Interplay between Big Spectrum Data and Mobile Internet of Things: Current solutions and future challenges

Abstract

In the current epoch of technology trends, Internet of Things (IoT) is an emerging technology that illustrates the significant transition for enterprises to extend their businesses. Such technologies not only spark the growth in business, but also add values to our daily lives in many aspects such as livelihood, health, work, and entertainment. Nowadays, with the emergence of wireless infrastructure and the advancements in cellular technologies, Mobile IoT (MIoT) has gained considerable amount of attention. Intelligent decisions are made based on the information retrieved from raw data through sensors, machines, and other devices. These decisions are widely utilized in many fields of life such as smart health-care, smart transportation, and smart energy etc. Usually such smart systems are realized through MIoT infrastructure. The devices participating in MIoT are heterogeneous and produce huge amount of data, and contribute to cross-platform solutions covering plethora of applications. In the wake of such volume and variety, the data produced because of spectrum analysis for the entire IoT network is also huge and thus referred to as Big Spectrum Data (BSD). To this end, BSD is a way forward to get deep insights to the big data generated by MIoT. In this paper, we conduct a systematic review of the MIoT network focusing on the characteristics of mobility in MIoT from BSD perspective. More precisely, we focus on the relationship between MIoT and BSD, and discuss in detail, the BSD analytics to harness its benefits in MIoT. Furthermore, we investigate and outline the current solutions of BSD in MIoT. Additionally, through this work, we identify the existing challenges faced in dealing with BSD in MIoT and future research directions.