Designing for the Internet of Things: A paradigm shift in reliability

More than 50 billion devices are expected to be internet enabled by 2020 [1]. These devices, commonly referred to as the “Internet of Things” (IoT), are expected to become ubiquitous and involved in every aspect of life, ranging from wearable devices to sensors monitoring industrial processes. The networking equipment connecting these devices will need to seamlessly communicate with several different software platforms, with software continuously upgraded. In addition, these devices will be exposed to unprecedented, highly varying external stimuli: harsh thermal fluctuations, fluids, moisture, vibrations and shock. Networking products have traditionally been protected in data centers, where temperature, humidity and vibrations are well controlled. Traditional networking devices are not designed for use in the unpredictable, varying environments that devices supporting the IoT ecosystem will endure. A different methodology is needed to design for the reliability of these networking products for the IoT ecosystem. Traditional Telecom industry requirements for hardware reliability are “5 Nines”: 99.999%, which translates to 5 minutes and 15 seconds of downtime in a year. In this paper, we will present a methodology for estimating hardware reliability given uncertain use conditions, to derive probabilistic estimates for overall system reliability. The methodology is applied to illustrative case studies with different use conditions and target life requirements. Numerical Finite Element Models (FEM) are combined with statistical techniques and Monte Carlo simulations to develop a reliability prediction approach. The models developed can then be used to perform sensitivity studies to determine which factors are most influential in degrading reliability, and rank ordering them. This in turn can help identify the specific issue (hardware component or software issue) to focus on, to meet target lifetime goals. The models can also be used to d- rive the optimal design window, which engineers can then use to design their IoT products while ensuring their reliability targets are met. Finally, an overall framework will be presented, on how this methodology can be extended to any electronic system in the IoT ecosystem and beyond.