正在积极利用这些在地化运算能力。
| 市场概览 | |
|---|---|
| 预测期 | 2027-2031 |
| 市场规模:2025年 | 11.2372亿美元 |
| 市场规模:2031年 | 4,898,320,000 美元 |
| 复合年增长率:2026-2031年 | 27.81% |
| 成长最快的细分市场 | 软体 |
| 最大的市场 | 亚太地区 |
然而,该市场面临许多障碍,包括高昂的基础设施成本和复杂的整合流程。多厂商环境下缺乏标准化通讯协定阻碍了互通性,也使得企业和营运商难以实现统一的扩充性。解决这些财务和技术障碍仍然是该生态系统实现广泛商业性成功的关键挑战。
5G独立组网(SA)和先进网路基础设施的引进将成为行动边缘运算领域的关键驱动力,为网路切片和超低延迟奠定必要的架构基础。与依赖传统核心网路的非独立网路架构不同,5G SA允许营运商将处理能力直接部署在网路边缘,从而支援需要即时回应的关键任务型应用。这项基础设施正在全球迅速扩展;根据全球行动供应商协会(GMSA)于2024年11月发布的《5G市场概述》,已有64通讯业者在其公共网路上试运行、正式发布或部署了5G独立组网。这种广泛的部署将为边缘服务创造一个商业性可行性的环境,并实现分散式云端资源的无缝集成,从而提升频宽密集型应用的效能。
同时,智慧製造和工业IoT的快速发展推动了对本地数据处理的需求,以确保营运效率和数据主权。製造工厂正越来越多地将专用网路与边缘节点结合,在本地处理大量感测器数据,从而降低传输成本并减轻与公共云端相关的安全风险。诺基亚在2024年6月发布的《2024年工业数位化报告》中重点强调了这项策略,该报告显示,39%拥有专用无线网路的公司正在部署本地边缘技术以支援其数位化目标。此外,广泛的连接性也推动了这一需求,GSMA预测,到2029年,5G将占所有行动连线的50%以上,这凸显了边缘运算在管理资料流量快速成长方面将发挥的关键作用。
全球行动边缘运算市场面临诸多挑战,包括高昂的基础设施成本和整合碎片化标准的复杂性。建构稳健的边缘架构需要大量资本投入,以便在靠近终端用户的位置部署密集的运算资源和储存节点。多厂商环境下的互通性不足进一步加剧了这项财务负担。当专有解决方案无法无缝协作时,通讯业者和企业被迫经营碎片化的生态系统,导致重复的工程工作和不可预测的可扩展性。这种技术碎片化增加了整体拥有成本 (TCO),并延迟了投资回报,使得潜在用户在进行大规模部署之前犹豫不决。
这些整合挑战的影响在关键产业领域(这些领域最能受益于低延迟连线)的缓慢普及中显而易见。儘管试验计画已经启动,但协调各种硬体和软体通讯协定的困难阻碍了这些计划扩展到全面的商业部署。根据全球行动供应商协会 (GSA) 的数据,截至 2024 年 12 月,全球私有行动网路部署的客户案例总数仅为 1,603 个。虽然这一数字正在成长,但它仅占潜在企业市场的一小部分,这表明整合复杂性和高成本如何直接限制了生态系统的潜在规模。
人工智慧 (AI) 和机器学习 (ML) 在边缘的整合正在从根本上重塑市场格局,它能够实现即时推理,并减少对集中式云端平台处理频宽密集型工作负载的依赖。这一趋势在预测性维护和电脑视觉部署中尤其明显,本地数据处理消除了延迟瓶颈,提高了营运响应速度。这种方法的价值正在推动其快速普及。诺基亚于 2024 年 6 月发布的《2024 年工业数位化报告》显示,75% 的受访企业透过整合视讯分析和边缘运算资源,实现了至少 10% 的效率提升。这些实际成果正促使各行业优先考虑即时资料洞察,而非简单的连接,并将 AI 驱动的边缘节点直接整合到本地网路中。
同时,企业正经历着向云端原生和容器化边缘架构的重大转型,以将软体与底层硬体解耦,并确保工作负载在混合环境中的可移植性。这种架构演进使营运商和企业能够动态管理跨公共云端和本地边缘节点的应用程序,从而解决静态旧有系统固有的互通性挑战。这种对柔软性的需求也得到了行业趋势的支持:根据 Nutanix 于 2024 年 3 月发布的《2024 年企业云指数》,95% 的组织在过去 12 个月中已将应用程式迁移到不同的 IT 环境,以优化效能和安全性。这种频繁的工作负载迁移需要云端原生边缘解决方案提供的标准化容器环境,以确保应用程式无论实体位置如何都能一致地运作。
The Global Mobile Edge Computing Market is projected to expand from USD 1,123.72 million in 2025 to USD 4,898.32 million by 2031, registering a CAGR of 27.81%. Mobile Edge Computing (MEC) strategically places storage and computing resources at the network edge, closer to end-users, to reduce latency and maximize bandwidth efficiency. This market growth is primarily fueled by the escalating needs of data-heavy applications, including augmented reality and autonomous vehicles, as well as the rapid expansion of the Internet of Things (IoT), which necessitates real-time processing. The broad rollout of 5G networks further acts as a catalyst, offering the high-speed connectivity required for distributed cloud architectures. Data from the GSMA indicates that in 2025, the smart cities and media sectors each represented 22% of private 5G network deployments, underscoring the specific industries actively leveraging these localized computing capabilities.
