Data stream compression attracts much attention recently due to the rise of IoT applications.
Thanks to the balanced computational power and energy consumption, asymmetric …

In the burgeoning realm of Internet of Things (IoT) applications on edge devices, data stream
compression has become increasingly pertinent. The integration of added compression …

This work is the first systematic investigation of stream processing with data compression:
we have not only identified a set of factors that influence the benefits and overheads of …

Stream processing prevails and SQL query on streams has become one of the most popular
application scenarios. For example, in 2021, the global number of active IoT endpoints …

Scientific applications, such as those simulating earthquakes, the origins of universe, etc.,
often produce massive amounts of data as high-performance computing (HPC) systems are …

Compression is essential to high bandwidth applications such as scientific simulations and
sensing applications to reduce resource burden such as storage, network transmission, and …

Data compression plays an important role in the era of big data; however, such compression
is typically one of the bottlenecks of a massive data processing system due to intensive …

DNA sequencing has moved into the realm of Big Data due to the rapid development of high-
throughput, low cost Next-Generation Sequencing (NGS) technologies. Sequential data …

Lightweight Temporal Compression (LTC) is among the lossy stream compression methods
that provide the highest compression rate for the lowest CPU and memory consumption. As …

Graphics Processing Unit (GPU) performance has relied heavily on our ability to scale of
number of transistors on chip, in order to satisfy the ever-increasing demands for more …