The emerging MEC service environment will facilitate a seamless access experience, dramatically lower latency, and improve capacity optimization for content, services, and applications. Mobile Network Operators (MNO) have the opportunity to play a greater role in the emerging MEC ecosystem as they can add value through optimized apps and content. MNOs also have the opportunity to realize improved ROI in their LTE and 5G network investments through improved data efficiency and ability to deliver capacity on-demand when and where it is needed.
ETSI has recently redefined MEC to account for addressing multiple MEC hosts being deployed in many different networks, owned by various operators and running edge applications in a collaborative manner. This new view of MEC is why the term Multi-access is used as there is now a focus upon many different means of accessing the edge including Heterogeneous Networks (HetNet) using various evolved versions of LTE, 5G technologies including millimeter wave RF, fixed wireless deployments, WiFi, and more. This new view of MEC also means that standards will evolve to encompass all different types of Communication Service Providers (CSP) and not just cellular carriers.
This research evaluates MEC technology, architecture and building blocks, ecosystem, market drivers, applications, solutions, and deployment challenges. The report also analyzes MEC industry initiatives, leading companies, and solutions. The report includes a market assessment and forecast for MEC users/devices within CSP networks and MEC revenue globally, regionally, and within the enterprise market for years 2017 to 2022.
This research also evaluates the technologies, companies, and solutions that leverage edge computing for real-time IoT data processing and analytics. The report assesses challenges and opportunities associated with realizing business value from real-time analytics. The report provides detailed forecasts globally, regionally, and across industry verticals and solution categories for 2017 to 2022.
Key Topics Covered:
Multi-access Edge Computing 2017 - 2022
1 Executive Summary
2 Introduction 2.1 Understanding Multi-access Edge Computing 2.1.1 Edge Computing 2.1.2 Edge Computing vs. Cluster Computing 2.1.3 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 MEC Benefits 2.3.1 Business Benefits 2.3.2 Technical Benefits 2.3.3 Mobile Network Operator Benefits
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 MEC Value Chain for Edge Cloud Computing 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 Akamai Cloudlet Solution 3.4.7 OPENi Cloudlet Storage Framework 3.5 MEC Deployment
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 (5G) 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
5 MEC Ecosystem 5.1 Network Ecosystem 5.2 MEC Ecosystem Players 5.2.1 Software and ASPs 5.2.2 OTT Service and Content Providers 5.2.3 Network Infrastructure and Equipment Providers 5.2.4 Mobile Network Operators
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
7 MEC Market Forecasts 2017 - 2022 7.1 Global Market 2017 - 2022 7.1.1 Combined MEC Market 7.1.2 MEC Market by Segment 7.1.3 MEC Enterprise CAPEX and OPEX Spend 7.1.4 MEC Network Migration 7.1.5 MEC Enterprise Adoption 7.2 MEC Regional Market 2017 - 2022 7.3 MEC Network Users/Devices 2017 - 2022 7.3.1 Global MEC Network Users/Devices 7.3.2 MEC Network User by Supporting Network 7.3.3 Regional MEC Network User
8 Conclusions and Recommendations
Streaming IoT Data Market Outlook and Forecasts 2017 - 2022
1 Introduction 1.1 Research Background 1.2 Research Scope 1.3 Target Audience 1.4 Companies Covered
2 Executive Summary
3 Overview 3.1 Understanding IoT Data 3.1.1 IoT Data vs. other Unstructured Data 3.1.2 Key IoT Data Characteristics 184.108.40.206 IoT Data is Real Time 220.127.116.11 Massive Volumes of IoT Data 18.104.22.168 IoT Data Generates Useful Insights 3.2 IoT Data Management Operations 3.2.1 Basic Data Implementation and Operational Challenges 22.214.171.124 IoT Data Scalability 126.96.36.199 IoT Data Integration 3.2.2 Data Management and Processing Raw Data 3.2.3 Centralized Storage and Decentralized Processing 3.2.4 Accessing and Exchanging IoT Data via APIs 3.2.5 Data Security and Personal Information Privacy 3.4 Market Outlook for IoT Data Analytics 3.4.1 IoT Data Management is a Ubiquitous Opportunity across Enterprise 3.4.2 IoT Data becomes a Big Revenue Opportunity by 2022 3.4.3 Organizations increasing Adopt Predictive Analytics with IoT Data 3.5 Real-time Streaming IoT Data Analytics becoming a Substantial Business Opportunity
4 Vendor Analysis 4.1 Accenture 4.2 AGT International 4.3 Bosch Software Innovations 4.4 Capgemini 4.5 Cisco Systems, Inc. 4.6 GE Digital 4.7 Google 4.8 Intel Corporation 4.9 Lynx Software Technologies, Inc. 4.10 Maana, Inc. 4.11 Microsoft Corporation 4.12 MongoDB Inc. 4.13 ParStream (Cisco) 4.14 PTC 4.15 RIOT 4.16 SAP SE 4.17 SQLstream, Inc. 4.18 Tellient 4.19 Teradata Corporation 4.20 Wind River
5 Streaming IoT Data Analytics Revenue 2017 - 2022 5.1 Global Streaming Data Analytics Revenue for IoT 5.2 Global Streaming IoT Data Analytics Revenue by App, Software, and Services 5.3 Global Streaming IoT Data Analytics Revenue in Industry Verticals 5.3.1 Streaming IoT Data Analytics Revenue in Retail 5.3.2 Streaming IoT Data Analytics Revenue in Telecom and IT 5.3.3 Streaming IoT Data Analytics Revenue in Energy and Utility 5.3.4 Streaming IoT Data Analytics Revenue in Government 5.3.5 Streaming IoT Data Analytics Revenue in Healthcare and Life Science 5.3.6 Streaming IoT Data Analytics Revenue in Manufacturing 5.3.7 Streaming IoT Data Analytics Revenue in Transportation & Logistics 5.3.8 Streaming IoT Data Analytics Revenue in Banking and Finance 5.3.9 Streaming IoT Data Analytics Revenue in Smart Cities 5.3.10 Streaming IoT Data Analytics Revenue in Automotive 5.3.11 Streaming IoT Data Analytics Revenue in Education 5.3.12 Streaming IoT Data Analytics Revenue in Outsourcing Services 5.4 Streaming IoT Data Analytics Revenue by Leading Vendor Platform 5.4.1 Global Investment in IoT Data by Industry Sector 2017 - 2022
6 Appendix 6.1 Regional Streaming IoT Data Analytics Revenue 2017 - 2022 6.1.1 Revenue in Region 6.2 Streaming IoT Data Analytics Revenue by Country 2017 - 2022