Blog

Fog, Edge and the Internet of Things

Share on FacebookTweet about this on TwitterShare on LinkedInShare on Google+Email this to someonePrint this page

Wireless broadband communications has been an integral part in the realization and proliferation of the Internet of Things (IoT). Where terrestrial communications like fiber is not available, wireless communications like cellular and satellite have quickly stepped in to provide the communication means to enable the flow of data.

However, with the increased push towards connecting more devices to the Internet and big data pushing billions and billions more bytes over our networks, there has been a slight shift in the architecture of some of these deployments. Where previously companies would design their networks to push a constant stream of data from the “edge of the network” to a central server (or the Cloud), now network architects find themselves asking whether it is necessary to have this constant flow of sometimes meaningless data. Is it better to do some of the data processing in the field (or edge) before sending the data to the Cloud?

Edge Analytics and Fog

The concept of edge analytics is not new but carries an important benefit that is often overlooked. There is a cost to send every status report. Whether it is wireless airtime or space on the Cloud/server, does it make sense for companies to incur costs for data that provides no value? As the number of devices, sensors and actuators on the internet compounds, this question becomes even more relevant.

Many Machine-to-Machine (M2M) and IoT companies are spending more time addressing the issue of relevancy in data. Big Data pundits are emphasizing the value of “smart data” rather than just “volume of data”. Cisco is pushing the concept of Fog computing where Cloud computing and services are pushed to the edge of the network. Like in the Cloud, Fog provides data, computational, storage, and application services to end-users at the edge.

Edge analytics and/or Fog enables data analytics processes to convert data into actionable information. It reduces service latency and improves Quality of Service (QoS) to support the real-time demands of industrial automation and other applications with a network of sensors and actuators.

Example of Edge Analytics for Smart Grid

In Latin America, SkyWave IDP satellite terminals are being used to provide the primary and backup communications to monitor and control reclosers in Smart Grid applications. The reason for choosing M2M asset tracking devices rather than broadband devices is that they are a lower cost solution for applications that only need to send small amounts of data.

The other reason for choosing M2M devices is that many, such as SkyWave IDP devices, offer the ability to embed edge analytics capabilities. “Intelligence” can be added to the device to control the information exchange between the remote site and the cloud. Tools like thresholds and filters allow only vital messages, like changes in current, voltage and power factor information, and commands to be transmitted and reduce the amount of data sent wirelessly.

In areas with no RTUs or IEDs, Modbus or DNP protocol can be embedded into the intelligent terminal thereby integrating with legacy equipment and allowing them to be more readily part of the IoT.

DigitalOilExample of Edge Analytics in Oil & Gas

Edge analytics is also occurring in the oil and gas industry as more of their equipment and sensors go online. A large Latin American petroleum company had technicians drive to gas well sites multiple times a day to read, pressure, volume of gas being extracted, open/close valves and check the general health of the equipment.

This workflow meant data was analyzed six or more hours after it was collected which inhibited the ability to maximize gas production. By adding real-time monitoring, communications and analytics capability at the edge, only vital data like instantaneous high and low pressure and flow; average high and low pressure and last hour volume is now being sent wirelessly. With threshold settings, any out-of-range values are sent as well.

Edge computing also supports automatic opening and closing of valves without the intervention of a technician. This has enabled the company to increase production by more than 30 per cent.

Sizable Market for Analytics

According to ABI Research, revenues from products and services involved in analytics related to the IoT are poised to reach $5.7 billion in 2015. IDC thinks the big data and analytics market will reach $125 billion worldwide.

In addition to sizable market potential, IDC says that applications incorporating advanced and predictive analytics will grow 65 per cent faster than applications without predictive functionality. IDC also says that the adoption of technology that continuously analyzes streams of events will accelerate in 2015 and is expected to grow at a five-year compound annual growth rate (CAGR) of 30 per cent.

With the proven examples, support of industry leaders and increasing demand for network resources, it is clear that Fog and edge computing are here to stay.

Originally appeared in Remote Magazine.

Share on FacebookTweet about this on TwitterShare on LinkedInShare on Google+Email this to someonePrint this page
Anu Sood
About

Anu Sood, Director of Channel Marketing at ORBCOMM, has nearly two decades of expertise in the telecommunications, software development, and satellite industries.

Posted in 4. Oil & Gas / Utilities, 5. M2M/IoT Trends Tagged with: , ,

Leave a Reply

Your email address will not be published. Required fields are marked *

*

Sign Up for Updates

Follow Us

ORBCOMM on Twitter