相关论文: RT-DAP: A Real-Time Data Analytics Platform for La…
The demand for stream processing is increasing at an unprecedented rate. Big data is no longer limited to processing of big volumes of data. In most real-world scenarios, the need for processing stream data as it comes can only meet the…
Big data trend has enforced the data-centric systems to have continuous fast data streams. In recent years, real-time analytics on stream data has formed into a new research field, which aims to answer queries about what-is-happening-now…
Distributed stream processing systems are widely deployed to process real-time data generated by various devices, such as sensors and software systems. A key challenge in the system is overloading, which leads to an unstable system status…
In industrial and IoT environments, massive amounts of real-time and historical process data are continuously generated and archived. With sensors and devices capturing every operational detail, the volume of time-series data has become a…
Datacenter capacity is growing exponentially to satisfy the increasing demand for emerging computationally-intensive applications, such as deep learning. This trend has led to concerns over datacenters' increasing energy consumption and…
The high-dimensionality and volume of large scale multistream data has inhibited significant research progress in developing an integrated monitoring and diagnostics (M&D) approach. This data, also categorized as big data, is becoming…
One of the purposes of Big Data systems is to support analysis of data gathered from heterogeneous data sources. Since data warehouses have been used for several decades to achieve the same goal, they could be leveraged also to provide…
The exponential growth in smart sensors and rapid progress in 5G networks is creating a world awash with data streams. However, a key barrier to building performant multi-sensor, distributed stream processing applications is high…
The digitization of traffic sensing infrastructure has significantly accumulated an extensive traffic data warehouse, which presents unprecedented challenges for transportation analytics. The complexities associated with querying…
Any industrial system goes along with objectives to be met (e.g. economic performance), disturbances to handle (e.g. market fluctuations, catalyst decay, unexpected variations in uncontrolled flow rates and compositions,...), and…
Modern manufacturers are currently undertaking the integration of novel digital technologies - such as 5G-based wireless networks, the Internet of Things (IoT), and cloud computing - to elevate their production process to a brand new level,…
The proliferation of IoT sensors and their deployment in various industries and applications has brought about numerous analysis opportunities in this Big Data era. However, drift of those sensor measurements poses major challenges to…
IoT-enabled devices continue to generate a massive amount of data. Transforming this continuously arriving raw data into timely insights is critical for many modern online services. For such settings, the traditional form of data analytics…
Radiotherapy (RT) planning is complex, subjective, and time-intensive. Advances with artificial intelligence (AI) promise to improve its precision and efficiency, but progress is often limited by the scarcity of large, standardized…
Interconnectivity of production machines is a key feature of the Industrial Internet of Things (IIoT). This feature allows for many advantages in producing. Configuration and maintenance gets easier, as access to the given production unit…
With the deepening of digital transformation, business process optimisation has become the key to improve the competitiveness of enterprises. This study constructs a business process optimisation model integrating artificial intelligence…
We present Pathway, a new unified data processing framework that can run workloads on both bounded and unbounded data streams. The framework was created with the original motivation of resolving challenges faced when analyzing and…
IoT devices and sensor networks present new opportunities for measuring, monitoring, and guiding scientific experiments. Sensors, cameras, and instruments can be combined to provide previously unachievable insights into the state of ongoing…
Advancements in scientific instrument sensors and connected devices provide unprecedented insight into ongoing experiments and present new opportunities for control, optimization, and steering. However, the diversity of sensors and…
Data analysis and monitoring of road networks in terms of reliability and performance are valuable but hard to achieve, especially when the analytical information has to be available to decision makers on time. The gathering and analysis of…