Optimised Distributed Edge

  • Edge Computing

  • IoT

An optimised mesh ensures that your organisation's IoT and edges are communicating efficiently. An optimised mesh is capable of collecting rich, accurate data and providing value at every edge of your organisation.

Data is the lifeblood of modern business, providing valuable business insight and supporting real-time control over critical business processes and operations. Today's businesses are awash in an ocean of data, and huge amounts of data can be routinely collected from sensors and IoT devices operating in real time from remote locations and inhospitable operating environments almost anywhere in the world.

But this virtual flood of data is also changing the way businesses handle computing. The traditional computing paradigm built on a centralized data center and everyday internet isn't well suited to moving endlessly growing rivers of real-world data. Bandwidth limitations, latency issues and unpredictable network disruptions can all conspire to impair such efforts. Businesses are responding to these data challenges through the use of edge computing architecture.

Edge computing moves some portion of storage and compute resources out of the central data center and closer to the source of the data itself. Rather than transmitting raw data to a central data center for processing and analysis, that work is instead performed where the data is actually generated -- whether that's a retail store, a factory floor, a sprawling utility or across a smart city.

Our distributed edge optimisation solutions ensure that the data you collect and the services you build at the edge are effective & performant.

Priorities while optimising your distributed edge

  • Improving performance & autonomy of edge devices
  • Hardening security of edge devices to prevent unwanted access
  • Increasing effective throughput of devices to generate rich data
  • Optimising value of edge consumers by providing near-complete experiences

Principles of our distributed edge optimisation

We strive to convert your IoT into an intelligent edge. The 6 foundational principles that we follow are,

  • Shifting Computing Workloads to the Data Source. The intelligent edge requires the proliferation of smaller, edge-based cloudlets and devices which can handle large computing workloads on their own. They do not need to send all data back to a centralized data center for processing. This idea is at the heart of all edge computing. It is enabled by the ever-increasing processing capabilities and flexibility of smaller devices or appliances, and the overall sinking cost of computing.
  • Geographic “Nearness” to the Data Source. Everything happening “at the edge”, the cloudlets and devices need to be as close as possible to the data source, a hop away from the connected sensors. Coupled with higher network speeds that can deliver Gbps-range rates, this “nearness” is a guarantee for low latency. We have recently spoken of content delivery networks that support this concept.
  • Real-time Data Collection, Analysis and Storage. Data must not just be collected and sent to a large data center for processing. The analysis and sorting of data is done close to the data source in real-time, to enable a more rapid turnaround time and lower latency. Read our article on IoT-powered transformation to get a clearer idea of this.
  • Filtering Critical and Non-critical Data. As it demands immediate attention, critical data will be processed locally and stored immediately for re-use. Non-critical data may be simply be discarded or, if relevant, sent to a far-away data center for archiving.
  • Horizontal Scalability. It must be possible to expand the power of an edge cloudlets by adding more resources and connect them together to work as a single, efficient logical unit. Take a look at our article for more details on what is a scalable solution.
  • Ability to Function with Sporadic Connectivity. The systems must continue to collect and store data when connectivity to the data network is down. Cloudlets and devices must be autonomous for their power supply. Moreover, when connectivity or power is back, all must prioritize data to send the most critical information first and continue the processes where they halted.

If you can't get the data closer to the data center, get the data center closer to the data.

Get in touch with us for an initial consult and know how we can help your organisation optimise its distributed edge.

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Environment, Carbon Neutral

Data Architecture

Big Data, Machine Learning