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Understanding operational 5G: a first measurement study on its coverage, performance and energy consumption

The Morning Paper

Understanding operational 5G: a first measurement study on its coverage, performance and energy consumption , Xu et al., There are high hopes for 5G , for example unlocking new applications in UHD streaming and VR, and machine-to-machine communication in IoT. energy consumption). Energy Consumption. SIGCOMM’20.

Energy 130
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What is Greenplum Database? Intro to the Big Data Database

Scalegrid

In this blog post, we explain what Greenplum is, and break down the Greenplum architecture, advantages, major use cases, and how to get started. Greenplum Database is an open-source , hardware-agnostic MPP database for analytics, based on PostgreSQL and developed by Pivotal who was later acquired by VMware. The Greenplum Architecture.

Big Data 321
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Noon Lights — an IoT Review

Adrian Cockcroft

I’ve been gradually installing some IoT automation at home over the last few months, and was looking for a lighting solution to fit a fairly complex situation. noonhome.com Their over-all architecture is to manage one room at a time, using one special switch as a Noon Director and up to ten Noon Extension switches.

IoT 40
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5 signs you need to implement test automation

Testsigma

Just a manual testing approach would not suffice for today’s wired devices and dynamic architectural applications of Industry 4.0. We have software that communicates with different components, such as APIs, databases, and hardware, and data flows in real-time across many connected devices in the IoT environment (internet of things).

Testing 54
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Use Parallel Analysis – Not Parallel Query – for Fast Data Access and Scalable Computing Power

ScaleOut Software

Whether it’s ecommerce shopping carts, financial trading data, IoT telemetry, or airline reservations, these data sets need fast, reliable access for large, mission-critical workloads. For more than a decade, in-memory data grids (IMDGs) have proven their usefulness for storing fast-changing data in enterprise applications.

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Use Parallel Analysis – Not Parallel Query – for Fast Data Access and Scalable Computing Power

ScaleOut Software

Whether it’s ecommerce shopping carts, financial trading data, IoT telemetry, or airline reservations, these data sets need fast, reliable access for large, mission-critical workloads. For more than a decade, in-memory data grids (IMDGs) have proven their usefulness for storing fast-changing data in enterprise applications.