One of the reasons why IoT has gained momentum in the recent past is the rise of cloud services. Though the concept of M2M existed for over a decade, organizations never tapped into the rich insights derived from the datasets generated by sensors and devices. Existing infrastructure was just not ready to deal with the massive scale demanded by the connected devices architecture. That’s where cloud becomes an invaluable resource for enterprises.
With abundant storage and ample computing power, cloud became an affordable extension to the enterprise data center. The adoption of cloud resulted in increased usage of Big Data platforms and analytics. Organizations are channelizing every bit of data generated from a variety of sources and devices to the cloud where it is stored, processed, and analyzed for deriving valuable insights. The combination of cloud and Big Data is the key enabler of Internet of Things. IoT is all set to become the killer use case for distributed computing and analytics.
Cloud service providers such as Amazon, Google, IBM , Microsoft, Salesforce, and Oracle are offering managed IoT platforms that deliver the entire IoT stack as a service. Customers can on-board devices, ingest data, define data processing pipelines that analyze streams in real-time, and derive insights from the sensor data. Cloud-based IoT platforms are examples of verticalized PaaS offerings, which are designed for a specific use case.
While cloud is a perfect match for the Internet of Things, not every IoT scenario can take advantage of it. Industrial IoT solutions demand low-latency ingestion and immediate processing of data. Organizations cannot afford the delay caused by the roundtrip between the devices layer and cloud-based IoT platforms. The solution demands instant processing of data streams with quick turnaround. For example, it may be too late before the IoT cloud shuts down an LPG refilling machine after detecting an unusual combination of pressure and temperature thresholds. Instead, the anomaly should be detected locally within milliseconds followed by an immediate action trigged by a rule. The other scenario that demands local processing is healthcare. Given the sensitivity of data, healthcare companies don’t want to stream critical data points generated by life-saving systems. That data needs to be processed locally not only for faster turnaround but also for anonymizing personally identifiable patient data.
The demand for distributing the IoT workloads between the local data center and cloud has resulted in an architectural pattern called Fog computing. Large enterprises dealing with industrial automation will have to deploy infrastructure within the data center that’s specifically designed for IoT. This infrastructure is a cluster of compute, storage, and networking resources delivering sufficient horsepower to deal with the IoT data locally. The cluster that lives on the edge is called the Fog layer. Fog computing mimics cloud capabilities within the edge location, while still taking advantage of the cloud for heavy lifting. Fog computing is to IoT what hybrid cloud is to enterprise IT. Both the architectures deliver best of both worlds.
Cisco is one of the early movers in the Fog computing market. The company is credited with coining the term even before IoT became a buzzword. Cisco positioned Fog as the layer to reduce the latency in hybrid cloud scenarios. With enterprises embracing converged infrastructure in data centers and cloud for distributed computing, Cisco had vested interest in pushing Fog to stay relevant in the data center. Almost after five years of evangelizing Fog computing with little success, Cisco finally found a legitimate use case in the form of IoT.
In November 2015, leading vendors in the space of infrastructure and cloud formed an industry body called the OpenFog Consortium. According to the official website, the mission of the consortium is to drive industry and academic leadership in fog computing architecture, testbed development, and a variety of interoperability and composability deliverables that seamlessly leverage cloud and edge architectures to enable end-to-end IoT scenarios.
ARM, Cisco, Dell , Intel, Microsoft, and Princeton University are the founding members of the OpenFog Consortium. Except Princeton University, which is chartered with the academic outreach, all other members of the consortium have a solid business interest in making Fog computing mainstream. ARM is making inroads into the data center and edge computing by offering affordable processing power. It is aiming to power IoT Gateways that are designed to manage local sensor networks. After acquiring WindRiver and McAfee, Intel has become a key contender in the IoT Gateway market. Dell is building purpose-built IoT Gateways powered by Intel processors. Of course, Cisco is trying to be in the forefront of the new paradigm. With the recent acquisition of Jasper, the company is hoping to capture significant market share.
Microsoft has more than one reason to be a part of the OpenFog Consortium. Windows 10 IoT Core is evolving fast to become the choice of embedded OS for IoT Gateways and high-end devices. With its support for ARM and Intel, Microsoft is aggressively pushing Windows 10 as the OS of IoT. Azure IoT is one of the leading enterprise IoT cloud platforms, which has all the essential building blocks for delivering a robust solution. With Windows 10 IoT Core in the Fog layer and Azure IoT in the cloud, Microsoft is hoping to dominate the market.
OpenFog Consortium has pledged to work with existing industry bodies such as IIC, OCF, OpenFV, and MEC. On April 12, 2016, GE Digital, Schneider Electric, and IEEE joined the consortium’s board of directors. OpenFog also found its first member in Asia, SAKURA Internet, which is chartered to drive the momentum in Asia Pacific as Japan.
To meet its goal, the OpenFog Consortium has to invest in reference architectures, developer guides, samples, and SDKs to articulate the value of Fog computing to developers and IT teams. They are critical for the success of this new initiative. Fog computing, along with the cloud, will accelerate the adoption of IoT in the enterprise.