The Internet of Things is connecting billions of “things” to the Internet, each “thing” collects data and all that data needs to be processed before it can be turned into intelligence or an automated action.
This massive increase of data transfer, storage and processing poses a computing question; should data processing happen at the “thing” (edge), in a central server (cloud), or something in between (fog)?
With approximately one third of all connected devices, smart buildings are at the forefront of answering this question and setting a path for the future of the IoT. Each device and function within a smart building has different needs, and each need may be best served by a different form of computing, but is it practical to develop infrastructure for cloud, fog and edge computing or can one form dominate the sector?
Cloud computing, or simply “the cloud”, has become somewhat of a household term in recent years with consumer facing applications as well as background functions for buildings and industry. It refers to the delivery of on-demand computing resources, including everything from applications to data centers, over the Internet on a pay-for-use basis.
“In order to effectively process real time big data streams, organizations are increasingly turning to the cloud to access both the required processing capacity and data storage facilities to handle their data streams. Cloud computing can offer flexible, adaptable and scalable processing resources to the analysis of data, which in turn can provide dramatic improvements in real time problem solving and cost avoidance,” explains our new report The Internet of Things in Smart Commercial Buildings.
Fast access public cloud computing services are offered by dedicated firms, giving their clients access to significant computing power without the need to purchase hardware, software or supporting infrastructure. This is particularly beneficial for start-up companies who require strong data processing power but may not have the resources to setup their own servers and processing facilities.
“The combination of ease of use, and low capital investment requirements has prompted a boom in the number of software as a service (SaaS) providers. The SaaS market set for strong growth to 2020, with a projected CAGR of 11%,” the report predicts.
Clouds can also be private, reducing the users reliance on external providers for their computing needs. Such private clouds are particularly appealing for larger companies wishing to benefit from the cost and flexibility of a cloud based approach. Establishing a private cloud can also help minimize threats related to security and privacy.
Recently the emergence of the IoT has introduced a new paradigm for smart buildings that supports a decentralized architecture where a great deal of analytics processing can be done at the edge (the sensor unit) instead of the cloud or a central server. This computing approach, often called “edge computing” or “fog computing,” provides real-time intelligence and greater control agility while at the same time off-loading the heavy communications traffic.
With new developments in computing technology we now have access to cheap and energy-efficient embedded processors that are well suited for such data processing. This affords the newfound ability to process the sensor analytics inside the sensor unit itself. Using this approach, the data that is sent over the network can be merely the final summary of the analysis, which is thinner in volume, and allows shorter response time. This capability has been setting the foundation for the next generation of rich data-driven smart sensors.
“This ‘Edge’ or ‘fog’ computing provides real-time intelligence and simultaneously reducing the communications traffic load. As technology evolves, we expect the gateways near to the edge of the network to form an increasingly important bridge between edge devices and higher level networks, making behavioral decisions, ensuring network security and helping to streamline data flows,” our research forecasts.
We might not quite be at that stage yet, however, as many IoT enabled smart devices are limited in their capabilities. Factors such as size, cost, and the power requirements, directly impact computational power meaning cloud capacity may still be required. In addition, maintaining some level of cloud-based capability helps improve scalability and elasticity of organizations because storage is available as required, and scaled back when not required.
In Memoori’s view, both cloud and edge approaches will continue to play a critical role in enabling organizations to extract the maximum value from data.
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