In a hyperconnected world, data will continually increase in both amount and velocity. The possibilities are amazing for both personal and business applications in all industries. Businesses will be able to tap into information from various types of sources including equipment, people, assets and sensors.
The potential for connectivity will have viable business benefits but also comes with several factors that need to be addressed when it comes to infrastructure.
The massive amount of data created by the Internet of Things (IoT) will force the issue of creating more efficient ways to transmit and store it.
It all comes down to what to do with the data
In the rush of developing new hardware, software and connectivity solutions, it’s easy to get dazzled by the shiny new objects—IoT platforms, “smart” things, sensors, actuators, IoT gateways and IoT edge devices—but IT teams have to make decisions that are best for their own companies.
No matter what configurations they create, they all have one thing in common—IoT data won’t be slowing down. Smart companies will get ahead of the IoT flood by examining their current infrastructure and landscape of solutions and technologies for viability in support of storing and transitioning raw data into actionable intelligence to benefit the business. Add in things like artificial intelligence and big data analytics and it’s a data storm that has to be managed.
So, what will be necessary to process, analyze, store and leverage the amount of IoT data coming into most organizations?
Capitalize on existing infrastructure
When determining infrastructure needs for IoT data processing, it’s smart to develop a plan that incorporates any existing structures, fiber cables, network switches, etc. If building a new facility, have your contractor work with your IoT vendor to define what is needed to incorporate an IoT deployment. Many times, there are cost savings in working like this because of the mistaken thinking that there should be separate or double the equipment when all IT can run on the same components.
Utilize cloud and fog computing
With cloud computing, data is moved and stored in data centers to be accessed by designated users. The Internet of Things will connect tons of devices and the resulting data will have to go somewhere. The cloud is a logical destination because of its capacity, controlled accessibility and security.
Fog computing—also known as edge computing—is where data is stored in local devices instead of making the trip to the cloud. Connected devices like sensors will send data to the fog devices such as routers or switches that process and analyze the incoming data.
“Fog provides the missing link for what data needs to be pushed to the cloud, and what can be analyzed locally, at the edge,” explains Mung Chiang, dean of Purdue University’s College of Engineering and one of the nation’s top researchers on fog and edge computing.
Work smarter, not harder
With the growth of fog computing, has come the rise of smaller devices for IoT deployments. As the devices and IoT mature, more intelligence will be pushed down to these edge devices. Microservices are becoming available on platforms where IoT software runs across many types of infrastructures, creating an intelligent edge.
Ultimately, the IoT network will one day be intelligent enough so that it will be able to select the most logical site in the infrastructure—the local edge, an IoT device, nearby collocation data center, an edge computing cluster or the cloud—where different types of data should be processed.
Security built in
Managing the massive amounts of data that the IoT will create also means building in security measures like we’ve never seen before. Before an IoT deployment even begins, developers need to assess security issues of the infrastructure, analyzing the possible risks and potential for cyber threats. A thorough audit includes all devices, networks and the cloud, measuring fraud impact against the cost of protection.
Devices need to be secured with robust identities and authentication procedures for the ultimate in security. Security lifecycle management will also help IoT devices adapt to dynamic threats and respond appropriately.
Data in the IoT infrastructure has to be protected along every point and at every destination. Data encryption and integrity protection will be critical in minimizing threats in any organization.
Infrastructure development and maintenance will be critical in Internet of Things applications not only for real-time processing and accessibility but also for the proper security measures that keep an organization and its data safe. Planning and maintaining an effective infrastructure will be an ongoing process and a critical one in ensuring data integrity for all involved.