Much has been written about the vast number and variety of things that will soon be connected to the Internet—from milk cartons and alarm clocks to sensors and trains. Already in 2008, that number exceeded the number of people on earth. By 2020, when the next incarnation of the Internet—aka the Internet of Things—is in full swing, the number is expected to reach 50 billion. And it’s not just things that will add value and relevance to networked connections, but also people, data and processes.
Think about it. Through their interactions with the Web, social networks and devices—especially mobile devices—people have a massive multiplier effect on the amount of IP traffic traversing the network. In 2012 alone, new, more powerful smartphone technologies combined with growth in both mobile bandwidth and apps produced annual mobile data traffic nearly 12 times greater than the total Internet traffic in 2000 (Cisco Mobile VNI 2013).
Add to that a coming tsunami of constantly streaming data as sensors in just about everything become the norm—not just wearable sensors attached to our bodies, clothes and shoes, but also sensors, meters and actuators in our cars, machinery and infrastructure. And let’s not forget the critical role that processes will play in managing and automating this explosive growth in connections as well as in the collection, analysis and communication of data. People, data, processes and things. Together, they will make up the next phase of the Internet of Things—the Internet of Everything.
Data in Motion vs. Data at Rest
Zooming in on data in the age of the Internet of Everything, there’s another critical distinction that needs to be made. You see, not all data is created equal. Most of the new data being generated today is real-time data that fits into a broad category called Data in Motion. This refers to the constant stream of sensor-generated data that defies traditional processes for capture, storage and analysis, and requires a fundamentally different approach.
Let’s back up a minute. Historically, in order to find gems of actionable insight, enterprises have tended to focus their analytics or business intelligence applications on data captured and stored using traditional relational data warehouses or “enterprise historian” technologies.
However, the limits of this approach have been tested by the increase in volume of this so-called Data at Rest. The challenges inherent in collecting, searching, sharing, analyzing and visualizing insights from these ever-expanding data sets have led to the development of massively parallel computing software running on tens, hundreds, or even thousands of servers. As innovative and adaptive as these Big Data technologies are, they still rely on historical data to find the proverbial needle in the haystack.
This rising tide of Data in Motion is not going to slow down. In fact, as the Internet of Everything gathers momentum, the vast number of connections will trigger a zettaflood of data, at an even more accelerated pace. While this new Data in Motion has huge potential, it also has a very limited shelf life. As such, its primary value lies in its being captured soon after it is created—in many cases, immediately after it is created.
For instance, real-time traffic information from cameras, sensors and connected cars allows drivers to avoid traffic jams and use suggested alternate routes, potentially reducing hours of unproductive time spent behind the wheel. Similarly, manufacturers can connect their stock inventory with their suppliers’ production systems so that potential delays can be identified as early as possible and corrective actions taken on their respective shop floors to better prioritize people’s activities. In each of these cases, it’s easy to see the added value of connecting not just things, but also people, data and processes.
The real challenge for data-driven organizations is how to manage and extract value from this constant stream of information, and turn it to competitive advantage. Data in Motion represents a new type of data whose value can not always be extracted through traditional analytics. In a next post, we will look at examples of Data in Motion and how to extract value from it.
If you’re like me, you probably remember the days when computers meant oversized monitors, loud, humming power supplies, and more cables than you knew what to do with. Thanks to Moore’s Law, those days are long gone. With devices getting less costly, smaller, and capable of more efficient computing power, people and businesses of today and tomorrow have more opportunity to connect to the Internet of Everything (IoE).
Take the Raspberry Pi, for example. This low-cost computer was developed to provide computer science learning experiences for children around the world. For $35, the device features USB ports for a keyboard and mouse and an HDMI port to hook up to a monitor. The Raspberry Pi Foundation officially launched the device in February 2012. By September, more than half a million had been sold, and thousands were being manufactured each day, making computing accessible to everyone.
