This position paper presents ThothSP, a Semantic Programming framework with the aim of lowering the coding effort in building smart applications on the Device-Edge-Cloud continuum by leveraging semantic knowledge. It introduces a novel neural-symbolic stream fusion mechanism, which enables the specification of data fusion pipelines via declarative rules, with degrees of learnable probabilistic weights. Moreover, it includes an adaptive federator that allows the Thoth>runtime to be distributed across multiple compute nodes in a network, and to coordinate their resources to collaboratively process tasks by delegating partial workloads to their peers. To demonstrate ThothSP's capability, we report a case study on a distributed camera network to show ThothSP's behaviour against a traditional edge-cloud setup.

翻译：本文提出ThothSP语义编程框架，旨在通过语义知识降低在设备-边缘-云连续体上构建智能应用的编码工作量。该框架引入了一种新颖的神经-符号流融合机制，支持通过声明式规则指定数据融合流水线，并具有可学习的概率权重程度。此外，它还包含一个自适应联邦器，允许Thoth运行时分布部署在网络中的多个计算节点上，并通过将部分工作负载委托给对等节点来协调资源以协作处理任务。为展示ThothSP的能力，我们针对分布式摄像头网络开展案例研究，展示了ThothSP相比传统边缘-云设置的性能表现。