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IoT 邊緣運算

市場調查報告書

商品編碼

1372605

全球行動邊緣運算市場 - 2023-2030

Global Mobile Edge Computing Market - 2023-2030

出版日期: 2023年10月18日 | 出版商:

DataM Intelligence | 英文 199 Pages | 商品交期: 約2個工作天內

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簡介目錄

概述

全球行動邊緣運算市場在2022年達到6億美元，預計2030年將達到31億美元，2023-2030年預測期間年複合成長率為26.3%。

擴增實境、虛擬實境、自動駕駛汽車和物聯網設備等應用需要極低的延遲。行動邊緣運算透過處理更靠近來源的資料來減少延遲，從而改善使用者體驗。 5G 網路的推出提供了行動邊緣運算有效運作所需的高頻寬和低延遲。行動邊緣運算透過實現資料的本地處理來補充 5G，從而減少將資料傳輸到集中式雲端伺服器的需要。

例如，2023 年 9 月 26 日，東南亞最大的電信供應商 Telkomsel 選擇 Amazon Web Services 作為其數位轉型工作的首選雲端供應商。 Telkomsel 將把各種 IT 應用程式遷移到 AWS，包括客戶管道、遊戲平台、中間件和機器學習。 Telkomsel 在印尼擁有超過 1.53 億用戶，旨在使用 AWS 增強用戶體驗並更快部署新服務。

亞太地區一直處於5G技術部署的前沿。 5G網路的推出提供了行動邊緣運算所需的高頻寬和超低延遲。行動邊緣運算透過使運算資源更接近網路邊緣來補充 5G，從而實現即時和低延遲的應用。處理物聯網設備在邊緣產生的大量資料需要行動邊緣運算。工業、農業和智慧城市等行業正在使用行動邊緣運算來實現物聯網應用。

動力學

5G應用不斷興起

與前幾代相比，5G 提供了更高的頻寬。行動邊緣運算利用此頻寬來處理和交付資料密集型應用程式，例如 4K 視訊串流、雲端遊戲和大規模物聯網部署。行動邊緣運算透過根據每個網路切片的特定要求自訂邊緣運算資源來補充這一點，確保最佳效能。行動邊緣運算透過在本地處理敏感資訊來增強安全性和資料隱私，從而最大限度地減少資料在傳輸到集中式資料中心期間的暴露。

例如，2021 年2 月2 日，新加坡新加坡電信為企業推出了5G 邊緣運算基礎設施，提供Microsoft Azure Stack 作為選項之一，這使企業能夠在更接近最終目標的情況下處理自動開機車輛、無人機器、機器人和混合實境等應用程式-使用者。借助新加坡電信的 5G 網路，這些應用程式可以以低於 10 毫秒的低延遲交付。

採用先進的網路解決方案

行動邊緣運算將處理任務從集中式資料中心卸載到邊緣伺服器，減少了對核心網路高頻寬連線的需求，從而最佳化了頻寬使用並緩解了網路擁塞。行動邊緣運算架構具有高度可擴展性，可以有效添加邊緣伺服器來滿足不斷成長的工作負載和用戶需求，因為這種可擴展性對於處理不斷增加的物聯網設備和應用程式數量至關重要。

例如，2023 年2 月21 日，T-Mobile 和Amazon Web Services (AWS) 合作，將T-Mobile 的5G 網路解決方案與AWS 基於雲端的服務相結合，此次合作旨在為企業提供更無縫的方式來存取和部署5G邊緣運算能力，加速採用並降低成本。此整合產品被稱為 AWS 上的整合專用無線，將允許組織針對特定用例客製化解決方案，例如遠端工業園區監控、製造中的預測性維護等。

技術進步與創新

人工智慧 (AI) 和機器學習 (ML) 在邊緣的整合是行動邊緣運算的重要驅動力。邊緣人工智慧使各行業的本地決策、預測性維護和智慧自動化成為可能。行動邊緣運算可以透過在本地處理敏感資料而不是將其傳輸到集中式資料中心來增強安全性，這種方法可以減少資料在傳輸過程中面臨潛在威脅的風險。

