Cloud

How Fog Computing Can Optimize the Energy Sector

When serious computer power is needed at remote locations, the cloud could use a little help.

Doug Bonderud is an award-winning writer capable of bridging the gap between complex and conversational across technology, innovation and the human condition.

Delivering power on demand and discovering resources at scale require geographical reach. To meet increasing global need, energy and utility companies require diverse and often distant platforms — from floating oil rigs in the Gulf of Mexico to waterborne power plants off the coast of Alaska. Energy organizations are also under pressure to adopt the emerging expectations of Industry 4.0, which includes always-connected devices that are power-efficient and continuously monitored, and that consistently deliver streams of data to the cloud for analysis.

But the confluence of distance and data presents a challenge: latency. For every 60 miles of distance from a cloud server, latency increases by approximately one millisecond. With oil rigs and power plants sometimes thousands of miles from the nearest cloud hub, this delay makes generating real-time insight problematic. Companies could miss critical notifications about potential equipment failure or resource discovery, increasing risk and reducing ROI.

Fog computing offers a way to close the gap between cloud distance and compute demands. Here’s how this technology could help optimize the energy sector.

Fog Helps Make Remote Decisions Quickly

Cloud computing still generates confusion, with some workers certain this distributed resource resides in the sky. Despite its inaccuracy, the comparison is useful for energy sector modeling: The relative distance of large-scale cloud networks to offshore rigs or remote power plants puts them similarly out of reach.

For companies to capture and process data on demand, they need a way to keep compute tasks closer to home. One solution is edge computing, which effectively offloads small tasks onto Internet of Things devices, allowing them to selectively send or discard data points based on preprogrammed rules. Fog computing moves the focus outside devices but grounds it near IoT networks, providing a platform to aggregate data from multiple devices and then make intelligent decisions.

For example, if connected sensors report a consistent increase to power plant core temperature, fog networks can direct safety measures to engage and then send a report back to cloud servers to prompt further action. Without fog, decision time is slowed — and in the case of failing equipment or emergent environmental concerns, this could have disastrous effects.

Delivering Data in the Growing ‘Internet of Types’

The term “fog computing” was originally coined by Cisco. The company recognized that as growing numbers of IoT devices created “an unprecedented volume and variety of data,” the delay between acquisition and action meant “the opportunity to act on it might be gone.”

This becomes especially problematic as the number of connected devices skyrockets; already, these devices generate more than 2 exabytes of data per day. Add in the expanding range of device “types” — everything from connected cameras and wireless access points to machine controllers and temperature sensors — it becomes critical for energy companies to both aggregate and analyze disparate data at speed.

And despite its ability to handle large data volumes at scale, the cloud simply can’t keep up. Tackling the Internet of Things to deliver reliable, real-time information demands a middle ground.

The Cost Benefit of Fog

Along with the ability to analyze data onsite and increase decision-making speed, fog solutions also offer benefits in scale and scope.

Fog computing offers substantive cost benefits over typical clouds when it comes to data transmission, computing, data storage and power consumption at scale. And according to work from the Department of Information Engineering and Telecommunication at the Sapienza University of Rome, Big Data analytics “can be done faster and with better results” across geographically diverse networks by using fog computing. In addition, fog computing naturally supports heterogeneous devices, allowing companies to unify disparate sensor and monitoring data at speed.

Leveraging these advantages is critical to realizing the long-term benefits of fog computing: SCADA networks, mobile endpoints and storage resources, all connected to a middle-ground fog network capable of both taking action on demand and facilitating the downstream benefits of Industry 4.0 in the cloud for energy organizations.

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