EasiDARM: Distributed Based Adaptive Register Method for Internet of Things

With the perfecting and practicability of the access protocols of the Internet of things (IoT), it is becoming a mainstream architecture to connect devices to cloud platforms for support of real-time access. Considering the dynamic nature of IoT devices and networks, we must make the devices register on the platforms periodically to ensure real-time access between the devices and the platforms. However, existing register methods cost much time and consume a lot of resources on devices, Internet and platforms; and what’s more, the platforms will be overload when many devices or networks are dynamic. In this paper, we present a distributed based adaptive register method (EasiDARM) to reduce the costs of resources and time. By using multiple devices to complete the measurement of network address translation (NAT) timeout which is complex and time-consuming, and sharing the result of measurement among the devices, EasiDARM accelerates the processes of the measurement and self-adaption. The process of measurement is divided into fast update (FU) and fast converge (FC) stage, EasiDARM assigns and probes the candidate intervals with exponential growth during the FU stage to extend the register interval rapidly, and with linear growth during the FC stage to converge the measurement quickly. Through experiments show that compared with the traditional adaptive register method, EasiDARM can reduce 46% of time, 46% of consumption on devices and 53% of consumption on Internet and platforms in the process of measurement, and cut 36% of instantaneous consumption on platforms.