Content-based dynamic superframe adaptation for Internet of Medical Things

Abstract

IEEE 802.15.4 standard is widely used as a communication protocol by low-powered devices, including Internet of Medical Things–enabled technologies. These low-powered technologies have the ability to integrate several communicating and interacting devices for the purpose of wide range applications such as Smart homes and healthcare applications. However, the fixed superframe structure of IEEE 802.15.4 results in the unequal resource utilization among these low-powered heterogeneous Internet of Things devices. The low resource utilization degrades the network performance. In order to improve the network performance and optimum resource utilization, dynamic superframe approach is recommended. This article presents a content-based dynamic superframe adaptation algorithm for the low-powered Internet of Medical Things devices to address the resource utilization challenges. In the content-based dynamic superframe adaptation, the network coordinator dynamically adjusts the superframe along with the backoff exponent. It uses five Quality of Service metrics simultaneously: the application defined data traffic, receive ratio, Personal Area Network source nodes in numbers, number of collisions, and observed delay to achieve the optimal solution. A detailed analysis of the simulations shows that the content-based dynamic superframe adaptation is able to behave more intelligently to adjust superframe dynamic allocations according to the application’s content requirements. Moreover, it outperforms the other existing schemes in achieving the better resource utilization in IEEE 802.15.4 framework.