This mobile edge computing market report evaluates the telecom and IT ecosystem in support of communications and computing infrastructure providers, managed services vendors, carriers, and OTT providers. This edge computing market analysis includes a focus on company strategies and offerings relative to current and anticipated future market needs.
The report also provides quantitative analysis of the MEC market including segmentation by industry vertical, region of the world, application, and services. It also provides forecasts for MEC-based streaming data and real-time data analytics.
Select Report Findings
- Mobile edge computing will be a key enabler of immersive technologies deployed with 5G
- Greatest opportunities will be in teleoperation/cloud robotics, telepresence, and virtual reality
- The global mobile edge computing market for software and APIs will reach $3.16 billion by 2028
- The market for MEC software in support of IoT applications will reach $721 million globally by 2028
- The largest industry vertical opportunities for MEC will be manufacturing, healthcare and automobile
Often used synonymously, MEC refers to Mobile Edge Computing or Multi-Access Edge Computing with the former being more cellular network-centric (LTE and 5G) and the latter terminology adopted by standards groups to generalize edge computing to reflect that it may be also be used by WiFi and other wireless access technologies. The distinction between Multi-Access Edge Computing vs. Mobile Edge Computing for MEC largely ends with radio access and network type as almost every other aspect is the same including localizing computing (e.g. computation and storage closer to the end-user), network element virtualization, software, and service-centric operations.
In cellular networks, edge computing via MEC is beneficial for LTE but virtually essential for 5G. This is because Mobile Edge Computing facilitates optimization of fifth generation network resources including focusing communications and computational capacity where it is needed the most. The author's research findings indicate a strong relationship between edge computing and 5G. In fact, if it were not for MEC, 5G would continue to rely upon back-haul to centralized cloud resources for storage and computing, diminishing much of the otherwise positive impact of latency reduction enabled by 5G.
Another driver for the multi-access edge computing market is that MEC will facilitate an entirely new class of low-power devices for IoT networks and systems. These devices will rely upon MEC equipment for processing. Stated differently, some IoT devices will be very lightweight computationally speaking, relying upon edge computing nodes for most of their computation needs.
Mobile Edge Computing Market Drivers
The fundamental question often asked by those not close to telecom networks and application optimization is: What is driving the need for edge computing in data centers? There are many reasons. However, the core areas for improvement with mobile edge computing are: throughput, congestion, latency, and backhaul.
Additional important considerations that spawn from these improvements are as follows:
- Improved Overall Throughput: By way of example, testing between Saguna Networks and Vodafone indicated substantially lower wait times and stalls while viewing video.
- Core Congestion Reduction: Related to improved throughput is the reduction of core congestion. MEC enables users and devices to store/access much higher volumes of data by way of direct access to the Internet rather than relying upon transport through the core of cellular networks.
- Application Latency Reduction: Mobile edge computing will be particularly important in support of Ultra-Reliable and Low-Latency Communication (URLLC) for latency-sensitive apps and services for various consumer, enterprise, and industrial use cases. The combination of 5G and MEC is expected to reduce network latency significantly, which will enable many previously tethered-only applications and services such as streaming 4K video, real-time remote control, haptic or tactile communications, and more.
- Backhaul Reduction: Related to core congestion reduction, backhaul is reduced as processing may be done at the edge rather than back-hauled to more centralized core cloud computing resources. This will be particularly important for 5G, which would continue to rely upon back-haul to centralized cloud resources for storage and computing, diminishing much of the otherwise positive impact of latency reduction enabled by 5G new radio technology.
- Network Awareness and Context: Placing Virtual Network Functions closer to the point of usage allows carriers to better determine context, leading to operational improvements and better use of localized data.
- Streaming Data and Real-time Analytics: Edge computing facilitates vast amounts of fast-moving data from sensors and devices. For many use cases, data flows constantly from the device or sensor to the network and sometimes back to the device. In some cases, these streams of data are simply stored (for potential later use) and in other cases, there is a need for real-time data processing and analytics.
- Network and Application Resiliency: Edge computing networks are distributed and thus more resilient because there are many mini-data centers rather than one or a few larger ones.
Despite all of the aforementioned advantages of deploying distributed computing and mini-datacenters, there is at least one important concern - cybersecurity. With mobile edge computing, security becomes a problem as there is now another point of attack with edge hardware and software. However, the aforementioned advantages provide ample rationale to move forward for carriers and data center providers alike.
