Big-Sensing-Data Curation for the Cloud is Coming: A Promise of Scalable Cloud-Data-Center Mitigation for Next-Generation IoT and Wireless Sensor Networks

Abstract

Modern sensing devices play a pivotal role in achieving data acquisition, communication, and dissemination for the Internet of Things (IoT). Naturally, IoT applications and intelligent sensing systems supported by sensing devices, such as wireless sensor networks (WSNs), are closely coupled. Modern intelligent sensing systems generate huge volumes of sensing data, well beyond the processing capabilities of common techniques and tools. As a result, collecting, managing, and processing IoT big sensing data within an acceptable time duration is a new challenge for both research and industrial applications. The massive size, extreme complexity, and high speed of big sensing data bring new technical requirements including data collection, data storage, data organization, data analysis, and data publishing in real time when deploying real-world IoT applications. To better facilitate these IoT applications, the convergent research of WSNs, big data, the IoT, and cloud computing is a natural scientific development trend. In this article, we concentrate on big-sensing-data curation and preparation issues with cloud computing under the theme of the IoT. There are three especially critical issues that need to be addressed: scalable big-sensing-data cleaning, scalable big-sensing-data compression, and cloud-based data curation response for IoT device optimization. Viewed from the IoT side, all IoT sensing devices are integrated together in an adaptive solution and upload their data onto the cloud. The automatic responses from both the cloud and intelligent sensors will change the status or behavior of sensing devices and, therefore, the status of the IoT itself.