| Market Overview | |
|---|---|
| Forecast Period | 2027-2031 |
| Market Size 2025 | USD 1,123.72 Million |
| Market Size 2031 | USD 4,898.32 Million |
| CAGR 2026-2031 | 27.81% |
| Fastest Growing Segment | Software |
| Largest Market | Asia Pacific |
However, the market faces substantial obstacles regarding high infrastructure costs and the complexities associated with integration. The lack of standardized protocols across multi-vendor environments hinders interoperability, making it difficult for enterprises and operators to achieve uniform scalability. Addressing these financial and technical barriers remains a crucial challenge for the ecosystem to achieve widespread commercial success.
Market Driver
The rollout of 5G Standalone (SA) and advanced network infrastructure serves as a major driver for the mobile edge computing sector, establishing the architectural foundation necessary for network slicing and ultra-low latency. Unlike non-standalone architectures that depend on legacy cores, 5G SA allows operators to locate processing capabilities directly at the network edge, supporting mission-critical applications that require instantaneous response times. This infrastructure is rapidly expanding globally; the '5G-Market Snapshot' released by the Global mobile Suppliers Association in November 2024 notes that 64 operators have already soft-launched, launched, or deployed standalone 5G in public networks. This widespread deployment creates a commercially viable environment for edge services, enabling the seamless integration of distributed cloud resources to enhance the performance of bandwidth-intensive applications.
Simultaneously, the exponential rise in smart manufacturing and Industrial IoT adoption is driving the need for localized data processing to ensure operational efficiency and data sovereignty. Manufacturing plants are increasingly utilizing private networks combined with edge nodes to process massive amounts of sensor data on-site, thereby reducing transmission costs and mitigating security risks associated with public clouds. This strategy is highlighted in Nokia's '2024 Industrial Digitalization Report' from June 2024, which reveals that 39% of enterprises with private wireless networks have deployed on-premise edge technology to support their digitalization goals. Furthermore, the broader connectivity landscape reinforces this demand, as the GSMA projects that 5G will account for over 50% of total mobile connections by 2029, emphasizing the critical role of edge computing in managing the impending surge in data traffic.
Market Challenge
The Global Mobile Edge Computing Market encounters a significant barrier due to high infrastructure costs combined with the complexities of integrating fragmented standards. Establishing a robust edge architecture requires substantial capital investment to deploy dense computing resources and storage nodes physically closer to end-users. This financial burden is exacerbated by the lack of interoperability within multi-vendor environments. When proprietary solutions fail to communicate seamlessly, operators and enterprises must navigate a disjointed ecosystem, resulting in redundant engineering efforts and unpredictable scalability. This technical fragmentation increases the total cost of ownership and delays the return on investment, causing potential adopters to hesitate before committing to full-scale rollouts.
The impact of these integration challenges is reflected in the slow pace of adoption across key industrial verticals that would otherwise benefit most from low-latency connectivity. Although pilot programs are initiating, the difficulty in harmonizing diverse hardware and software protocols prevents these projects from expanding into mass commercial deployments. According to the Global mobile Suppliers Association (GSA), in December 2024, the total number of unique customer references for private mobile network deployments reached only 1,603 globally. While this figure is growing, it represents a minute fraction of the potential enterprise market, illustrating how integration complexity and high costs are directly restricting the ecosystem from achieving its full volume potential.
Market Trends
The incorporation of Artificial Intelligence and Machine Learning at the Edge is fundamentally reshaping the market by facilitating real-time inference and reducing reliance on centralized clouds for bandwidth-heavy workloads. This trend is particularly prominent in the deployment of predictive maintenance and computer vision, where processing data locally eliminates latency bottlenecks and improves operational responsiveness. The value of this approach is driving rapid adoption; according to Nokia's '2024 Industrial Digitalization Report' from June 2024, integrating video analytics with edge computing resources allowed 75% of surveyed enterprises to achieve an efficiency improvement of at least 10%. Such tangible gains are compelling industries to embed AI-driven edge nodes directly into their local networks, prioritizing immediate data insights over simple connectivity.
At the same time, there is a notable shift toward Cloud-Native and Containerized Edge Architectures as enterprises seek to decouple software from underlying hardware to ensure workload portability across hybrid environments. This architectural evolution permits operators and businesses to dynamically manage applications across public clouds and on-premise edge nodes, resolving the interoperability challenges inherent in static legacy systems. The demand for this flexibility is substantiated by industry behavior; Nutanix's 'Enterprise Cloud Index 2024' from March 2024 reports that 95% of organizations migrated applications between different IT environments in the previous twelve months to optimize performance and security. This high frequency of workload movement necessitates the standardized, containerized environments provided by cloud-native edge solutions, ensuring that applications run consistently regardless of their physical location.
Report Scope
In this report, the Global Mobile Edge Computing Market has been segmented into the following categories, in addition to the industry trends which have also been detailed below:
Company Profiles: Detailed analysis of the major companies present in the Global Mobile Edge Computing Market.
Global Mobile Edge Computing Market report with the given market data, TechSci Research offers customizations according to a company's specific needs. The following customization options are available for the report: