硬件感知的流处理：综述

基于模式的事件处理器调度和缓冲区最小化

Schema-based Scheduling of Event Processors and Buffer Minimization for Queries on Structured Data Streams

我们介绍了一个扩展的XQuery语言，FluX，支持基于事件的查询处理和有意识的处理主内存缓冲区。这种语言的基于事件的查询可以以非常直接的方式在流XML数据上执行。然后，我们开发了一种算法，允许有效地重写Xcovery到基于事件的Flux语言。此算法使用来自DTD的顺序约束来调度事件处理程序，从而最小化计算查询所需的缓冲量。我们讨论了我们的框架内的查询优化和查询评估的各种技术方面。这是补充与我们的方法的实验评估。

CStream：多核边缘设备上的并行数据流压缩

CStream: Parallel Data Stream Compression on Multicore Edge Devices

本文提出CStream框架，通过软硬件协同设计在多核边缘设备上并行化数据流压缩，结合有损压缩、非对称多核与硬件感知并行策略，实现高压缩比、高吞吐、低延迟和低能耗。

PanJoin: A Partition-based Adaptive Stream Join

In stream processing, stream join is one of the critical sources of performance bottlenecks. The sliding-window-based stream join provides a precise result but consumes considerable computational resources. The current solutions lack support for the join predicates on large windows. These algorithms and their hardware accelerators are either limited to equi-join or use a nested loop join to process all the requests. In this paper, we present a new algorithm called PanJoin which has high throughput on large windows and supports both equi-join and non-equi-join. PanJoin implements three new data…

GALOIS：一种混合式且平台无关的流处理架构

GALOIS: A Hybrid and Platform-Agnostic Stream Processing Architecture

针对物联网场景下边缘数据流处理系统的硬件与平台异构性问题，提出基于WebAssembly的混合式平台无关架构GALOIS，结合P2P与主从模式通信，实验验证其在能耗和CPU占用上优于Docker方案。

Zero-Shot Cost Models for Distributed Stream Processing

This paper proposes a learned cost estimation model for Distributed Stream Processing Systems (DSPS) with an aim to provide accurate cost predictions of executing queries. A major premise of this work is that the proposed learned model can generalize to the dynamics of streaming workloads out-of-the-box. This means a model once trained can accurately predict performance metrics such as latency and throughput even if the characteristics of the data and workload or the deployment of operators to hardware changes at runtime. That way, the model can be used to solve tasks such as optimizing the pl…