Four trends to watch out for in 2018

Even with all the coffee or energy drinks in the world, humans still need sleep. Doctors recommend seven to eight hours of sleep a night to be at their best during the day. But machines don’t have the same limitations. Machines don’t need breaks or vacations. They can run 24 hours a day, seven days a week. That means they’re sensing, analyzing, and transmitting data all the time.

According to IDC, there are expected to be 8.6 billion connected devices in the Asia Pacific region by 2020. For these devices to function properly, billions of machines around the world need to run 24 hours a day, 7 days a week.

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Obviously, there are more devices than people in the world. When all these devices and computers start talking to each other, it puts a lot of pressure on any network. Starting in 2018, as the IoT market in Asia Pacific continues to grow, this pressure will increase. According to IDC, by 2020, the market size will reach 583 billion US dollars. For the Chinese IoT market, the "Internet Plus" action plan proposed by the Premier in his 2015 Government Work Report also pointed out that the integration of modern manufacturing and infrastructure should be promoted through technologies such as IoT.

Looking ahead to 2018, we will see data centers impacted by machine-to-machine communications in four ways:

Laying the foundation for 5G

Yes, 5G will happen in the data center, too. All the devices that need to communicate with each other and with people will drive higher demand for fiber, especially as we look at 5G, which is expected to be available in the next 5 to 10 years. There is still a lot of preparation to be done before 5G officially arrives. Wireless networks require a large number of "wired" assets to effectively deliver fiber backhaul to the core and edge of the network. 5G is also required for the densification of cellular base stations (such as small cells). In addition, there will be a variety of new power solutions on the market, allowing operators to power various devices at the edge of the network in a more cost-effective way.

Low latency

Machines are able to process the information they receive in real time, which is difficult for humans to do. Especially in data centers, decisions are made in an instant, which requires a strong network backbone to support. Unlike the past when data centers only played the role of data storage, today's data centers need to calculate, analyze and process information in real time. IDC listed the "modernization" of data centers as one of its important predictions for 2018, "predictive analysis will be used extensively to improve accuracy and reduce downtime." Countries and regions such as Hong Kong and Japan have a more urgent need to build modern data centers due to land scarcity, and edge computing will play an important role.

Higher density and speed

Deploying more fiber is of course the best solution, but reality does not always allow it. The most effective solution is to deploy high-density fiber from the beginning to enable machine-to-machine communication to be realized quickly. Therefore, a modular high-speed platform that can support multiple generations of equipment is the best choice.

Intelligent and automated management

People are increasingly unable to process complex data, and the probability of human error is much greater than that of machines, so the things done by machines need to be managed by machines, and all management and maintenance links need to be participated by machines to improve reliability and availability. For example, network management needs to be automated, data center management needs to be automated, and cabling system management also needs to be automated.

The most cited machine learning examples

A pilot project in Pittsburgh has made self-driving cars a reality. The project has been able to proceed smoothly thanks to a strong network and near-perfect sensors. The car can process data faster than any human driver, like a data center on wheels! We can also see similar projects in China, such as Baidu's "Apollo" autonomous driving technology open plan. According to Lu Qi, president and chief operating officer of Baidu Group, artificial intelligence technology has great potential in promoting social development, and smart cars are one of the biggest industrial opportunities.

Compared to humans, cars can stay awake, not text while driving, not feel sleepy while driving, and have faster reaction times. As long as cars can make the right decision at the right time, they can drive into the future.

But humans have been driving for a century. We make mistakes, so should computers replace the human drivers who are behind the wheel today? Computers or machines don't have sympathy, empathy, or any emotions, so are they missing something human in that sense?

It depends on how you look at it, after all, machines are only as good as their algorithms and programming. They can be easily manipulated (hackers) by humans or other machines. In fact, according to Gartner, by 2022, most people in mature economies will consume more false information than true information. It can even be said that false information will "facilitate large financial fraud." With more devices than people on the planet, it can be said that we are becoming more vulnerable to hacking and data theft.

As digital payments take off in the Asia-Pacific region, we are increasingly concerned about digital security. With WeChat, China is at the forefront of digital payments, and we also see countries such as India and Singapore steadily advancing the development of digital payment technology. Therefore, security will become more important, including the issue of data privacy. As more and more countries formulate laws and regulations related to data sovereignty, we can expect to see more data center operators, especially hosting service providers, invest in data sovereignty and commit to fully addressing security issues.

There is a school of thought that machines will take over jobs that once might have only been done by humans. With the introduction of artificial intelligence (AI), it is inevitable that some roles played by humans will be replaced. However, this does not necessarily mean that people will lose their jobs. What we will see is a shift in roles, and people are being equipped with new tools to work more efficiently. For example, high-precision robots can increase consistency and accuracy to a level that is difficult for humans to achieve, especially in technologies such as fiber optic connections and circuits. Gartner also reports that by 2020, machine learning technology will abolish 1.8 million jobs, but create 2.3 million jobs. There are still many jobs for us humans to do, although they may be different from what we are doing now.

The world won’t be run by robots alone anytime soon. People need to change their mindset and let go of machine-to-machine technology. There will be problems along the way, but this will be a big step forward for the “Fourth Industrial Revolution.” The industry is evolving, and now is the time to get involved.

About the author Wu Jian:

As CommScope's Technical Director for North Asia, Mr. Wu Jian leads the technical team in North Asia to complete pre-sales and after-sales technical support, product promotion and technical training for projects in North Asia.

Mr. Wu Jian has been engaged in the design, management and maintenance of cabling systems and network systems since 1995. He has participated in the planning, design and implementation of many large-scale national projects and has presided over the installation guidance and acceptance testing of large-scale integrated cabling projects. He has also been hired as a consultant to participate in the design, planning and construction of many large data centers.

In the professional field, he is proficient in integrated cabling design and installation and network integration, familiar with data communication theory, good at network testing and network management, and has rich experience in the planning and design of large data centers. He is currently the deputy leader of the integrated cabling working group of the Information and Communication Professional Committee of the China Engineering Construction Standardization Association and an expert member of the China Data Center Expert Technical Committee. At the same time, he actively participates in the drafting and formulation of multiple domestic related standards.

Mr. Wu Jian also has many years of experience in university teaching, teaching courses such as computer networks, integrated cabling, and network security. He was an authorized lecturer for the Cisco Networking Academy.

Mr. Wu Jian holds a master's degree from the University of Science and Technology Beijing, CCNP teacher certification from Cisco Networking Academy, CCTT instructor certification from Fluke Networks, CDCS certification for data center experts, and DCDC data center design expert certification from BICSI.