Weighing the advantages vs. the challenges, the multi-access edge computing market will clearly be an enabler of 5G apps and services including improved mobile broadband (ultra-fast and high definition video, enhanced web browsing, etc.), Ultra-Reliable Low Latency Communications (URLLC) dependent apps (virtual reality, UAV operation, autonomous vehicles, robotics, etc.), and massive expansion of the Internet of Things (IoT).
In terms of IoT, one of the key drivers for the multi-access edge computing market is that MEC will facilitate an entirely new class of low-power devices for IoT networks and systems. These devices will rely upon MEC equipment for processing. Stated differently, some IoT devices will be very lightweight computationally speaking, relying upon edge computing nodes for most of their computation needs.
Mobile Edge Computing Market Deployment Alternatives
As the author has stated in the past, the primary standards body for MEC standardization is the European Telecommunications Standards Institute (ETSI), which has done much to move edge computing in mobile/wireless networks forward.
ETSI identifies four physical areas for MEC deployment as follows:
- Co-location at Base Station
- Co-location at Transmission Node
- Co-location at Network Aggregation Point
- Co-location with Core Network Functions
This ETSI document was authored by representatives from leading ICT companies including Huawei, HPE, Telefonica, ZTE, Viavi Solutions, Saguna, ETRI, Nokia, Vodafone, Quortus, Interdigital, Intel, TIM, and ITRI. Additional MEC deployment-related items covered include mobile edge computing architecture relative to 5G networks and systems as well as MEC use case scenarios.
An additional industry group that also has an impact on edge computing is the Central Office Re-architected as a Data Center (CORD) supported by AT&T, China Unicom, NTT Communications, SK Telecom, and Verizon. CORD has identified a few potential points of deployment for mobile edge computing platforms including enterprise sites, hub sites, cloud RAN sites, pre-aggregation sites, IP aggregation sites, and co-located with core network equipment.
Among other documents, CORD has issued M-CORD as an Open Reference Solution for 5G Enablement, which they position as an open-source reference solution for mobile edge computing deployment alternatives that is built on the pillars of SDN, NFV and cloud technologies. The organization also provides guidance regarding mobile edge computing operations, installation, development, and testing.
Another organization involved in MEC architecture and datacenter evolution is the O-RAN Alliance, which is developing an architecture designed to enable next-generation Radio Access Network (RAN) infrastructures. Founded by AT&T, China Mobile, Deutsche Telekom, NTT DoCoMo, and Orange, the O-RAN Alliance defines a cloud-native RAN that leverages MEC. The organization sees the potential to embed intelligence in every layer of the RAN architecture. Part of this intelligence could be within the edge computing equipment, supported with AI-optimized closed-loop automation software control.
Depending on the vendor, there are many different views. For example, Vapor IO, who recently purchased the edge co-location business from one of its investors, Crown Castle, sees the most distributed approach with MEC at every base station. To get there, the company sees interim steps such as building a nationwide network of edge data centers throughout major metropolitan areas in the United States. The company will interconnect edge computing sites within a city to form a larger, virtual data center the company refers to as Vapor Kinetic Edge that covers an entire metro area.
While this logical extreme may ultimately come to fruition, other companies, such as Saguna Networks, see a large role for enterprise-deployed MEC, particularly in conjunction with private LTE and 5G deployments. Other vendors such as Deutsche Telekom backed MobiledgeX (recently acquired by Google) also see a strong mobile edge computing market for enterprise and industrial applications such as smart buildings and smart factories respectively.
In this business-owned/controlled edge computing market model, the carriers will minimally provide a network as a service (via connectivity and communications services) solution and potentially a certain degree of computing as a service. However, it is likely that many enterprise and industrial customers may manage their own apps and/or allow access by third parties via edge computing APIs for provisioning, administration, and overall management.
Carrier Mobile Edge Computing Market Deployment Considerations
It is important to understand that multi-access edge computing servers and platforms can be deployed in many locations including, but not limited to, an LTE and/or 5G macro base station site, the 3G Radio Network Controller site, a multi-RAT cell aggregation site, or at an aggregation point. Communication Service Providers (CSP) are not accustomed to planning for remote servers.
