Embedded Appliances for Intelligent Edge Computing
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16 July 2018

The Internet of Things (IoT) is an undeniable and unstoppable revolution. Immense numbers of intelligent sensors and devices are generating huge amounts of data that contain possibly game-changing information. It is a formidable challenge for IT leaders to collect insights from that data rapidly, cost-effectively, without opening up security vulnerabilities, or in violation of compliance directives.

With earlier data business intelligence projects, organizations transferred data to a central data repository for processing in order to garner strategic insights. Big data projects were similar, blending large amounts of data of varying types into a “data lake” for subsequent analysis.

But now, with IoT data being churned out in bulk by sensors in factories, warehouses, and other facilities, many organizations are finding it makes much more sense to analyze that data close to where it is generated: at the edge of the corporate, industrial and government networks. Benefits include faster insights and data that are secure and compliant. Best of all, data analysis at the edge avoids the high costs of sending huge volumes of data across long distances.  

The Value of the Intelligent Edge

The term "Intelligent Edge" is used in many ways, but perhaps the best way to think of it is as where the action is. It's a manufacturing floor, a building, a campus, a city, your house, a crop field, a wind farm, a power plant, an oil rig, a telecommunications outpost, a sports arena, a battlefield, in your car, in the sky, or under the sea. It's everywhere everything is, and it's where the "things" are in the Internet of Things (IoT).

The edge is "intelligent" because there's technology in these places that is connected, computational, and controlling. Critically, the Intelligent Edge provides analytics capabilities that were formerly limited to on-premises or cloud data centers. 

By considering its three dimensions, we reveal the power of the Intelligent Edge:

•Connectivity: Network or directly connect things and devices at the edge: people, appliances, gadgets, tools, robots, etc
•Computing: Analysis of data at the edge to reveal new scientific, engineering, or business insights
•Control: Configure, activate, or manage the things (intelligent devices) and equipment at the edge

Computing at the Intelligent Edge 

When discussing the Intelligent Edge, it's instructive to first understand the generalized four-stage IoT solutions architecture. "Things" are connected to sensors for data capture and actuators to control the things—either wired or wirelessly. These sensors and actuators connect to gateways, switches, and data acquisition systems in stage 2. Stage 3 is comprised of computing systems that are at the edge, and stage 4 is the remote data center or cloud. Not all IoT solutions include all four stages (e.g., some are sensor-to-cloud solutions), but a large portion of IoT solutions can be mapped into this architecture.

Although each of the connect, compute, and control of the Intelligent Edge contribute to edge intelligence, compute improvements are especially important because they can derive immediate insights from edge data at relatively low cost. Edge compute can be improved by shifting enterprise-class compute resources from the data center out to the edge which enables important benefits.

There are many mission-critical applications requiring immediate insight and control where compute must take place at the edge due security and latency requirements. Edge computing is also the simplest and lowest-cost solution for sending big data back and forth from things to the cloud data center. This process can consume massive bandwidth. Processing data at the edge also reduces security vulnerabilities as data is vulnerable to attacks and breaches when transferring to and storing in an offsite location.

Setting aside security vulnerabilities, data can be corrupted on its own. Retries, drops, and missed connections plague edge-to-data-center communications. Edge computing can also help in maintaining compliance as laws and corporate policies can govern the remote transfer of data. For example, certain countries forbid companies from moving their citizens’ personal data outside national borders. 

Interface Masters Technologies: Accelerating Success at the Intelligent Edge

Interface Masters Technologies is an innovator with an extensive portfolio of embedded appliances for intelligent edge computing deployments.  Interface Masters embedded networking appliance offerings can reduce power consumption, complexity and cost. These solutions enable edge compute to be architected with simple, low-cost, low-power configurations which provide a building block for supporting the broad range computing, storage and wireless/wired networking features. Interface Masters’ appliances provide the flexibility, power, efficiency, and cost savings that are essential for success in today’s challenging Intelligent Edge market, making them ideal for a range of edge computing applications.


Interface Masters Technologies has for over 20 years been providing off-the-shelf innovative network security solutions with customization services to OEMs, Fortune 100 and startup companies. Our headquarters are located in San Jose, California in the heart of Silicon Valley where we are proud to design and manufacture all of our products.  Based on MIPS, ARM, PowerPC and x86 processors, Interface Masters appliance models enable OEMs to significantly reduce time-to-market with reliable, pre-tested and pre-integrated networking solutions that can meet the most challenging security requirements. 

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