Blueprint: Rethinking Mobile Infrastructures for IoT

by Don DeLoach, CEO of Infobright

The sheer magnitude of machine-to-machine (M2M) data currently being generated by the Internet of Things (IoT) is mind-blowing. Global mobile data traffic grew 69 percent in 2014 according to a recent Cisco report, and that data is expected to increase nearly tenfold with 11.5 billion mobile-connected “smart” devices (including M2M modules) estimated to be in existence by 2019.

The report’s researchers say that growth in mobile data traffic can be traced to the rapid growth of M2M applications and mobile devices such as tablets and smartphones as the IoT – which delivers this data through M2M interfaces such as surveillance video systems, utility meters and GPS devices – is only expected to grow from its 109 million figure in the current market to 578 million by 2019. Each year, according to the report, several new devices in different forms such as smartwatches or tablets along with increased capabilities and intelligence are introduced to the market, accounting for nearly half a billion mobile connections and devices added in 2014.

What this all boils down to is that the implementation of the Internet of Things over the next few years will create a powerful, vast amount of M2M data in the hands of mobile network operators looking to glean actionable business insights from it. The problem is, not all that data is essential to the business’ bottom line. If a network operator needs to find out how many end-users are women between 18-35 years old, then end-users who are men, or outside of that age range, would not be practical for the immediate business need at hand.

The IoT is about analyzing the true value, or the utility value, of the data that will effect real change to improve whatever end result is desired by a company, such as product development, marketing campaigns, customer support resolution or SLA root cause monitoring. This is the real “Holy Grail” of the Internet of Things. This means that in order to gain the most out of their bottom line, telecoms and their service providers need to take a hard look at where their current infrastructures are falling short in collecting, storing and analyzing this wealth of data and identify the areas in which they need updating so that they can quickly and efficiently decipher the true data sets specific to their needs. Innovative companies must rethink legacy systems in order to address the sheer volume and velocity of data sets never before seen prior to the IoT explosion.

So let’s take a look at exactly how telecoms should be rethinking their infrastructures to meet these new data demands.  For starters, they should implement an explore and exploit approach to collecting, ingesting, storing, and querying new sets of data. With the explore side of the equation, it is essential for telecoms to keep a close watch on the interesting pieces of information within the data (and only the interesting pieces) that will enable them to yield the exact results they are looking for.  If they wouldn’t expend time and/or money on useless details that won’t add anything to their bottom line, why waste resources in the beginning looking for them? Once telecoms have identified those interesting data sets, they are then able to move to the exploit side of the coin, where they can reproduce that valuable insight so that they can continue to use it to change how their business works.

But in order for telecoms to even start approaching this vital explore and exploit approach to data collecting, they must ensure that their infrastructures are able to hold an enormous volume of data, held over a long period of time, and received as close to real-time as possible. This is a very different proposition from traditional analytics, which deals with this volume in a monolithic relational database and, in a lot of cases, sacrifices some functionality for the ability to load that data quickly as possible. For telecoms to gain and maintain a competitive edge, they must embed within their infrastructures real-time investigative or ad-hoc analytics solutions to provide value-added and customized services to their end-customers. One way of doing so lies with Hadoop, which has grown in popularity as a cost-effective and highly scalable way to store and manage big data. Data typically stored with Hadoop is complex, from multiple data sources, and includes structured and unstructured data. However, companies are realizing that they may not be extracting the full value of their data with Hadoop due to a lack of high-performance ad-hoc query capabilities.

To fully address the influx of M2M data generated by the IoT, telecoms can deploy a range of technologies to leverage distributed processing frameworks like Hadoop and NoSQL and improve performance of their analytics, including enterprise data warehouses, analytic databases, data visualization, and business intelligence tools. These can be deployed in any combination of on-premise software, appliance, or in the cloud.

The reality is that there is no single silver bullet to address the entire analytics infrastructure stack. Specific business requirements will determine where each of these elements plays its role. The key is to think about how business requirements are changing and move the conversation from questions like, “How did my network perform?” to time-critical, high-value-add questions such as, “How can I improve my network’s performance?”

The ability to compete based on analytical maturity, coupled with the overwhelming contribution of new data coming from the multitude of IoT devices and sensors, means conventional ways of storing and analyzing data will need to adapt. By maximizing insight into the data, mobile network operators can make better decisions at the speed of business, thereby reducing costs, identifying new revenue streams, and gaining a competitive edge.

About the Author


Don DeLoach is CEO and president of Infobright. Don has more than 30 years of software industry experience, with demonstrated success building software companies with extensive sales, marketing, and international experience. Don joined Infobright after serving as CEO of Aleri, the complex event processing company, which was acquired by Sybase in February 2010. Prior to Aleri, Don served as President and CEO of YOUcentric, a CRM software company, where he led the growth of the company before being acquired by JD Edwards in 2001. Prior to YOUcentric, Don spent five years in senior roles at Sybase.  He has also served as a Director at Broadbeam Corporation and Chairman of the Board at Apropos Inc. Don currently also serves on the Board of the Illinois Technology Association as well as the Board of the Juvenile Protective Association.

About Infobright

Infobright delivers a high performance analytic database platform that serves as a key underlying infrastructure for The Internet of Things. Specifically focused on enabling the rapid analysis of machine generated data, Infobright powers applications to perform interactive, complex queries resulting in better, faster business decisions enabling companies to decrease costs, increase revenue and improve market share. With offices around the globe, Infobright’s platform is used by market-leading companies such as Mavenir, Yahoo! Bango, JDSU and Polystar. For more information on Infobright’s customers and solutions please visit www.infobright.com