However, MEC essentially needs many remote data centers. The author predicts that CSPs will need to partner with network integration companies to realize the full vision of MEC. CSPs cannot be bogged down in negotiations, planning, engineering, and deployment of MEC communications/computing platforms every time a new site is acquired.
With the multi-access edge computing market, there is clearly a new computational-communications paradigm in which communications and computing are no longer thought of as separate things. Furthermore, they are planned, engineered, deployed, and operated together. In parallel with this new paradigm, mobile networks are becoming video networks.
This is essentially the case because the vast majority of bandwidth demand is driven by video usage of some type. This is anticipated to accelerate with MEC as there will be many more uses for video, such as public safety (e.g. face recognition to identify potential threats). With this new paradigm, there will be a need for more efficient management of real-time data and analytics as vast amounts of data is collected, much of which will require real-time processing.
Implementation and operation of multi-access edge computing have profound implications. For example, there will not be a need to always route completely through the entire switching fabric for Internet transport. In other words, certain content and applications can be consumed locally rather than relying upon back-hauling and/or hair-pinning through a home gateway to the (centralized/core) cloud.
This environment is characterized by ultra-low latency and high bandwidth as well as real-time access to radio network information that can be leveraged by applications and QoE platforms located "deep into the network". Better performance through partial off-load from device to edge or centralized cloud to edge. One good example app that will benefit from this is cloud gaming.
Companies in Report:
- ADLINK Technology Inc.
- Advanced Micro Devices
- Advantech
- Affirmed Networks
- Akamai Technologies
- Allot Communications
- AT&T
- Brocade Communications Systems
- Cavium Networks
- Ceragon Networks
- China Mobile
- China Unicom
- Cisco Systems
- Cloudify
- Cradlepoint
- Deutsche Telekom
- EdgeConneX
- Edgeworx
- Ericsson
- ETRI
- Fujitsu Technology Solutions
- Hewlett Packard Enterprise (HPE)
- Huawei Technologies Co. Ltd.
- IBM Corporation
- Integrated Device Technology
- Intel Corporation
- InterDigital Inc.
- ITRI
- Juniper Networks
|
- Mimic Technology
- MobiledgeX (Google)
- NEC Corporation
- Nokia Corporation
- NTT Communications
- NTT DoCoMo
- Orange
- Ori
- PeerApp Ltd.
- Pixeom
- Pluribus Networks
- Quortus
- Redhat, Inc.
- Saguna Networks
- Samsung Electronics Co. Ltd.
- SK Telecom
- Sony Corporation
- SpiderCloud Wireless
- Telefonica
- TIM
- Vapor IO
- Vasona Networks (ZephyrTel)
- Verizon
- Viavi Solutions
- Vodafone
- Xilinx, Inc.
- Yaana Ltd.
- ZTE Corporation
|
Table of Contents
1. Executive Summary
2. Introduction
- 2.1. Understanding Multi-Access Edge Computing
- 2.1.1. Edge Computing in an ICT Context
- 2.1.2. Proximity Computing: The Edge in Physical and Logical Context
- 2.1.3. Edge Computing vs. Other Computational Approaches
- 2.1.4. Multi-access Edge Computing
- 2.2. Important Characteristics of MEC
- 2.2.1. Processing at the Edge
- 2.2.2. Low Latency
- 2.2.3. Context Based
- 2.2.4. Location and Analytics
- 2.3. Multi-Access Edge Computing Benefits
- 2.3.1. Business Benefits
- 2.3.2. Technical Benefits
- 2.3.3. Mobile Network Operator Benefits
- 2.3.4. Key Element of Carrier Heterogeneous Network Strategy