例如，2023 年 9 月 14 日，總部位於班加羅爾的新創公司 KaleidEO Space Systems 成為第一家在太空展示邊緣運算的印度公司，實現了一個重要的里程碑。該公司使用深度學習演算法即時分析由衛星星座提供商 Satellogic 捕獲的高解析度衛星圖像，這一成就為 KaleidEO 開發具有機載邊緣運算功能的衛星鋪平了道路，使它們能夠捕獲和分析圖像獨立。

有限的資料中心和複雜的伺服器

與集中式資料中心相比，邊緣伺服器的處理能力有限。複雜的運算和資源密集型應用程式可能仍需要雲端或資料中心資源，從而導致此類任務的延遲。 dge 伺服器在 CPU、記憶體和儲存方面的資源有限，這限制了可以在邊緣運行的應用程式的類型和大小。

擴展邊緣基礎設施以適應不斷成長的工作負載和用戶需求可能非常複雜且成本高昂。它需要部署額外的邊緣伺服器並確保與現有網路的無縫整合。管理分散式邊緣環境可能比管理集中式資料中心更複雜。它需要邊緣伺服器的高效編排、監控和維護。

Applications such as augmented reality, virtual reality, autonomous vehicles and IoT devices require extremely low latency. Mobile edge computing reduces latency by processing data closer to the source, improving the user experience. The rollout of 5G networks provides the high bandwidth and low latency necessary for mobile edge computing to function effectively. Mobile edge computing complements 5G by enabling localized processing of data, reducing the need to transmit data to centralized cloud servers.

For instance, on 26 September 2023, Telkomsel, Southeast Asia's largest telecommunications provider, chose Amazon Web Services as its preferred cloud provider for its digital transformation efforts. Telkomsel will migrate various IT applications to AWS, including customer channels, gaming platforms, middleware and machine learning. With over 153 million subscribers in Indonesia, Telkomsel aims to enhance the user experience and deploy new services more quickly using AWS.

Asia-Pacific has been at the forefront of the deployment of 5G technology. The rollout of 5G networks provides the necessary high bandwidth and ultra-low latency required for mobile edge computing. Mobile edge computing complements 5G by bringing computing resources closer to the network edge, enabling real-time and low-latency applications. Processing the vast quantities of data produced at the edge by IoT devices requires mobile edge computing. Mobile edge computing is being used by sectors like industry, agriculture and smart cities to allow IoT applications.

Dynamics

Rising Application of 5G

5G offers significantly higher bandwidth compared to previous generations. Mobile edge computing leverages this bandwidth to process and deliver data-intensive applications, such as 4K video streaming, cloud gaming and large-scale IoT deployments. Mobile edge computing complements this by tailoring edge computing resources to the specific requirements of each network slice, ensuring optimal performance. Mobile edge computing enhances security and data privacy by processing sensitive information locally and this minimizes the exposure of data during transit to centralized data centers.

For instance, on 2 February 2021, Singapore's Singtel launched 5G edge compute infrastructure for enterprises, offering Microsoft Azure Stack as one of the options and this allows enterprises to process applications such as autonomous guided vehicles, drones, robots and mixed reality closer to their end-users. With Singtel's 5G network, these applications can be delivered with low latency of less than 10 milliseconds.

Adoption of Advanced Network Solutions

Mobile edge computing offloads processing tasks from centralized data centers to edge servers, reducing the need for high-bandwidth connections to the core network and this optimizes bandwidth usage and alleviates network congestion. Mobile edge computing architecture is highly scalable, allowing for the efficient addition of edge servers to accommodate growing workloads and user demands as this scalability is crucial for handling the increasing volume of IoT devices and applications.

For instance, on 21 February 2023, T-Mobile and Amazon Web Services (AWS) partnered to combine T-Mobile's 5G network solutions with AWS cloud-based services and this collaboration aims to provide businesses with a more seamless way to access and deploy 5G edge compute capabilities, accelerating adoption and reducing costs. The integrated offering, known as Integrated Private Wireless on AWS, will allow organizations to customize solutions for specific use cases, such as remote industrial campus monitoring, predictive maintenance in manufacturing and more.

