**4. Connected the unconnected world and things: an evolution in connectivity beyond the 5G revolution**

The future of the connected world is not only about the latest cutting-edge technologies, such as the constellations of high-speed 5G and low earth orbit satellites. Much will be defined by the advancement and development of current advanced connectivity technologies, such as fiber, low to medium band 5G, 6G, and different other long and short-range solutions. The modern connectivity architecture also includes cloud and edge computing which is accessible with less expensive and more efficient devices and platforms as well as the FPGA SoC (discussed in the above section), as depicted in **Figure 3**. Computing power, storage, and sensors are all getting more robust and reasonable. With the converges of these trends, the connectivity ecosystem will be dominated with more technologies, services, and vendors more than before.

The new and improved networks will enable and complement other critical technologies such as cloud computing and FPGA SoC-based edge computing. These developments, when combined, will allow some of the most data-intensive applications of the future. Cloud computing will keep to serve as a processing backbone for use cases that need a high level of computing power, storage capacity, and complex data analysis capabilities. This computing is required for a variety of

*Future Internet of Things: Connecting the Unconnected World and Things Based on 5/6G… DOI: http://dx.doi.org/10.5772/intechopen.104673*

**Figure 3.** *The future trend of the connected world and things.*

tasks ranging from storing films to training artificial intelligence systems. Users' devices may not be able to run the most complex applications without a boost from cloud computing, or they may have to be considerably more expensive. On numerous fronts, FPGA SoC-based edge computing tries to alleviate some of the constraints of cloud computing. Instead of sending data to central cloud servers that may be hundreds or even thousands of miles away from the end user, FPGA edge computing delivers computing power, storage, and networking closer to where data is created or consumed. Actual computing could then take place in smaller-scale data centers on the outskirts of major cities (the metro periphery), at the base of radio access network base stations (the micro-periphery), in wiring closets at end-user premises (the Edge Gateway), or even on the device that generates data itself (the Edge device).

A number of factors are driving the urge to bring processing and storage closer to the end-user. The first is the proliferation of linked devices, particularly as the Internet of Things is implemented in an increasing number of locations. According to a recent IDC [57], prediction, there may be up to 42 billion linked IoT devices by 2025. These technologies are also growing more complicated, progressing from simple smart devices to intelligent linked systems and processes. As the number of increasingly complicated devices grows, so does the volume of data created, which may surpass what a centralized cloud can handle, especially as IoT applications rely more on video processing and ultra-high-definition audio. As a result, there is an increased demand for efficient storage that assures data protection. Another important driver of edge computing growth is the desire for real-time analytics, decision making, and changes. These features are critical for applications such as augmented and virtual reality, linked vehicles, drones, video surveillance, and industrial machinery remote control. This requirement for low latencies reduces transmission time to the cloud.

Also, application development is moving towards new solutions such as containercentric architecture, micro-services architecture, and server-less computing platforms. These solutions provide lightweight, portable alternatives for running applications at the edge, allowing developers to perform testing and maintenance faster and more efficiently. Finally, edge computing addresses a fundamental requirement for industrial operators managing transportation and logistics networks or remote facilities. They may now connect to compute, storage, and analytics resources in contexts with sporadic or restricted connection, as well as in extremely remote locations.

All those different factors point to the upgrading adoption of edge computing around the world. While it took 10–15 years for cloud computing to mature, edge computing is on a faster trajectory. The cloud ushered in a paradigm shift that shifted software and computing power from owned products to delivered services. Edge computing could be seen as an extension of this move towards a more decentralized model. The emphasis today is on defining the architecture (especially emerging industry standards for application development and maintenance, and for interoperability between edge, device, and cloud). Its acceptance may pick in speed once it becomes available.
