IoT Data Stream Handling, Analysis, Communication and Security Issues: A Systematic Survey

Massive data management or data stream handling has become a prominent study topic as a result of recent breakthroughs in the Internet of Things (IoT). With the developments in big data technologies and their applications in the IoT realm, the analyzing, processing,, and handling streams of data and information are attaining the vast attention of researchers. In IoT, continuous information generation, handling and secure communication are achieved through innumerable devices. This information is enormous and time-varying. In all IoT applications processing, analyzing, and handling such information are extremely critical, as the ceaseless flow of information and time-sensitive decisions may make it inefficacious to process after storage. Therefore, processing such massive or streams of information must be executed in real-time. A better understanding of the stream data handling, analysis and communication aspect can help in effective data management. This review work provides the vitality of secure data stream handling and analysis in IoT applications. It explains the critical features and requirements of IoT data for the analysis and security concerns in industrial applications like smart city, smart agriculture and smart transportation system. It explores various studies emphasizing massive data management and the complexities involved with it. This article further investigates the different models and techniques utilized for handling IoT stream data in existing research works and enumerates their merits in stream data performance management. The review work also describes the technical challenges and research gap existing in-stream data handling and crucial further developments needed in this arena for effective management of IoT stream data.