Technology Advancement and Innovations

The integration of artificial intelligence (AI) and machine learning (ML) at the edge is a significant driver of mobile edge computing. Edge AI enables local decision-making, predictive maintenance and intelligent automation in various industries. Mobile edge computing can enhance security by processing sensitive data locally instead of transmitting it to centralized data centers and this approach reduces the exposure of data to potential threats during transit.

For instance, on 14 September 2023, KaleidEO Space Systems, a Bengaluru-based startup, achieved a significant milestone by becoming the first Indian company to demonstrate edge computing in space. The company used deep learning algorithms to analyze high-resolution satellite imagery in real-time, captured by Satellogic, a satellite constellation provider and this achievement paves the way for KaleidEO to develop satellites with onboard edge computing capabilities, allowing them to capture and analyze images independently.

Limited Data Centers and Complex Servers

Edge servers have limited processing capabilities compared to centralized data centers. Complex computations and resource-intensive applications may still require cloud or data center resources, leading to latency for such tasks. dge servers have limited resources in terms of CPU, memory and storage and this restricts the types and sizes of applications that can run at the edge.

Scaling edge infrastructure to accommodate growing workloads and user demands can be complex and costly. It requires deploying additional edge servers and ensuring seamless integration with the existing network. Managing a distributed edge environment can be more complex than managing centralized data centers. It requires efficient orchestration, monitoring and maintenance of edge servers.

Segment Analysis

The global mobile edge computing market is segmented based on component, organization size, application, end-user and region.

Cloud-Native Technologies and Edge Network Deployment Boosts the Market

Mobile edge computing software leverages cloud-native technologies such as containerization and microservices which allows for scalable and flexible deployment of edge applications, making it easier for developers to create and manage mobile edge computing services. Intelligent decision-making in real-time has been rendered feasible by mobile edge computing software, which is essential for applications like autonomous vehicles, smart cities and predictive maintenance.

For instance, on 28 February 2023, 5G Networks and Intel announced a partnership to collaborate on edge network deployments in Australia. The companies plan to leverage Intel's technology, including Intel Xeon Scalable processors and FlexRAN software reference architecture, to enhance 5G Networks' edge computing capabilities and this partnership aims to provide businesses with low-latency, high-performance edge computing solutions for various applications, including IoT, artificial intelligence and more.

Geographical Penetration

Region Actively Deploys 5G Networks

North America has been actively rolling out 5G networks. Mobile edge computing leverages 5G to bring computing resources closer to the network edge, enabling real-time and low-latency services. Many cities in the region are implementing smart city projects, including traffic management, public safety and environmental monitoring whereas mobile edge computing plays a crucial role in enabling these initiatives by processing data at the edge in real-time.

For instance, on 30 December 2022, SK Telecom successfully transmitted terrestrial broadcasting in Washington D.C. using mobile edge computing and virtualization technologies in collaboration with Sinclair Broadcast Group, North America's largest terrestrial broadcast conglomerate. Mobile edge computing technology reduces latency by placing a small data center near a base station, minimizing data transmission distance. The platform enables efficient management of broadcast services for numerous regional stations across North America without requiring specialized equipment.

Competitive Landscape

The major global players in the market include: Advantech Co., Ltd., Johnson Controls International plc, Hewlett Packard Enterprise Development LP, Huawei Technologies Co., Ltd., Juniper Networks, Inc., SAGUNA Network LTD, SMART Global Holdings, Inc., Vapor IO, Inc., Nokia Corporation and Skyvera.

COVID-19 Impact Analysis

The pandemic forced many businesses to accelerate their digital transformation efforts to adapt to remote work and changing customer behavior. Mobile edge computing played a crucial role in enabling low-latency applications and services, such as video conferencing, telemedicine and e-commerce, to meet the increased demand. Mobile edge computing supported the growth of remote work and collaboration tools by reducing latency in video conferencing and virtual collaboration platforms.

Mobile edge computing facilitated the adoption of telemedicine and remote healthcare solutions, enabling real-time monitoring of patients and remote consultations with healthcare professionals and this was critical in managing healthcare services during lockdowns and minimizing the risk of virus transmission. Mobile edge computing combined with edge AI enabled the development of contactless solutions, including touchless payments, temperature screening and social distancing monitoring, to enhance safety in public spaces and businesses.

