Transactional stream processing engines (TSPEs) differ significantly in their designs, but all
rely on non-adaptive scheduling strategies for processing concurrent state transactions …

Large Language Models (LLMs) have demonstrated extraordinary performance across a
broad array of applications, from traditional language processing tasks to interpreting …

In a big data stream computing environment, the arrival rate of data streams usually
fluctuates over time, posing a great challenge to the elasticity of system. The performance of …

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 …

Transactional Stream Processing Engines (TSPEs) form the backbone of modern stream
applications handling shared mutable states. Yet, the full potential of these systems …

Data stream compression has attracted vast interest in emerging IoT (Internet of Things)
applications. However, adopting stream compression on IoT applications is non-trivial due to …

This thesis delves into the problem of compressing data generated by mobile networks,
which are formed by many antennas and IoT devices, that emit huge quantities of …

Transactional stream processing engines (TSPEs) have gained increasing attention due to
their capability of processing real-time stream applications with transactional semantics …