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Edge Computing Middleware: How It Can Tame IoT Complexity

Nastel Technologies®
June 26, 2019

The benefits of using edge computing middleware and tips for selecting the best approach for taming IoT complexity.

Edge computing middleware in an industrial or enterprise software architecture is akin to plumbing on steroids. This software layer must efficiently connect different applications, data sources, devices (such as sensors and endpoints), services and business entities.

Today, IoT and industrial IoT within an organization can pose enormous complexity because of the sheer scale of edge projects. The ability to run cloud and AI applications at the network edge only increases the level of intricacy.

Infrastructure management alone “can quickly become a problem of nightmarish proportions at the edge,” said IDC Analyst Ashish Nadkami.

The advent of cloud computing helped IoT explode. As a result, edge computing can reduce the cost of cloud performance by putting compute power close to the network edge and devices, said Keith Steele, chairman of the EdgeX Foundry technical steering committee.

“There are many problems associated with edge with lots of software and massive numbers of protocols around this,” Steele added. “Sometimes there is hardware fragmentation and silicon fragmentation. What we have at the edge is a real problem because it’s very heterogeneous, with many components, operating systems and silicon. Edge middleware is how we bring it together.”

Open or Proprietary Software

Edge middleware products can be divided into open platforms and proprietary platforms. For example, EdgeX Foundry is an open source, vendor-neutral software framework for IoT edge computing. There are many other open approaches, including FogLAMP, Kura, OpenHAB, Thingsboard.io, OpenEdge, SiteWhere and Kaa — the latter two offering enterprise editions. For the most part, open source approaches work by offering IT shops common building blocks and APIs (Application Programming Interfaces). They are often hardware and OS agnostic.

By comparison, proprietary approaches often come from large, well-known vendors such as Microsoft and AWS. Lesser-known vendors that often include open source software in their products include Zededa, Foghorn and Niolabs. Analysts are working to develop ways to rate vendors but there aren’t any clear leaders as yet.

This article originally appeared on iotworldtoday.com To read the full article, click here.

Nastel Technologies uses machine learning to detect anomalies, behavior and sentiment, accelerate decisions, satisfy customers, innovate continuously.  To answer business-centric questions and provide actionable guidance for decision-makers, Nastel’s AutoPilot® for Analytics fuses:

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Nastel Technologies is the global leader in Integration Infrastructure Management (i2M). It helps companies achieve flawless delivery of digital services powered by integration infrastructure by delivering tools for Middleware Management, Monitoring, Tracking, and Analytics to detect anomalies, accelerate decisions, and enable customers to constantly innovate, to answer business-centric questions, and provide actionable guidance for decision-makers. It is particularly focused on IBM MQ, Apache Kafka, Solace, TIBCO EMS, ACE/IIB and also supports RabbitMQ, ActiveMQ, Blockchain, IOT, DataPower, MFT, IBM Cloud Pak for Integration and many more.

 

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