The pandemic disrupted global supply chains, impacting the availability of hardware components needed for mobile edge computing infrastructure deployment. Delayed equipment deliveries and shortages affected deployment timelines. Economic uncertainties caused budget constraints for some organizations, affecting their ability to invest in mobile edge computing infrastructure and services.

AI Impact

AI algorithms deployed at the edge can process and analyze data in real-time and this enables mobile edge computing to make intelligent decisions locally, reducing the need to transmit data to centralized cloud servers. For example, AI-powered edge devices can detect anomalies, recognize patterns and respond to events without relying on remote data centers. AI inference tasks, such as image recognition, natural language processing and predictive analytics can be performed at the edge.

AI-driven personalization and content recommendations can be delivered at the edge, enhancing user experiences in areas like content streaming, gaming and retail. AI algorithms analyze user behavior and preferences locally, enabling real-time adjustments and content delivery. AI-powered edge devices can identify and respond to security threats in real time. For example, AI algorithms can detect unusual network patterns, intrusions or malware at the edge, preventing potential security breaches before they reach the core network.

For instance, on 13 February 2023, AICRAFT, an Australian artificial intelligence (AI) company, has achieved a milestone by launching its edge computing module named Pulsar into space. The module, deployed as part of the JANUS-1 satellite, is designed to perform ultra-fast processing of space data using AI while consuming minimal power. During ground tests, it demonstrated the ability to classify 1,250 images of Earth Observation data in about 10 seconds.

Russia- Ukraine War Impact

In the global technology supply chain, Ukraine is a major player, particularly in the software development and IT outsourcing sectors. The battle could affect the availability of qualified software engineers and IT specialists, which could have an impact on the creation and upkeep of mobile edge computing systems. Geopolitical tensions and conflicts can lead to uncertainty in international business relationships.

In regions affected by conflict, the stability of critical infrastructure, including data centers and communication networks, may be at risk. Mobile edge computing relies on robust and secure infrastructure, so disruptions in conflict zones could impact mobile edge computing deployments. Geopolitical conflicts can raise concerns about data privacy and security, especially when data is processed at the edge. Organizations may become more cautious about where and how their data is processed, potentially affecting mobile edge computing adoption.

By Component

Software
Hardware
Services

By Organization Size

Large Enterprises
SMEs

By Application

Smart Cities
IoT
Content Delivery
Augmented Reality
Others

By End-User

Manufacturing
Energy and Utilities
Retail and Consumer Goods
Media and Entertainment
Transportation and Logistics
Others

By Region

North America
- U.S.
- Canada
- Mexico

Europe
- Germany
- UK
- France
- Italy
- Russia
- Rest of Europe

South America
- Brazil
- Argentina
- Rest of South America

Asia-Pacific
- China
- India
- Japan
- Australia
- Rest of Asia-Pacific

Middle East and Africa

Key Developments

In September 2021, AT&T, the Official 5G Innovation Partner of the WNBA, collaborated with the league to introduce a new fan experience called "AT&T 5G Game View" and this feature, available within the WNBA app, offers fans a more immersive way to engage with WNBA games.
In September 2022, Nokia is collaborating with Flex Brazil to deploy 5G Standalone (SA) private wireless networks in Flex's manufacturing facilities in Brazil. The partnership aims to explore 5G technology's potential in manufacturing, including reliable connectivity, data transfer and layout flexibility on the shop floor. Nokia's Digital Automation Cloud (Nokia DAC) will provide private wireless on-demand services, along with MX Industrial Edge computing and digital-enabling applications.
In October 2022, Verizon partnered with Reset Digital to pioneer a neuroprogrammatic approach to audience engagement. Reset Digital's Neuroprogrammatic TM advertising platform is a programmatic solution that enables brands to engage omnichannel audiences based on their motivations, allowing for broader and deeper audience reach across all communities, including underrepresented ones.

Why Purchase the Report?

