The Cloud can present limitations in real-time transactions, time-critical tasks, and analytics when it comes to achieving responsive, real-time IoT. For years, administrators have been concerned that too much bandwidth is required to transmit two-way communication and data generated by sensors along a network in IoT implementations. Latency, security, and privacy within a network infrastructure can be problematic if applications rely completely on the Cloud. This is where Fog Computing comes in. It brings autonomy to the forefront with real-time analytics and performance available directly to an end-point and smart device.
Also known as fog networking or fogging, this architecture distributes computing resources and applications straight from the data source to the cloud. It removes the unreliability of cloud computing by reducing the amount of data transmitted for processing, storage, and analytics. It operates in real-time and is great for applications like smart cars, parking management, smart lighting, real-time security surveillance, real-time energy optimization, patient monitoring, water quality monitoring, and fleet management.
The Fog takes cloud analytics directly to the edge of network devices without latency or bandwidth constraints. This is because data is processed directly on a data hub on a smart device, smart router, or gateway device. There is no need for massive computation, storage, and communications distributed locally or routed over the Internet.
Fog Computing Benefits
A Fog computing architecture includes computing gateways which accept data from IoT device collection. It offers a wide degree of functionality that can include wireless or wired granular collection endpoints such as ruggedized routers or switching equipment. On-premise equipment and gateways can also access edge nodes. Higher end communication capabilities intelligently integrate core networks and routers, along with global cloud services and servers. Fog computing frameworks simply give organizations more choices for processing data whenever and wherever it is most appropriate, according to Tom Cornwell, Principal Consultant in Business Consulting for NWN.
“For some applications, data may need to be processed as quickly as possible,” says Cornwell. “For example – in a manufacturing use case where connected machines need to be able to respond to an incident as soon as possible – fog computing creates low-latency network connections between devices and analytics endpoints. The architecture in turn reduces the amount of bandwidth needed because data no longer has to be sent all the way back to a data center or cloud for processing.”
Fog offers smart devices an unparalleled level of real-time autonomy that empowers IoT applications.
- Fog can be used in situations where bandwidth availability is inconsistent to send data.
- Fog can be processed close to where it is created.
- Fog is more secure because users can place security features in a fog network from segmented network traffic to virtual firewalls to protect it.
Why Fog Networking Matters
Fog architectures can respond independently because they are decentralized. A user can position a compute closer to the resources that need compute power in order to respond quickly while the actual processing and decisions are controlled elsewhere.
- Fog is real-time compute on the edge. It is closer to the devices that are scattered around a network infrastructure.
- It allows for low-latency network connections that connect devices and endpoint analytics. That’s why it is perfect for self-driving cars. The fog allows onboard processors to make decisions independent of the data center when real-time decisions are necessary.
- There is plenty of compute power in the cloud to determine algorithms. The Fog retrieves data from the cloud and makes decisions autonomously. It goes back and forth symbiotically.
- A combination of Fog and Cloud allows users to access the very large amount of horsepower necessary to run analytics in the Cloud while running autonomous compute devices. This turbo-charges a network for seamless operation.
- Peripheral benefits – Most data from IoT centers require very small bits of metadata. That means large amounts of data don’t need to be moved from place to place. Lower transmission media can be run on a LoRaWAN network which doesn’t require extensive power or cabling to smart devices. This results in a significant cost and energy savings. That makes it a greener technology.
NWN Brings Fog Computing into Focus
NWN and our strategic partners help implement intuitive IoT strategies for manufacturing, medical facilities, municipalities, and other organizations. We have been on the ground floor for several fog rollouts and smart city implementations. We are currently assisting one major city in traffic management by updating their IT infrastructure and installing Fog for intersection loops where sensors must respond independently in real-time to unplanned events such as emergency vehicles that need the right-of-way.
To avoid traffic mishaps, a sudden emergency interruption requires zero lag time and autonomous devices that can respond independently of the data center through a preset algorithm. Fog computing also prevents traffic gridlock if the intersection devices are cut off from the data center. Peripheral devices can respond without needing the data center to aggregate information and make decisions.
IoT rollouts are on the rise and Fog is the wave of the future. These implementations are poised to eclipse $772 billion this year alone. Cities such as Boston, Las Vegas, and San Francisco have begun deployments. Manufacturing, transportation, utilities, and municipalities are all getting on board with smart technology. It all makes sense since installation and deployment of IoT technologies have a rapid payback with quick cost recovery. Get an NWN cloud assessment and find out how this technology can benefit you.