Content-based dynamic superframe adaptation for Internet of Medical Things

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.

A Novel Synchronization Scheme Based on a Dynamic Superframe for an Industrial Internet of Things in Underground Mining

The Industrial Internet of Things (IIoT) has a wide range of applications, such as intelligent manufacturing, production process optimization, production equipment monitoring, etc. Due to the complex circumstance in underground mining, the performance of WSNs faces enormous challenges, such as data transmission delay, packet loss rate, and so on. The MAC (Media Access Control) protocol based on TDMA (Time Division Multiple Access) is an effective solution, but it needs to ensure the clock synchronization between the transmission nodes. As the key technology of IIoT, synchronization needs to consider the factors of tunnel structure, energy consumption, etc. Traditional synchronization methods, such as TPSN (Timing-sync Protocol for Sensor Networks), RBS (Reference Broadcast Synchronization), mainly focus on improving synchronization accuracy, ignoring the impact of the actual environment, cannot be directly applied to the IIoT in underground mining. In underground mining, there are two kinds of nodes: base-station node and sensor node, which have different topologies, so they constitute a hybrid topology. In this paper, according to hybrid topology of unground mining, a clock synchronization scheme based on a dynamic superframe is designed. In this scheme, the base-station and sensor have different synchronization methods, improving the TPSN and RBS algorithm, respectively, and adjusts the period of the superframe dynamically by estimating the clock offset. The synchronization scheme presented in this paper can reduce the network communication overhead and energy consumption, ensuring the synchronization accuracy. Based on theCC2530 (Asystem-on-chip solution for IEEE 802.15.4, Zigbee and RF4CE applications), the experiments are compared and analyzed, including synchronization accuracy, energy consumption, and robustness tests. Experimental results show that the synchronization accuracy of the proposed method is at least 11% higher than that of the existing methods, and the energy consumption can be reduced by approximately 13%. At the same time, the proposed method has better robustness.