Fog Computing
As IoT (Internet of Things) is deployed in almost every field, limitations are encountered due to the excessive amount of data generated. It has become inevitable that the centralized cloud computing architecture is faced with limitations in bandwidth, data process, storage, latency, and analytics. To bridge the cloud and edge, the distributed approach called “fog computing” is introduced between the cloud and where the data is generated.
Source: Intel Corporation
Fog computing architecture adopts multiple mobile edge computing platforms to handle data originated from the edges. The data will be stored, routed, analyzed, and managed by these fog devices rather than the cloud, so that the latency that used to travel from the edges to the cloud can be minimized since the fog will be the primary network control.
With the interest of fog computing developments, Cisco, ARM, Dell, Intel, Microsoft and Princeton University established OpenFog Consortium on November, 2015, to define the interoperability of fog architecture.
x86-based Gateways as Fog Computing Elements
The most critical element of fog analytics is the adoption of x86-based computing platforms based on high-performance Intel processors and the ability to get all the edges connected and analytics enabled under an interoperable infrastructure. For deployment ease, the x86 gateways empowered by Intel platforms have the advantages in scalability, interoperability and wide OS compatibility. Furthermore, the x86 gateways provide end-to-end reference architecture, Intel product families, and its ecosystems to work with third party solutions as the foundation for seamless communication, localized analytics and interconnections of the edges. Thus, the unconnected will become connected to form the fog architecture.
Another deployment advantage with x86-based gateways is the Intel IoT Gateway Technology, consisting of scalable processor performance and multiple OS supports. This is an out-of-the-box offering with pre-integrated manageability, security and enhanced real-time analytics to provide developers the cost-effective and customizable solutions in virtually every domain.
Overall Benefits
Since cloud computing is not perfectly suited for real time analytics, there is a need for fog computing which enables proximity to the edges and localizes data analytics. This distributed approach minimizes latencies between edge and cloud and at the same time, offloads the bandwidth and saves power consumption as well.
See our comprehensive solutions on x86-based fog computing gateways