3. MEC Technology, Platforms, and Architecture
- 3.1. MEC Platform Architecture Building Blocks
- 3.1.1. MEC Infrastructure
- 3.1.2. MEC Application Platforms
- 3.1.3. MEC Management Framework
- 3.2. Edge Cloud Computing Value Chain
- 3.3. MEC Technology Building Blocks
- 3.3.1. Radio Network Information Service
- 3.3.2. Traffic Offload Function
- 3.3.3. MEC Interfaces
- 3.3.4. Configuration Management
- 3.3.5. Application Lifecycle Management
- 3.3.6. VM Operations and Management
- 3.3.7. Hardware Virtualization and Infrastructure Management
- 3.3.8. Core Network Elements
- 3.3.9. Open Standards
- 3.4. MEC Technology Enablers
- 3.4.1. Mobile Computing to Mobile Cloud Computing
- 3.4.2. Cloudlet based Mobile Cloud Computing
- 3.4.3. Cloudlet to Cloud
- 3.4.4. PacketCloud Open Platform for Cloudlets
- 3.4.5. Enterprise Cloud Architecture
- 3.4.6. Cloudlet Solutions
- 3.4.7. Cloudlet Storage Frameworks
- 3.5. MEC Deployment Considerations
- 3.5.1. MEC Implementation Challenges
- 3.5.2. MEC Operational Challenges
4. MEC Market Drivers and Opportunities
- 4.1. Limitations of Cloud Convergence
- 4.2. IT and Telecom Network Convergence
- 4.3. Base Station Evolution
- 4.4. Cell Aggregation
- 4.5. Virtualization in the Cloud
- 4.6. Continually Improving Server Capacity
- 4.7. Data Center to Network Interactions
- 4.8. Open and Flexible App and Service Ecosystem
- 4.9. Fifth Generation Wireless
- 4.10. Edge Cloud and Data Transferability
- 4.11. Proximate Cloud Computing
- 4.12. Increasingly Faster Content Delivery
- 4.13. Advantages of MEC Small Cell Deployment
- 4.14. Overall Mobile Data Demand
- 4.15. Low Latency Applications
- 4.16. Integration of MEC with Cloud RAN
- 4.17. MEC Enhances Real-time Data and Analytics
- 4.17.1. Why Data at the Edge?
- 4.17.2. Convergence of Distributed Cloud and Big Data
5. MEC Ecosystem
- 5.1. Overall Edge Computing Ecosystem
- 5.2. MEC Ecosystem Players
- 5.2.1. ETSI MEC ISG
- 5.2.2. Software and ASPs
- 5.2.3. OTT Service and Content Providers
- 5.2.4. Network Infrastructure and Equipment Providers
- 5.2.5. Mobile Network Operators
- 5.3. Individual Company Analysis
- 5.3.1. ADLINK Technology Inc.
- 5.3.1.1. Company Profile
- 5.3.1.2. Recent Developments
- 5.3.2. Advantech
- 5.3.2.1. Company Profile
- 5.3.2.1. Recent Developments
- 5.3.3. Affirmed Networks
- 5.3.3.1. Company Profile
- 5.3.3.1. Recent Developments
- 5.3.4. Akamai Technologies
- 5.3.4.1. Company Profile
- 5.3.4.2. Recent Developments
- 5.3.5. Allot Communications
- 5.3.6. Advanced Micro Devices
- 5.3.6.1. Company Profile
- 5.3.6.2. Recent Developments
- 5.3.7. Brocade Communications Systems
- 5.3.7.1. Company Profile
- 5.3.7.2. Recent Developments
- 5.3.8. Cavium Networks
- 5.3.8.1. Company Profile
- 5.3.8.2. Recent Developments
- 5.3.9. Ceragon Networks
- 5.3.9.1. Company Profile
- 5.3.9.2. Recent Developments
- 5.3.10. Cisco Systems
- 5.3.10.1. Company Profile
- 5.3.10.2. Recent Developments
- 5.3.11. Cloudify
- 5.3.11.1. Company Profile
- 5.3.11.2. Recent Developments
- 5.3.12. Cradlepoint
- 5.3.12.1. Company Profile
- 5.3.12.2. Recent Developments
- 5.3.13. EdgeConneX
- 5.3.13.1. Company Profile
- 5.3.13.2. Recent Developments
- 5.3.14. Edgeworx
- 5.3.14.1. Company Profile
- 5.3.14.2. Recent Developments
- 5.3.15. Ericsson
- 5.3.15.1. Company Profile
- 5.3.15.2. Recent Developments
- 5.3.16. Fujitsu Technology Solutions
- 5.3.16.1. Company Profile
- 5.3.16.2. Recent Developments
- 5.3.17. Hewlett Packard Enterprise
- 5.3.17.1. Company Profile
- 5.3.17.2. Recent Developments
- 5.3.18. Huawei Technologies Co. Ltd.
