ASAA: Multihop and Multiuser Channel Hopping Protocols for Cognitive-Radio-Enabled Internet of Things

The devices of the Internet of Things (IoT) are integrated and interconnected by using the traditional wireless communication technology. The unavailability of spectrum sharing occurs in traditional wireless communication due to the presence of a massive number of IoT devices. Thus, the cognitive radio network (CRN) is introduced as a promising technology to utilize the spectrum efficiently. Channel hopping sequence (CHS) is used to establish communication among CRN users. However, the majority of CHS mechanisms only focus on multiuser single-hop scenarios, which can lead to bottleneck and throughput degradation problems. It is also found that few existing CHS mechanisms still have a low percentage of rendezvous that can cause difficulties for the secondary users (SUs) to communicate. Thus, it is a challenge to design efficient CHS for establishing fast communication among SUs under multiuser, multihop scenarios, and asymmetric asynchronous environments. In this article, asymmetric synchronous and asymmetric asynchronous (ASAA) channel hopping (CH) algorithms are designed for the multiuser CRN-enabled IoT devices to share the unused spectrum in the multihop scenario. The multiuser asymmetric synchronous (MUAS) and multiuser asymmetric asynchronous (MUAA) protocols are designed in the proposed ASAA CH mechanism. The simulation results show that the proposed ASAA CHS algorithms outperform the existing CHS mechanisms in terms of throughput, channel loading (CL), channel utilization (CU), maximum time to rendezvous (MTTR), average time to rendezvous (ATTR), and maximum inter rendezvous interval (MIRI).

I. Introduction

Internet of Things (IoT) generally refers to the devices connected through the Internet and have communication and computational abilities to generate and exchange data among applications. These IoT devices are heterogeneous [1] and interconnected, and, therefore, can be integrated and implemented in various sectors, such as smart healthcare [2], smart transportation [3], smart industry [4], etc. For instance, in smart transportation, several traffic sensors are installed and connected wirelessly to control and monitor the traffic. CISCO [5] has predicted that data generated by IoT devices can be increased exponentially up to 49 Exabytes by 2021. With the rapid growth of IoT users and devices, the high demand for spectrum availability is inevitable. Conversely, spectrum resources are limited and precious as natural resources. Moreover, if no action is taken to utilize the wireless spectrum wisely, the spectrum scarcity problem [6] will be a global issue.