Digital Innovation & transformation


Cloud with an edge takes IoT to new heights

Digital Innovation & transformation

Some enterprises are adding edge computing to their cloud-based internet of things solutions, paving the way for accelerated data analysis and improved decision-making.

A blog post by Ken Carroll and Mahesh Chandramouli, senior managers, Deloitte Consulting LLP

Just a few years ago, many people expected the internet of things (IoT) network of interconnected machines, sensors, and other devices to send all its data to the cloud for storage and processing. Today, however, edge computing architecture can place processing and storage closer to the physical sources of data generation. A growing number of IoT solutions now benefit from a combination of edge and cloud computing, which can help to alleviate latency, increase scalability, and enhance access to information to enable better, faster decision-making, among other advantages.

Cloud Migration & operation

As the amount of data generated by sensors grows tremendously, enterprises are increasingly focused on the amount of time it takes data to move from a connected device to the cloud and then back to the device. In a cloud-only IoT architecture, information typically travels hundreds or even thousands of miles, so if quick, data-based decision-making is vital to an IoT solution’s efficacy, that information can lose value in milliseconds. In such cases, edge computing can dramatically decrease latency and improve response time. According to one estimate, as much as 55 percent of IoT data could soon be processed at or near the source.

Reducing latency is just one considerable benefit of adding edge capabilities to IoT architecture. Others can include more effective bandwidth use resulting from localized data processing; improved network connectivity and security; increased autonomous data processing and storage on everything from vehicles to medical devices; and enhanced data privacy, normalization, and filtering capabilities.

Cloud and edge in action

This balance between cloud and edge architecture can dramatically improve the aggregation and transmission of data across a wide range of operations relying on IoT solutions.

Smart factories. Many manufacturers have multiple plants in different locations, each typically with unique characteristics and functional requirements. The more spread out an operation, the more difficult it may be to maintain centralized data analysis capabilities in the cloud or at a corporate data center. While the cloud will continue to play an important role in smart manufacturing—monitoring systems and processes across large or even global portfolios, for example—an integrated edge-cloud architecture can provide the kind of speedy and nearly unimpeded connectivity necessary to support smarter operations on the factory floor.

Smart buildings. IoT-connected devices are transforming some offices, retail stores, hospitals, and other buildings into cost-efficient, responsive environments that can deliver better experiences to their occupants, support digital collaboration, and enable owners to conserve space, energy, water, and other resources. For example, edge computing can transmit occupancy data from strategically placed sensors to a cloud-hosted service that performs specialized analytics. The results can be sent back via the gateway or edge server to alter the schedules of a building’s lighting, ventilation systems, and other connected equipment to improve energy efficiency and lower costs.

Scaling IoT: Complexities and challenges

Despite the many benefits, adding edge computing in a cloud-based IoT environment can also pose operational and systems design complexities. Some widely distributed sensors or gateways may be scattered and difficult to physically reach or both when placed in offices, plants, and campuses; on pipelines; and in remote field sites, among other locales. An organization may have thousands of devices and hundreds of associated gateways and edge nodes with firmware and operating systems requiring backups, software patches, and other updates. Monitoring these disparate devices and addressing potential problems can require an enormous amount of automation and field service.

In addition, while the cloud offers on-demand scalability and can be readily configurable, automated, and resilient, providing these capabilities at the edge may be costly, requiring significant investment in additional hardware and software and much complex work to enable an increased number of devices and edge nodes.

Extending the cloud and the data center to the edge with multiple endpoints can also increase the surface area for cyberattacks. Insecure nodes and devices can be weak links that leave the entire network vulnerable, so maintaining the physical and cybersecurity position of all edge computing assets is critical.

IoT devices and the data they can provide are changing how enterprises interact with the world as well as how they gather and process massive quantities of business-critical information. While no single solution will suit every organization, a balanced approach to cloud and edge computing will likely play an increasingly prominent role in IoT architecture in the years ahead.

This article first appeared on the WSJ

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