- 5.3.18.1. Company Profile
- 5.3.18.2. Recent Developments
- 5.3.19. IBM Corporation
- 5.3.19.1. Company Profile
- 5.3.19.2. Recent Developments
- 5.3.20. Integrated Device Technology
- 5.3.20.1. Company Profile
- 5.3.20.2. Recent Developments
- 5.3.21. Intel Corporation
- 5.3.21.1. Company Profile
- 5.3.21.2. Recent Developments
- 5.3.22. InterDigital Inc.
- 5.3.22.1. Company Profile
- 5.3.22.2. Recent Developments
- 5.3.23. Juniper Networks
- 5.3.23.1. Company Profile
- 5.3.23.2. Recent Developments
- 5.3.24. Mimic Technology
- 5.3.24.1. Company Profile
- 5.3.24.2. Recent Developments
- 5.3.25. MobiledgeX
- 5.3.25.1. Company Profile
- 5.3.25.2. Recent Developments
- 5.3.26. NEC Corporation
- 5.3.26.1. Company Profile
- 5.3.26.2. Recent Developments
- 5.3.27. Nokia Corporation
- 5.3.27.1. Company Profile
- 5.3.27.2. Recent Developments
- 5.3.28. Ori
- 5.3.28.1. Company Profile
- 5.3.28.2. Recent Developments
- 5.3.29. PeerApp Ltd.
- 5.3.29.1. Company Profile
- 5.3.29.2. Recent Developments
- 5.3.30. Pixeom
- 5.3.30.1. Company Profile
- 5.3.30.2. Recent Developments
- 5.3.31. Pluribus Networks
- 5.3.31.1. Company Profile
- 5.3.31.2. Recent Developments
- 5.3.32. Quortus
- 5.3.32.1. Company Profile
- 5.3.32.2. Recent Developments
- 5.3.33. Redhat, Inc.
- 5.3.33.1. Company Profile
- 5.3.33.2. Recent Developments
- 5.3.34. Saguna Networks
- 5.3.34.1. Company Profile
- 5.3.34.2. Recent Developments
- 5.3.35. Samsung Electronics Co., Ltd.
- 5.3.35.1. Company Profile
- 5.3.35.2. Recent Developments
- 5.3.36. Sony Corporation
- 5.3.36.1. Company Profile
- 5.3.36.2. Recent Developments
- 5.3.37. SpiderCloud Wireless
- 5.3.37.1. Company Profile
- 5.3.37.2. Recent Developments
- 5.3.38. Vapor IO
- 5.3.38.1. Company Profile
- 5.3.38.2. Recent Developments
- 5.3.39. Vasona Networks (ZephyrTel)
- 5.3.39.1. Company Profile
- 5.3.39.2. Recent Developments
- 5.3.40. Xilinx, Inc.
- 5.3.40.1. Company Profile
- 5.3.40.2. Recent Developments
- 5.3.41. Yaana Ltd.
- 5.3.41.1. Company Profile
- 5.3.42. ZTE Corporation
- 5.3.42.1. Company Profile
- 5.3.42.2. Recent Developments
6. MEC Application and Service Strategies
- 6.1. Optimizing the Mobile Cloud
- 6.1.1. Mobile Network Operator Strategies
- 6.1.2. Service Strategies and End-user Demand
- 6.2. Context Aware Services
- 6.2.1. Commerce
- 6.2.2. Education
- 6.2.3. Gaming
- 6.2.4. Healthcare
- 6.2.5. Location-based Services
- 6.2.6. Public Safety
- 6.2.7. Connected Vehicles
- 6.2.8. Wearables
- 6.3. Data Services and Analytics
- 6.3.1. Localized Real-time Data Becomes King
- 6.3.2. Anonymizing Local and Real-time Data for Third-party Usage
- 6.3.3. Increasing Demand for Data as a Service (DaaS) in MEC Environment
7. Multi-Access Edge Computing Deployment
8. Multi-Access Edge Computing Market Analysis and Forecasts
- 8.1. Mobile Edge Computing Markets by Components
- 8.1.1. Mobile Edge Computing Cloud Server Market by Category
- 8.1.2. Mobile Edge Computing Equipment Market by Category
- 8.1.3. Mobile Edge Computing Platform Market by Category
- 8.1.4. Mobile Edge Computing Software and API Market in Vertical Segment
- 8.1.5. Mobile Edge Computing as a Service Market by Solution Type
- 8.2. Mobile Edge Computing Users by Supporting Network
- 8.3. Mobile Edge Computing Markets by Technology
- 8.4. Mobile Edge Computing Markets by Analytics Type
