Search results for: 'edge computing, data storage'

Traditional cloud computing models sends data from the device to the cloud for data analysis and the decision is sent back to the device for implementation. The agility of cloud computing is great but not enough to overcome certain challenges such as latency, bandwidth, processing the data for real-time decision making, costs associated with data t...

Frost & Sullivan expects SASE adoption to maintain strong growth momentum during the next 5 years, mainly because of factors including the shift to remote and hybrid work models, rapid adoption of cloud and cloud-delivered services, increasing requirements toward integrating disjointed networking and security solutions, and the rising need to suppo...

The global data centre industry is entering a new growth phase, driven by surging AI adoption, expanding cloud ecosystems, energy transition requirements, and the increasing digitisation of economies. The most significant growth opportunities are emerging at the intersection of computing capacity, energy infrastructure, cooling innovation, digital ...

Data center cooling systems are key components of data center architecture, which fulfill critical cooling requirements for electronic equipment. The global growth of the internet and mobile devices has created enormous volumes of data that require storage and processing. As a result, the construction of data centers of all sizes has reached a fren...

Data center capex growth has accelerated dramatically in the past 2 years, reaching US$500 billion in 2025. Strong growth is set to continue, with investment set to reach US$1.5 trillion. North America has historically dominated investment and will continue to be a key regional market, but there is also accelerating demand from China, India, and Ea...

This study examines the emerging landscape of neuromorphic computing and its role in enabling low-power, real-time, brain-inspired intelligence across edge and autonomous systems. It reviews advancements in spiking neural networks, memristor-based computing in memory, event-driven vision sensors, and hybrid neuromorphic and conventional architectur...

Edge computing refers to moving data processing and computing as close to the data source/ point of origination as feasible, enabling near-real-time decisions and insights to drive better outcomes. The goal is to reduce latency while still ensuring high efficiency of networks, operations, service delivery, and user experience. Edge computing all...

AI infrastructure is rapidly evolving from stand-alone compute environments to vertically integrated AI platforms that combine compute, networking, storage, cloud software, orchestration, security, and intelligent data management. Platform-centric architectures are becoming essential to support scalable AI training, inference, and agentic AI worklo...

The data center colocation industry has seen significant growth in recent years, driven by the increasing demand for data storage and processing requirements. Public cloud service providers, enterprises, and governments are increasingly reliant on best-in-class data centers and digital infrastructure. A growing trend among enterprises is to outsour...