To visualize the global mobile edge computing market segmentation based on component, organization size, application, end-user and region, as well as understand key commercial assets and players.
Identify commercial opportunities by analyzing trends and co-development.
Excel data sheet with numerous data points of mobile edge computing market-level with all segments.
PDF report consists of a comprehensive analysis after exhaustive qualitative interviews and an in-depth study.
Product mapping available as excel consisting of key products of all the major players.

The global mobile edge computing market report would provide approximately 69 tables, 71 figures and 199 Pages.

Target Audience 2023

Manufacturers/ Buyers
Industry Investors/Investment Bankers
Research Professionals
Emerging Companies

1. Methodology and Scope

1.1. Research Methodology
1.2. Research Objective and Scope of the Report

2. Definition and Overview

3. Executive Summary

3.1. Snippet by Component
3.2. Snippet by Organization Size
3.3. Snippet by Application
3.4. Snippet by End-User
3.5. Snippet by Region

4. Dynamics

4.1. Impacting Factors
- 4.1.1. Drivers
  - 4.1.1.1. Rising Application of 5G
  - 4.1.1.2. Adoption of Advanced Network Solutions
  - 4.1.1.3. Technology Advancement and Innovations
- 4.1.2. Restraints
  - 4.1.2.1. Limited Data Centers and Complex Servers
- 4.1.3. Impact Analysis

5. Industry Analysis

5.1. Porter's Five Force Analysis
5.2. Supply Chain Analysis
5.3. Pricing Analysis
5.4. Regulatory Analysis
5.5. Russia-Ukraine War Impact Analysis
5.6. DMI Opinion

6. COVID-19 Analysis

6.1. Analysis of COVID-19
- 6.1.1. Scenario Before COVID
- 6.1.2. Scenario During COVID
- 6.1.3. Scenario Post COVID
6.2. Pricing Dynamics Amid COVID-19
6.3. Demand-Supply Spectrum
6.4. Government Initiatives Related to the Market During Pandemic
6.5. Manufacturers Strategic Initiatives
6.6. Conclusion

7. By Component

7.1. Introduction
- 7.1.1. Market Size Analysis and Y-o-Y Growth Analysis (%), By Component
- 7.1.2. Market Attractiveness Index, By Component
7.2. Software*
- 7.2.1. Introduction
- 7.2.2. Market Size Analysis and Y-o-Y Growth Analysis (%)
7.3. Hardware
7.4. Services

8. By Organization Size

8.1. Introduction
- 8.1.1. Market Size Analysis and Y-o-Y Growth Analysis (%), By Organization Size
- 8.1.2. Market Attractiveness Index, By Organization Size
8.2. Large Enterprises*
- 8.2.1. Introduction
- 8.2.2. Market Size Analysis and Y-o-Y Growth Analysis (%)
8.3. SMEs

9. By Application

9.1. Introduction
- 9.1.1. Market Size Analysis and Y-o-Y Growth Analysis (%), By Application
- 9.1.2. Market Attractiveness Index, By Application
9.2. Smart Cities*
- 9.2.1. Introduction
- 9.2.2. Market Size Analysis and Y-o-Y Growth Analysis (%)
9.3. IoT
9.4. Content Delivery
9.5. Augmented Reality
9.6. Others

10. By End-User

10.1. Introduction
- 10.1.1. Market Size Analysis and Y-o-Y Growth Analysis (%), By End-User
- 10.1.2. Market Attractiveness Index, By End-User
10.2. Manufacturing*
- 10.2.1. Introduction
- 10.2.2. Market Size Analysis and Y-o-Y Growth Analysis (%)
10.3. Energy and Utilities
10.4. Retail and Consumer Goods
10.5. Media and Entertainment
10.6. Transportation and Logistics
10.7. Others

