According to analysts, the number of connected devices is expected to triple in the next 4 years, mainly due to IoT. That many connected devices will require a lot of additional hardware, software, platforms, databases, and networks. NB-IOT will be merged into 5G, fueling the demand for a flexible way to slice the network and hence fueling the demand for network virtualization.
Virtualization will support the business requirement to be able to provide dedicated IoT systems, for example a private area network and services on top of the IoT devices for a particular industrial customer. Each type of IoT device offering will need its own quality of service and Service Level Agreements. For example, a hospital solution with connected heart rate monitors requires much more uptime and responsiveness than a soda vending machine. Therefore we see a great demand for continuous and secure monitoring of the quality of these virtualized IoT offerings. One of the best ways to collect information about the quality of these devices, is by collecting the information through an applet on the embedded SIM or eSIM. For example, our cooperation with SIM card maker G&D, allows us to collect statistics on device uptime, battery, and network connectivity.
With the need to quickly provide different types of virtual network and services around IoT devices along with various SLA and quality expectations, the complexity to manage these services increases rapidly. Therefore, we see a key role for end-to-end life cycle management and automation. When a new IoT service is designed, it takes days rather than months to design, test, and launch a new service by using DevOps style tools. Once a new IoT service is up and running, the life cycle manager continuously monitors the health of the underlying infrastructure, the virtual network functions and components, as well as the end-to-end service quality monitored on the devices through the SIM collected quality data. Automated policy decisions by the life-cycle manager then eliminates the need for manual monitoring and intervention to continue the service with the associated quality expectation.
True autonomous life cycle management based on continuous quality monitoring is the only way to address the growing complexity in launching and operating the variety in IoT devices and services.