Data management systems will face several new challenges in supporting IoT applications
during the coming years. These challenges arise from managing large numbers of …

Abstract The Internet of Things (IoT) presents a novel computing architecture for data
management: a distributed, highly dynamic, and heterogeneous environment of massive …

A recent trend in stream processing is offloading the computation of decomposable
aggregation functions (DAF) from cloud nodes to geo-distributed fog/edge devices to …

ABSTRACT Stream Processing Engines (SPEs) execute long-running queries on
unbounded data streams. They mainly focus on achieving high throughput and low-latency …

In this work, we present COSTREAM, a novel learned cost model for Distributed Stream
Processing Systems that provides accurate predictions of the execution costs of a streaming …

The Internet of Things (IoT) is rapidly growing into a network of billions of interconnected
physical devices that constantly stream data. To enable data-driven IoT applications, data …

With the increasing prevalence of IoT environments, the demand for processing massive
distributed data streams has become a critical challenge. Data Stream Processing on the …

Mobile devices have become ubiquitous; smartphones, tablets and wearables are essential
commodities for many people. The ubiquity of mobile devices combined with their ever …

Soon, more data will be produced outside the cloud than inside. This constantly increasing
amount of data requires new systems that can holistically optimize the processing for so …

ABSTRACT Complex Event Processing (CEP) enables autonomous and real-time decision
making in data management systems. Today, applications leverage CEP only in cloud …