11. By Region

11.1. Introduction
- 11.1.1. Market Size Analysis and Y-o-Y Growth Analysis (%), By Region
- 11.1.2. Market Attractiveness Index, By Region
11.2. North America
- 11.2.1. Introduction
- 11.2.2. Key Region-Specific Dynamics
- 11.2.3. Market Size Analysis and Y-o-Y Growth Analysis (%), By Component
- 11.2.4. Market Size Analysis and Y-o-Y Growth Analysis (%), By Organization Size
- 11.2.5. Market Size Analysis and Y-o-Y Growth Analysis (%), By Application
- 11.2.6. Market Size Analysis and Y-o-Y Growth Analysis (%), By End-User
- 11.2.7. Market Size Analysis and Y-o-Y Growth Analysis (%), By Country
  - 11.2.7.1. U.S.
  - 11.2.7.2. Canada
  - 11.2.7.3. Mexico
11.3. Europe
- 11.3.1. Introduction
- 11.3.2. Key Region-Specific Dynamics
- 11.3.3. Market Size Analysis and Y-o-Y Growth Analysis (%), By Component
- 11.3.4. Market Size Analysis and Y-o-Y Growth Analysis (%), By Organization Size
- 11.3.5. Market Size Analysis and Y-o-Y Growth Analysis (%), By Application
- 11.3.6. Market Size Analysis and Y-o-Y Growth Analysis (%), By End-User
- 11.3.7. Market Size Analysis and Y-o-Y Growth Analysis (%), By Country
  - 11.3.7.1. Germany
  - 11.3.7.2. UK
  - 11.3.7.3. France
  - 11.3.7.4. Italy
  - 11.3.7.5. Russia
  - 11.3.7.6. Rest of Europe
11.4. South America
- 11.4.1. Introduction
- 11.4.2. Key Region-Specific Dynamics
- 11.4.3. Market Size Analysis and Y-o-Y Growth Analysis (%), By Component
- 11.4.4. Market Size Analysis and Y-o-Y Growth Analysis (%), By Organization Size
- 11.4.5. Market Size Analysis and Y-o-Y Growth Analysis (%), By Application
- 11.4.6. Market Size Analysis and Y-o-Y Growth Analysis (%), By End-User
- 11.4.7. Market Size Analysis and Y-o-Y Growth Analysis (%), By Country
  - 11.4.7.1. Brazil
  - 11.4.7.2. Argentina
  - 11.4.7.3. Rest of South America
11.5. Asia-Pacific
- 11.5.1. Introduction
- 11.5.2. Key Region-Specific Dynamics
- 11.5.3. Market Size Analysis and Y-o-Y Growth Analysis (%), By Component
- 11.5.4. Market Size Analysis and Y-o-Y Growth Analysis (%), By Organization Size
- 11.5.5. Market Size Analysis and Y-o-Y Growth Analysis (%), By Application
- 11.5.6. Market Size Analysis and Y-o-Y Growth Analysis (%), By End-User
- 11.5.7. Market Size Analysis and Y-o-Y Growth Analysis (%), By Country
  - 11.5.7.1. China
  - 11.5.7.2. India
  - 11.5.7.3. Japan
  - 11.5.7.4. Australia
  - 11.5.7.5. Rest of Asia-Pacific
11.6. Middle East and Africa
- 11.6.1. Introduction
- 11.6.2. Key Region-Specific Dynamics
- 11.6.3. Market Size Analysis and Y-o-Y Growth Analysis (%), By Component
- 11.6.4. Market Size Analysis and Y-o-Y Growth Analysis (%), By Organization Size
- 11.6.5. Market Size Analysis and Y-o-Y Growth Analysis (%), By Application
- 11.6.6. Market Size Analysis and Y-o-Y Growth Analysis (%), By End-User

12. Competitive Landscape

12.1. Competitive Scenario
12.2. Market Positioning/Share Analysis
12.3. Mergers and Acquisitions Analysis

13. Company Profiles

13.1. Advantech Co., Ltd.*
- 13.1.1. Company Overview
- 13.1.2. Product Portfolio and Description
- 13.1.3. Financial Overview
- 13.1.4. Key Developments
13.2. Johnson Controls International plc
13.3. Hewlett Packard Enterprise Development LP
13.4. Huawei Technologies Co., Ltd.
13.5. Juniper Networks, Inc.
13.6. SAGUNA Network LTD
13.7. SMART Global Holdings, Inc.
13.8. Vapor IO, Inc.
13.9. Nokia Corporation
13.10. Skyvera

LIST NOT EXHAUSTIVE