Innovation is essential for companies that maintain business relevance and avoid business interruptions, but where will these innovations appear?

　　Industry experts believe that innovation will not happen in the cloud, but at the edge. However, edge computing is only an extension of cloud computing. So what does this mean? Because cloud computing and edge computing may work together.

　　 In addition, whether the facial recognition technology adopted by Apple's iPhone X mobile phone will bring greater risks to users' personal information, which has attracted people's attention.

　　 Prior to this, Apple’s smart devices used fingerprint recognition technology, while some Android smart devices used iris recognition technology. Therefore, the plot in science fiction quickly became a scientific fact.

　　Enterprises need to take precautions, especially the EU’s "General Data Protection Regulation (GDPR)" that will take effect five months later. In order to ensure that retailers, government agencies, emergency service agencies, and other organizations do not violate regulations and standards, people need to consider whether the use of facial recognition, license plate recognition, vehicle sensors and other technologies can meet GDPR regulations and requirements.

　　 empower citizens

Jim McGann, Vice President of Marketing and Business Development at Index Engines, put forward his own thoughts on these legal regulations: "GDPR delegates the power of personal data to citizens. Therefore, companies that do business in the European Union (including the United States) must comply with this regulation. ."

　　 He added that GDPR raises a key issue for organizations to manage data. Many times, it is difficult for organizations to find personal data in their systems or paper records. And usually they cannot know whether the data needs to be saved, deleted, modified or corrected. Therefore, due to the possibility of facing huge fines, GDPR will push the responsibility of the organization to a new level.

However, he offered suggestions for adopting relevant solutions: “We provide information management solutions and application strategies to ensure that the organization’s business complies with data protection regulations. PB-level data needs to be sorted out, but the organization does not know what kind of data exists. Real understanding. Index Engines provides services to clear this data by looking at different data sources to understand what can be cleared. Many organizations can release 30% of their data, which allows them to manage data more effectively. Once the organization can By effectively managing data, they can implement corresponding strategies and measures, because most companies know what types of files contain personal data."

  clear data

　　 McGann continued: “Most of the data is very sensitive, so many companies are reluctant to talk about it, but we have also done a lot of work through legal consulting companies to make organizations comply with regulations.”

　　 For example, Index Engine, a Fortune 500 electronics manufacturer, has completed data cleaning. The company found that 40% of its data no longer contains any commercial value. Therefore, the company decided to remove it.

He pointed out: "This can save the management cost of the data center: They have obtained positive results by cleaning the data, but if it is a listed company, they cannot delete the data at will, because there are regulatory compliance issues." In some cases, Need to save files for up to 30 years. He suggested that “companies need to ask whether these files have commercial value or any regulatory compliance requirements.” For example, if there is no legal reason to save data, then it can be deleted. Some companies are also migrating their data to the cloud in order to delete data from the data center.

　　In this process, many companies need to check whether the data has commercial value in order to make their data migration decision. Organizations need to consider what's in their files—whether it's edge computing or cloud computing for data management, backup and storage.

　　Ensure information compliance

　　 Therefore, it is important for organizations to explore how to prevent new technologies from being used in ways that consumers and citizens do not like, and to consider how to use these data to create value for organizations and consumers. This is very important. And organizations that use these data need to pay attention to information security in providing, using, protecting, and improving digital services.

　　 For example, there are many applications for facial recognition technology, which not only allow users to unlock applications on their smartphones, but can also be used to pay for fees. Through the facial recognition technology of the smartphone, the image is stored in the locally deployed data center. Nevertheless, people still need to keep a certain amount of data in the database, and these data also need to be protected to prevent hackers from using personal data for malicious attacks.

　　Innovation in edge computing

With the increasing investment of organizations in autonomous vehicles and smart cities, as well as the development of connected car technologies such as automatic emergency braking (AEB), it is also necessary to consider places for innovation in 2018 and whether there is a need to achieve between regulatory compliance and innovation balance.

　　 In addition, more and more people believe that innovation will appear in edge computing instead of cloud, and edge computing is just an extension of cloud computing. Even if the data is to be analyzed close to the source, a large amount of data still needs to be analyzed in other places. Data and network latency is a historical obstacle, and people hope that the impact of latency can be reduced or eliminated.

Edge computing can expand the capabilities of data centers, allowing a large number of smaller data centers to store, manage, and analyze data, while allowing some data to be managed and locally analyzed by a disconnected device or sensor (such as connected autonomous cars) . Once there is a network connection, its data can be backed up to the cloud for further action.

　　 data acceleration

　　Reducing network latency and data latency can improve customer experience. However, due to the high possibility of data transmission to the cloud, network delay and packet loss may have a considerable negative impact on data throughput. Without machine intelligence solutions such as PORTrock IT, the effects of latency and packet loss may inhibit data and backup performance.

　　 If the database of facial recognition technology cannot quickly transmit citizenship and immigration information, this may cause airport delays, accidents or technical problems with autonomous vehicles.

　　 With the advent of autonomous vehicle technology, data generated by cars will travel between vehicles in a continuous way. Some of these data (such as critical status and safety data) require fast-response turnover, while other data is usually road information, such as traffic flow and driving speed. Self-driving cars send all safety-critical data back to the central cloud location through the 4G or 5G network. Before the data is received, due to network delays, a large amount of data delay may be added during the turnaround. However, there is no simple and economical way to reduce the delay between networks. The speed of light is the main factor that people cannot change. Therefore, how to effectively and efficiently manage network and data delays is crucial.

　　The challenge of massive data

　　 Hitachi said that autonomous vehicles will create approximately 2PB of data per day. It is expected that connected cars will create approximately 25 terabytes of data per hour. Consider that there are more than 800 million cars in the United States, China and Europe. Therefore, in the near future, it will exceed 1 billion vehicles. If half of the cars have a full network connection, assuming an average of 3 hours a day, then 37.5 billion gigabytes of data will be created every day.

　　 If, as expected, most of the new cars were self-driving cars in the mid-2020s, then the above figures are trivial. Obviously, not all data can be immediately transmitted back to the cloud without a certain degree of data verification and reduction. There must be a compromise solution, and edge computing can support this technology, which can be applied to autonomous vehicles.

　　 From a physical point of view, storing increasing amounts of data will be a challenge. The size and scale of the data is sometimes very important. This creates financial and economic issues of cost per GB. For example, although people think that electric vehicles are the mainstream of the future, power consumption will inevitably increase.

　　 In addition, it is also necessary to ensure that large amounts of data created by individuals or devices do not violate data protection legislation.