| Abstract | With the development of the Internet of Things (IoT), various large-scale real-time data processing applications for handling real-time sensor data are becoming one of the important applications in cloud computing. The academia, the industry, and even the government institutions have already begun to pay close attention to how to efficiently process large amounts of sensor data in real-time using cloud computing technology. Although cloud computing technology has attracted much attention with high-performance, there are strong needs for improving data processing efficiency of large-scale real-time data for IoT-based applications. In addition to this, currently the IoT paradigm is facing increasing difficulty to handle the data generated from IoT applications. As a result of this, it is challenging to ensure low latency and network bandwidth consumption, optimal utilization of computational recourses, scalability, security, and energy efficiency of IoT devices while moving all data to the cloud. Therefore, this centralized computing model is starting to shift to a decentralized model termed as edge computing, that allows data to be handled from the cloud to local devices such as smartphones, smart gateways or routers, local PCs or sensor nodes on a smaller scale in real-time. |