But even more interesting, when the Raspberry Pi went on sale, hackers and experimenters ordered them by the handful to create special purpose applications. They dedicated a whole low-cost computer to the task and moved the computing function to the edge of the network, shifting how we solve the computing problem. So again, we now have another Moore’s Law phenomena. As computers get smaller, more energy efficient, and less expensive, it causes us to rethink where we put the computing in the network and whether it is centralized or at the edge. Moore’s Law enables this natural progression, allowing us to recentralize through the web and distribute through the cloud.
The Nest Thermostat demonstrates a great example of this. Through a combination of sensors, algorithms, machine learning, and cloud computing, Nest learns behaviors and preferences and begins to adjust the temperature up or down. It can be controlled from your laptop, smartphone, or tablet, and it starts to recognize your preferences, automatically adjusting faster and faster and becoming more and more efficient. You have an entire computer (thermostat) on the wall, a classic convergence of more and more things being connected.
This, in turn, changes what’s happening in the data center and the cloud, because having more entry points enables us to connect more things. Sensor technology is also being affected, becoming smaller and less expensive. Texas Instruments now makes a chip that runs an IPv6 stack for connectivity, has built-in wireless, and only costs ninety-nine cents. Moore’s Law has led to a low-powered, low-cost chip, giving us yet another opportunity to rethink and innovate the use of computing.
With these growing ubiquitous opportunities, we can connect more and learn more. As more devices are added to the network, the power and potential for what they will make possible will continue to grow exponentially. Anything you can measure will be measured. Anything you can sense will be sensed. It’s an economical model making the case to be measured for nearly no cost. This shift will help connect the 99 percent of things that are still unconnected in the world, creating real value for the IoE.
How will the amazing possibilities enabled by the IoE affect you? I’d love to know your thoughts. Send me a tweet @JimGrubb.
As the Internet of Everything evolves and grows, we see more and more innovations focused on convenience, safety and security, thereby impacting parenting. Today, video-enabled baby monitors connect to the Internet and allow parents to watch and talk or sing to their baby from miles away. These types of technologies are just the beginning. The Internet of Everything will enable cribs to monitor vital signs – capturing each time a baby takes a breath -- and collecting sleeping and feeding pattern data.
While much of this technology wasn’t available when my children were small, it is exciting think of the possibilities for the future of parenting.
As my daughter is preparing to go away to college, I often wonder the best way for us to stay connected. For now, I’m going to rely on video chatting. She said the bear didn’t go with her dorm décor.
How would you like to see the IoE impact how you connect with your children? Please join the discussion at: #IoE and #InternetofEverything.
Orchestras are often used as metaphors for all sorts of things--organizational structure, planning sessions and even families.
Have you been to the symphony recently? Musicians sit in a regimented ordering around the stage. The concertmaster sets the tune. The conductor lifts the baton. And then, with the pull of a bow across a string, or breath across a mouthpiece, the music begins. Throughout the performance, each section of the orchestra plays a specific part – either separately or together – to create a harmonized work of art.
The prestigious Czech National Orchestra, known for its versatility, lived up to its reputation during a recent performance (for a new BNP product called Hello Bank!). They put their instruments – some hundreds of years old – aside in favor of newer, more common instruments: smartphones and tablets.
Version 6 of the Internet protocol (IPv6) is a key enabler of the Internet of Everything (IoE). People, data, and things all need IP addresses to connect to the Internet. But we’ve already run out of IP addresses under IPv4, which dictates almost all (98.5 percent) of Internet traffic today. Even with all of the attention IPv6 has received, confusion and misinformation abound.
I’m extremely pleased to have Mark Townsley, Cisco Fellow and recognized industry expert on IP, explore IPv6 over a series of three blogs.
In these posts, Mark will demystify IPv6, discuss how to best make the transition from IPv4 to IPv6, and take a look “under the hood” of IP so that companies and industries can get the most value from IoE. Read More »