Data stream processing (DSP) has emerged over the years as the reference paradigm for
the analysis of continuous and fast information flows, which often have to be processed with …

Event processing (EP) is a data processing technology that conducts online processing of
event information. In this survey, we summarize the latest cutting-edge work done on EP …

随着云计算在学术界和工业界的兴起, 云计算也不可避免的带来了一些安全问题.
本文对云计算的安全需求进行了总结, 指出云计算不仅在机密性, 数据完整性 …

Stream processing is an emerging paradigm to handle data streams upon arrival, powering
latency-critical application such as fraud detection, algorithmic trading, and health …

The rise of streaming big data has revolutionized the domain of real-time analytics, enabling
organizations to process and analyze data as it is generated (Sun et al., 2020). Unlike …

Cloud data centers are generally composed of heterogeneous commodity servers hosting
multiple virtual machines (VMs) with potentially different specifications and fluctuating …

Resource provisioning in multi-tenant stream processing systems faces the dual challenges
of keeping resource utilization high (without over-provisioning), and ensuring performance …

In this tutorial we present the results of recent research about the cloud enablement of data
streaming systems. We illustrate, based on both industrial as well as academic prototypes …

In the era of data explosion, high volume of various data is generated rapidly at each
moment of time; and if not processed, the profits of their latent information would be missed …

Stream computing, also known as data stream processing, has emerged as a new
processing paradigm that processes incoming data streams from tremendous numbers of …