In the 40 years since the first appliance – a Coke machine at Carnegie Mellon Universitywas connected to the internet; the internet has grown up. Today, 53.6% of the world’s population enjoys internet access, almost 30% have smartphones, and the typical American consumes nearly two hours of smartphone media per day. Still, until now, the possibilities inherent in Carnegie Mellon’s network connected Coke machine have never been properly explored. Enter the Internet of Things (IoT).
A network of devices replete with embedded sensors and chips, the IoT allows for the collection and exchange of data about and between disparate devices. Such devices range from smart thermostats to jet engines, which can produce 1TB of data per flight. The number of IoT devices in use globally is expected to increase from 6.4 billion to between 20.8 and 30 billion by 2020 (see Figure 1) catalyzing revolutions in everything from transportation to manufacturing.
Figure 1: Estimated Number of Connected Devices by 2020 (billions)
One subset of the IoT, the Industrial Internet of Things (IIoT), will have a direct impact on the management of data centers. The IIoT applies the power of the IoT to industry in order to increase production efficiency and minimize downtime. Current spending on the IIoT is conservatively estimated at $20 billion, but is predicted to grow to $514 billion by 2020 with a potential to generate $15 trillion in value by 2030vi.
Broadly, the impact of the IoT on data centers falls into two categories: efficiency improvements and load increases. To improve efficiency Data centers will start to employ predictive instead of preventative maintenance, which is expected to reduce maintenance costs by 30%vii. At the same time, data centers will have to cope with vast new flows of data. IoT traffic is forecast to triple to almost 2.2ZB by 2020. This will require both an expansion of existing data center capacity, as well as a move towards distributed edge data centers.
Using IoT for predictive maintenance
The shift towards predictive maintenance will revolutionize how work is carried out in data centers and beyond.
Predictive maintenance uses IoT capable devices to collect data about assets and feed it into machine learning algorithms that are capable of predicting when assets will fail. Instead of being reactive (performing corrective maintenance after failures have occurred) or preventative (performing maintenance at regularly scheduled intervals), assets will be able to signal to technicians when they require maintenance. With the emergence of the IoT, data can now be fed from devices into data center infrastructure management (DCIM) systems, where machine learning algorithms can identify patterns that indicate an asset is at risk of failing. By combining this capacity with the real-time monitoring and change management capabilities of a DCIM, operators can perform maintenance before failures even occur. This minimizes downtime and avoids unnecessary maintenance cycles.
A survey by the Aberdeen Group predicts a 13% YoY decrease in maintenance costs as well as a 24% increase in the return on assets, purely by switching to a predictive maintenance model. The costs of such predictive technologies, for example, sensors and computing power, are recouped several times over by the decrease in maintenance costs, downtime, and risk of system failure. In 2013, a single failure at Amazon resulted in 30 minutes of downtime and cost the company an estimated $2 million. Predictive maintenance promises a revolution in how data centers are maintained in addition to substantial cost savings. Data center operators should be eager to embrace the changes brought about by the arrival of the IoT.
Managing load increases using IoT
Efficiency improvements will be especially vital in addressing the IoT’s second major impact on the data center industry: load increases. The huge amount of data generated by billions of internet connected devices will strain data center resources. Cisco estimates the amount of data generated will increase from 145ZB in 2015 to 600ZB in 2020 (although about 90% of this is ephemeral and will never be transmitted)vii. In a 2014 paper, Gartner argues that the WANs linking data centers to customers are sized for the amount of data generated by humans but not for machine to machine (M2M) interactions. Fabrizio Biscotti, research director at Gartner, argues that "IoT deployments will generate large quantities of data that need to be processed and analyzed in real time […] leaving providers facing new security, capacity and analytics challenges.”x Data centers will have to grow more efficient even as they expand their offerings. Additionally, Gartner VP and analyst Joe Skorupa argues that due to the global distribution of IoT data, handling and processing all of it at a single site will be neither technically nor economically viable. All this suggests a move away from traditional hyperscale data centers and towards increased edge deployments will be desirable in the years to come. Operators will have to acquire the tools and expertise required to efficiently manage multi-site, distributed infrastructures.
Figure 2: Data Generated by Connected Devices (in ZB)vii
With the rise of the Internet of Things, the next 5 to 10 years promises a revolution in the design, maintenance, and use of data centers across the world. As humanity comes to rely on smooth access to data and calculating power,especially with the advent of driverless vehicles, downtime will become increasingly unacceptable. Luckily, sensors and artificial intelligence promise to open up a new frontier in predictive maintenance for those data centers prescient enough to make the switch. This, combined with a move towards edge data centers, will allow the industry to cope with the massive, globally distributed influx of data. It has been 40 years in the making but the Internet of Things is finally here and it is here to stay.
Author: Thomas Menzefricke
Palmer, D. (2015, March 12). The future is here today: How GE is using the Internet of Things, big data and robotics to power its business. Retrieved October 12, 2017, from https://www.computing.co.uk/ctg/feature/2399216/the-future-is-here-today-how-ge-is-using-the-internet-of-things-big-data-and-robotics-to-power-its-business
Cisco Global Cloud Index: Forecast and Methodology, 2015-2020 (White Paper). (2016). Retrieved October 12, 2017, from Cisco website: https://www.cisco.com/c/dam/en/us/solutions/collateral/service-provider/global-cloud-index-gci/white-paper-c11-738085.pdf
Six steps to using the IoT to deliver maintenance efficiency. (n.d.). Retrieved October 12, 2017, from https://i.dell.com/sites/doccontent/shared-content/data-sheets/en/Documents/DELL_PdM_Blueprint_Final_April_8_2016.pdf
Clay, K. (2013, August 19). Amazon.com Goes Down, Loses $66,240 Per Minute. Forbes. Retrieved October 12, 2017, from https://www.forbes.com/sites/kellyclay/2013/08/19/amazon-com-goes-down-loses-66240-per-minute/#4ffd2605495c