- 8.5. Mobile Edge Computing Markets by Applications
- 8.6. Mobile Edge Computing by Market Segment
- 8.7. Mobile Edge Computing Markets by Industry Vertical
- 8.8. Regional Mobile Edge Computing Markets
- 8.8.1. North America Mobile Edge Computing Market
- 8.8.1.1. Mobile Edge Computing Market Size by Segment
- 8.8.1.2. Mobile Edge Computing Cloud Server Market by Category
- 8.8.1.3. Mobile Edge Computing Equipment Market by Category
- 8.8.1.4. Mobile Edge Computing Platform Market by Category
- 8.8.1.5. North America MEC Software and API Market by Solution
- 8.8.1.6. Mobile Edge Computing as a Service Market by Type
- 8.8.1.7. Mobile Edge Computing Markets by Industry Vertical
- 8.8.2. Europe Mobile Edge Computing Market
- 8.8.2.1. Mobile Edge Computing Market Size by Segment
- 8.8.2.2. Mobile Edge Computing Cloud Server Market by Category
- 8.8.2.3. Mobile Edge Computing Equipment Market by Category
- 8.8.2.4. Mobile Edge Computing Platform Market by Category
- 8.8.2.5. Mobile Edge Computing Software & API Market in Vertical Segment
- 8.8.2.6. Mobile Edge Computing as a Service Market by Type
- 8.8.2.7. Mobile Edge Computing Markets by Industry
- 8.8.3. APAC Mobile Edge Computing Market
- 8.8.3.1. Mobile Edge Computing Market Size by Segment
- 8.8.3.2. Mobile Edge Computing Cloud Server Market by Category
- 8.8.3.3. Mobile Edge Computing Equipment Market by Category
- 8.8.3.4. Mobile Edge Computing Platform Market by Category
- 8.8.3.5. Mobile Edge Computing Software and API Market in Vertical Segment
- 8.8.3.6. Mobile Edge Computing as a Service Market by Type
- 8.8.3.7. Mobile Edge Computing Markets by Industry
9. Conclusions and Recommendations
- 9.1. Anticipated Market Needs and Opportunities
- 9.1.1. The need for MEC Integration with Public Cloud Platforms
- 9.1.2. Enterprise (Dedicated and Shared Resources) MEC Integration
- 9.1.3. Dedicated MEC Public Safety and Homeland Security Infrastructure
- 9.2. Insights into Future Market Dynamics
- 9.2.1. MEC will Facilitate Downward Price Pressure on Non-real-time Data
- 9.2.2. MEC will Drive Demand for Virtual Network Operators
- 9.2.3. MEC will Drive the Need for New Players as well as M&A
- 9.2.4. MEC Deployment will be Very Different across Market Segments
- 9.2.5. Anticipated MEC Business Models
10. Appendix One: Real-time Data Analytics Revenue
- 10.1. Global Streaming Data Analytics Revenue
- 10.2. Global Real-time Data Analytics Revenue by App, Software, and Services
- 10.3. Global Real-time Data Analytics Revenue in Industry Verticals
- 10.3.1. Real-time Data Analytics Revenue in Retail
- 10.3.1.1. Real-time Data Analytics Revenue by Retail Segment
- 10.3.1.2. Real-time Data Analytics Retail Revenue by App, Software, and Service
- 10.3.2. Real-time Data Analytics Revenue in Telecom and IT
- 10.3.2.1. Real-time Data Analytics Revenue by Telecom and IT Segment
- 10.3.2.2. Real-time Data Analytics Revenue by Telecom & IT App, Software, and Service
- 10.3.3. Real-time Data Analytics Revenue in Energy and Utility
- 10.3.3.1. Real-time Data Analytics Revenue by Energy and Utility Segment
- 10.3.3.2. Real-time Data Analytics Energy and Utilities Revenue by App, Software, and Service
- 10.3.4. Real-time Data Analytics Revenue in Government
- 10.3.4.1. Real-time Data Analytics Revenue by Government Segment
- 10.3.4.2. Real-time Data Analytics Government Revenue by App, Software, and Service
