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Edge Computing Orchestration in IoT: Coordinating Distributed Workloads

DZone

In the rapidly evolving landscape of the Internet of Things (IoT), edge computing has emerged as a critical paradigm to process data closer to the source—IoT devices. This proximity to data generation reduces latency, conserves bandwidth and enables real-time decision-making.

IoT 195
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Act locally, connect globally with IoT and edge computing

All Things Distributed

The answer to this question is actually on your phone, your smartwatch, and billions of other places on earth—it's the Internet of Things (IoT). This is the exciting future for IoT, and it's closer than you think. Already, IoT is delivering deep and precise insights to improve virtually every aspect of our lives.

IoT 126
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Adding New Capabilities for Real-Time Analytics to Azure IoT

ScaleOut Software

The population of intelligent IoT devices is exploding, and they are generating more telemetry than ever. The Microsoft Azure IoT ecosystem offers a rich set of capabilities for processing IoT telemetry, from its arrival in the cloud through its storage in databases and data lakes.

IoT 52
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Edge Data Platforms, Real-Time Services, and Modern Data Trends

DZone

By processing data at the edge of the network, latency can be minimized, which means that data can be processed and analyzed faster. This is especially important for applications that require real-time responses, such as autonomous vehicles, industrial IoT applications, or streaming media.

IoT 130
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What is serverless computing? Driving efficiency without sacrificing observability

Dynatrace

When an application is triggered, it can cause latency as the application starts. Connecting IoT devices (for example, AWS IoT Device Management ). This creates latency when they need to restart. The platform builds the trigger to initiate the app. How does serverless computing tackle inefficiencies?

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Digital Twins Enable Seamless Use of Edge Computing in IoT

ScaleOut Software

Digital twins are software abstractions that track the behavior of individual devices in IoT applications. Because real-world IoT applications can track thousands of devices or other entities (e.g., The digital twin model is worth a close look when designing the next generation of IoT applications.

IoT 45
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Digital Twins Enable Seamless Use of Edge Computing in IoT

ScaleOut Software

Digital twins are software abstractions that track the behavior of individual devices in IoT applications. Because real-world IoT applications can track thousands of devices or other entities (e.g., The digital twin model is worth a close look when designing the next generation of IoT applications.

IoT 40