The article explains cloud computing fundamentals, highlights its limitations, introduces edge and mobile edge computing (MEC) as complementary solutions, and details how MEC reduces latency and bandwidth usage to enable advanced use cases such as autonomous driving in the 5G era.
The article analyzes the rapid rise of industrial IoT, outlines four key obstacles—high investment cycles, fragmented connectivity, security risks, and immature standards—and explains how Tencent Cloud’s full‑stack IoT portfolio, including TencentOS tiny, IoT Explorer, Trust ID, and the IoT Marketplace, addresses these issues with real‑world smart‑manufacturing case studies.
Edge computing is emerging as a crucial IoT trend because it reduces data transmission and storage costs, enables sub‑second response times for safety‑critical operations, enhances security and privacy, and is supported by a growing ecosystem of cloud providers, vendors, and open‑source projects.
Looking ahead to 2019, the article forecasts that Kubernetes will mature and accelerate adoption, service meshes like Istio and Envoy will dominate multicloud networking, containerized micro‑service marketplaces will expand, SaaS providers will deepen enterprise app portfolios, and hybrid‑cloud and edge computing will grow, driven by cloud‑native architectures.
The article details JD's borderless retail concept by presenting the experience architecture, AI‑driven interaction, edge‑perception layers, technical stack, and data‑driven metrics that together enable a low‑cost, scalable digital transformation of fashion brick‑and‑mortar stores.
ARM has introduced the Neoverse N1 and E1 platforms, built on a 7nm process to deliver high scalability, performance and power efficiency for 5G, IoT and next‑generation cloud‑to‑edge infrastructure, while sparking debate among industry leaders about the future of server architectures.
The article outlines eight emerging technology trends for 2019—including autonomous objects, augmented analytics, AI‑driven development, digital twins, autonomous edge computing, immersive AR/VR experiences, blockchain, and smart spaces—explaining their current state, future potential, and impact on work and daily life.
An in‑depth analysis of China's IDC market predicts continued growth beyond 200 billion yuan by 2020, outlines evolving development models that combine large‑scale, energy‑efficient facilities with micro‑IDC edge deployments, and examines technological trends such as cloudification, modular data centers, high‑density, green, and customized solutions.
This article details Alibaba's end‑to‑end solution for digitizing offline retail foot traffic, combining existing surveillance cameras, RFID tags, and advanced AI techniques such as lightweight YOLO detection, knowledge distillation, and multi‑level pedestrian re‑identification to capture, analyze, and act on shopper behavior for both business operations and personalized in‑store experiences.
This article explains why video streams can still lag on high‑speed mobile networks, introduces the origin and principles of Content Delivery Networks (CDNs), and shows how CDNs reduce latency, improve user experience, and benefit both internet and telecom operators.
The article reviews the latest IoT and edge‑computing trends, outlines Tencent’s multi‑layer IoT platform, edge solutions, LoRa network deployment, and how AI‑driven data analysis will transform the fragmented IoT market into a smarter, more integrated ecosystem.
Alibaba’s latest AI breakthroughs—including a voice assistant that understands hidden user intent, a new edge‑cloud computing whitepaper, record R&D spending, and a medical AI project for flu prediction—showcase the company’s rapid advances across artificial intelligence and cloud technologies.
This article traces OpenStack’s rise, decline, and recent resurgence, describing how the foundation refocused on core services, launched pilot projects in CI/CD, containers, edge computing, and AI, and positioned the platform as a mature, widely‑adopted private‑cloud solution.
Alibaba’s senior tech expert explains the concept, architecture, core AI capabilities, real‑world case studies, and future roadmap of the Tmall “Future Store”, a vision‑driven, sensor‑rich unmanned retail experience that merges computer‑vision, edge computing, and data‑driven operations.
Alibaba’s senior IoT expert outlines how the company’s IoT platform enables device connectivity, edge computing, massive data processing, predictive maintenance, and application hosting, while addressing challenges of device integration, network stability, and scalability, ultimately fostering a collaborative ecosystem for diverse industry solutions.
At SIGCOMM 2018 in Hungary, Alibaba showcased its pioneering network research, sharing visions on programmable hardware, integrated software‑hardware design, intelligent operations, the Hyper‑scale Edge Network, RDMA deployment, and network visualization, while presenting several influential papers and collaborating with leading academia.
Gartner’s 2018 strategic tech trends revolve around the Intelligent Digital Mesh, a framework that combines AI‑driven intelligence, immersive digital experiences, and mesh‑based connectivity to shape the future of enterprise IT, with ten detailed sub‑trends ranging from AI foundations to blockchain and adaptive risk management.
This article examines the five critical demands—latency/determinism, local interactivity, data/bandwidth, privacy/security, and limited autonomy—that will dictate the evolution of edge computing, offering strategic recommendations for I&O leaders and outlining how these forces will shape future edge solutions.
The article details Cainiao Network's 2018 Global Smart Logistics Summit, where AI‑driven flexible automation technologies—including modular robotics, IoT, edge computing, and large‑scale multi‑agent planning—were presented as a transformative solution for scalable, efficient warehouse operations.
The Think in Cloud 2018 conference in Beijing showcased how cloud platforms enable rapid AI deployment across sectors such as autonomous driving, intelligent customer service, and education, highlighting challenges, platform‑centric solutions, and real‑world case studies that illustrate the growing synergy between cloud computing and artificial intelligence.
The article examines how the rapid growth of IoT devices in 2018 raises significant security concerns, predicts large‑scale attacks and data challenges, and highlights a shift toward edge computing and tighter IT‑OT collaboration to manage the expanding data and protect networks.
The article explains how serverless computing, emerging since 2017, is being integrated with edge computing and Tencent Cloud services—covering its benefits for rapid, elastic application development, current IoT productization efforts, cloud-function use cases, and upcoming VPC connectivity to enable seamless access to backend resources.
This article explains how Serverless and cloud functions enable edge computing and AI by moving compute close to data, covering Backend‑as‑a‑Service, Function‑as‑a‑Service, IoT device deployment, edge AI scenarios, and future integration with CDN and VPC.
The article explains that traditional CDNs deliver limited performance gains for mobile users because the dominant last‑mile latency of wireless networks overshadows CDN benefits, and it explores data, misconceptions, cost considerations, and possible strategies for improving mobile content delivery.
The article chronicles UPYUN's cloud CDN development from its modest 30‑40 node deployment in 2010, through multiple architectural revisions, scaling to over 130 edge nodes by 2014, and outlines future plans for DNS‑based load balancing, international backbone expansion, and video/live‑stream acceleration up to 2016.
This article explains what a Content Delivery Network (CDN) is, why it improves website response times, outlines its basic acceleration strategy, describes its core components such as origin servers, edge caches and smart DNS, and walks through the typical CDN operation flow.
The article analyzes Ilya Grigorik's findings that traditional CDNs deliver minimal performance gains for mobile users due to high last‑mile latency, outlines latency components, presents comparative data, and discusses the operational challenges of deploying mobile‑optimized edge caching.