- 10.3.5. Real-time Data Analytics Revenue in Healthcare and Life Science
- 10.3.5.1. Real-time Data Analytics Revenue by Healthcare Segment
- 10.3.6. Real-time Data Analytics Revenue in Manufacturing
- 10.3.6.1. Real-time Data Analytics Revenue by Manufacturing Segment
- 10.3.6.2. Real-time Data Analytics Manufacturing Revenue by App, Software, and Service
- 10.3.7. Real-time Data Analytics Revenue in Transportation and Logistics
- 10.3.7.1. Real-time Data Analytics Revenue by Transportation & Logistics Segment
- 10.3.7.2. Real-time Data Analytics Transportation & Logistics Revenue by App, Software, and Service
- 10.3.8. Real-time Data Analytics Revenue in Banking and Finance
- 10.3.8.1. Real-time Data Analytics Revenue by Banking and Finance Segment
- 10.3.8.2. Real-time Data Analytics Revenue by Finance App, Software, and Service
- 10.3.9. Real-time Data Analytics Revenue in Smart Cities
- 10.3.9.1. Real-time Data Analytics Revenue by Smart City Segment
- 10.3.9.2. Real-time Data Analytics Revenue by Smart City App, Software, and Service
- 10.3.10. Real-time Data Analytics Revenue in Automotive
- 10.3.10.1. Real-time Data Analytics Revenue by Automobile Industry Segment
- 10.3.10.2. Real-time Data Analytics Revenue by Automotive Industry App, Software, and Service
- 10.3.11. Real-time Data Analytics Revenue in Education
- 10.3.11.1. Real-time Data Analytics Revenue by Education Industry Segment
- 10.3.11.2. Real-time Data Analytics Revenue by Education Industry App, Software, and Service
- 10.3.12. Real-time Data Analytics Revenue in Outsourcing Services
- 10.3.12.1. Real-time Data Analytics Revenue by Outsourcing Segment
- 10.3.12.2. Real-time Data Analytics Revenue by Outsourcing Industry App, Software, and Service
- 10.4. Real-time Data Analytics Revenue by Leading Vendor Platform
- 10.5. Global Investment in Data by Industry Sector
11. MEC Case Studies
- 11.1. Automotive
- 11.2. Financial Sector
- 11.3. Healthcare
- 11.4. Smart Cities
- 11.5. Industrial Manufacturing
- 11.6. Augmented Virtual Reality
12. Appendix Two: 5G Technology and Solution Outlook
- 12.1. 5G Market Defining Solutions
- 12.2. Evolution of Mobile Communication Standards (1G to 5G)
- 12.3. Introduction to 5G Technology
- 12.4. 5G Spectrum Options and Utilization
- 12.5. What 5G Technology will Provide
- 12.5.1. Faster Data Speeds and Less Expensive Services
- 12.5.2. Emerging Business Models
- 12.6. Key Advantages and Growth Drivers of 5G
- 12.7. 5G Challenges
- 12.7.1. Consistent Growth in Technology Requirements and Service Characteristics
- 12.7.2. Standardization Challenges
- 12.7.3. Network Challenges
- 12.7.4. Mobile Device Challenges
- 12.7.5. Application Challenges
- 12.8. 5G Roadmap
- 12.8.1. 5G Requirements
- 12.8.2. 5G Wireless Subsystem
- 12.8.3. Network Virtualization & Software Networks
- 12.8.4. Converged Connectivity
- 12.9. 5G Use Cases
- 12.9.1. 5G in M2M and IoT
- 12.9.2. 5G in Robotics
- 12.9.3. 5G in Augmented and Virtual Reality
- 12.9.4. 5G in Home Internet
- 12.9.5. 5G in Wireless Office
- 12.9.6. Other Use Cases
- 12.9.6.1. High Speed Train
- 12.9.6.2. Remote Computing
- 12.9.6.3. Non-Stationary Hot Spots
- 12.9.6.4. 3D Connectivity: Aircraft
- 12.9.6.5. Natural Disaster
- 12.9.6.6. Public Safety
- 12.9.6.7. Context Aware Service
- 12.10. Business Opportunities