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市場調查報告書
商品編碼
1914649
行動邊緣運算市場 - 全球產業規模、佔有率、趨勢、機會及預測(按組件、應用、組織規模、技術、垂直產業、地區和競爭格局分類),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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全球行動邊緣運算市場預計將從2025年的11.2372億美元成長到2031年的48.9832億美元,複合年成長率(CAGR)達27.81%。行動邊緣運算(MEC)將儲存和運算資源策略性地部署在網路邊緣,更靠近終端用戶,從而降低延遲並最大限度地提高頻寬效率。這一市場成長的主要驅動力是擴增實境(AR)和自動駕駛汽車等資料密集型應用需求的不斷成長,以及物聯網(IoT)的快速發展,後者需要即時處理。 5G網路的廣泛部署將進一步推動市場成長,為分散式雲端架構提供所需的高速連線。根據GSMA的數據,到2025年,智慧城市和媒體將分別佔私有5G網路部署的22%,凸顯了特定產業正在積極利用這些在地化運算能力。
| 市場概覽 | |
|---|---|
| 預測期 | 2027-2031 |
| 市場規模:2025年 | 11.2372億美元 |
| 市場規模:2031年 | 4,898,320,000 美元 |
| 複合年成長率:2026-2031年 | 27.81% |
| 成長最快的細分市場 | 軟體 |
| 最大的市場 | 亞太地區 |
然而,該市場面臨許多障礙,包括高昂的基礎設施成本和複雜的整合流程。多廠商環境下缺乏標準化通訊協定阻礙了互通性,也使得企業和營運商難以實現統一的擴充性。解決這些財務和技術障礙仍然是該生態系統實現廣泛商業性成功的關鍵挑戰。
5G獨立組網(SA)和先進網路基礎設施的引進將成為行動邊緣運算領域的關鍵驅動力,為網路切片和超低延遲奠定必要的架構基礎。與依賴傳統核心網路的非獨立網路架構不同,5G SA允許營運商將處理能力直接部署在網路邊緣,從而支援需要即時回應的關鍵任務型應用。這項基礎設施正在全球迅速擴展;根據全球行動供應商協會(GMSA)於2024年11月發布的《5G市場概述》,已有64通訊業者在其公共網路上試運行、正式發布或部署了5G獨立組網。這種廣泛的部署將為邊緣服務創造一個商業性可行性的環境,並實現分散式雲端資源的無縫整合,從而提升頻寬密集型應用的效能。
同時,智慧製造和工業IoT的快速發展推動了對本地數據處理的需求,以確保營運效率和數據主權。製造工廠正擴大將專用網路與邊緣節點結合,在本地處理大量感測器數據,從而降低傳輸成本並減輕與公共雲端相關的安全風險。諾基亞在2024年6月發布的《2024年工業數位化報告》中重點強調了這項策略,該報告顯示,39%擁有專用無線網路的公司正在部署本地邊緣技術以支援其數位化目標。此外,廣泛的連接性也推動了這一需求,GSMA預測,到2029年,5G將佔所有行動連線的50%以上,這凸顯了邊緣運算在管理資料流量快速成長方面將發揮的關鍵作用。
全球行動邊緣運算市場面臨諸多挑戰,包括高昂的基礎設施成本和整合碎片化標準的複雜性。建構穩健的邊緣架構需要大量資本投入,以便在靠近終端用戶的位置部署密集的運算資源和儲存節點。多廠商環境下的互通性不足進一步加劇了這項財務負擔。當專有解決方案無法無縫協作時,通訊業者和企業被迫經營碎片化的生態系統,導致重複的工程工作和不可預測的可擴展性。這種技術碎片化增加了整體擁有成本 (TCO),並延遲了投資回報,使得潛在用戶在進行大規模部署之前猶豫不決。
這些整合挑戰的影響在關鍵產業領域(這些領域最能受益於低延遲連線)的緩慢普及中顯而易見。儘管試驗計畫已經啟動,但協調各種硬體和軟體通訊協定的困難阻礙了這些計劃擴展到全面的商業部署。根據全球行動供應商協會 (GSA) 的數據,截至 2024 年 12 月,全球私有行動網路部署的客戶案例總數僅為 1,603 個。雖然這一數字正在成長,但它僅佔潛在企業市場的一小部分,這表明整合複雜性和高成本如何直接限制了生態系統的潛在規模。
人工智慧 (AI) 和機器學習 (ML) 在邊緣的整合正在從根本上重塑市場格局,它能夠實現即時推理,並減少對集中式雲端平台處理頻寬密集型工作負載的依賴。這一趨勢在預測性維護和電腦視覺部署中尤其明顯,本地數據處理消除了延遲瓶頸,提高了營運響應速度。這種方法的價值正在推動其快速普及。諾基亞於 2024 年 6 月發布的《2024 年工業數位化報告》顯示,75% 的受訪企業透過整合視訊分析和邊緣運算資源,實現了至少 10% 的效率提升。這些實際成果正促使各行業優先考慮即時資料洞察,而非簡單的連接,並將 AI 驅動的邊緣節點直接整合到本地網路中。
同時,企業正經歷著向雲端原生和容器化邊緣架構的重大轉型,以將軟體與底層硬體解耦,並確保工作負載在混合環境中的可移植性。這種架構演進使營運商和企業能夠動態管理跨公共雲端和本地邊緣節點的應用程式,從而解決靜態舊有系統固有的互通性挑戰。這種對柔軟性的需求也得到了行業趨勢的支持:根據 Nutanix 於 2024 年 3 月發布的《2024 年企業雲指數》,95% 的組織在過去 12 個月中已將應用程式遷移到不同的 IT 環境,以最佳化效能和安全性。這種頻繁的工作負載遷移需要雲端原生邊緣解決方案提供的標準化容器環境,以確保應用程式無論實體位置如何都能一致地運作。
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: