Paper ID: 2202.13958

CQELS 2.0: Towards A Unified Framework for Semantic Stream Fusion

Anh Le-Tuan, Manh Nguyen-Duc, Chien-Quang Le, Trung-Kien Tran, Manfred Hauswirth, Thomas Eiter, Danh Le-Phuoc

We present CQELS 2.0, the second version of Continuous Query Evaluation over Linked Streams. CQELS 2.0 is a platform-agnostic federated execution framework towards semantic stream fusion. In this version, we introduce a novel neural-symbolic stream reasoning component that enables specifying deep neural network (DNN) based data fusion pipelines via logic rules with learnable probabilistic degrees as weights. As a platform-agnostic framework, CQELS 2.0 can be implemented for devices with different hardware architectures (from embedded devices to cloud infrastructures). Moreover, this version also includes an adaptive federator that allows CQELS instances on different nodes in a network to coordinate their resources to distribute processing pipelines by delegating partial workloads to their peers via subscribing continuous queries

Submitted: Feb 15, 2022