most citedEdge Intelligence with Spiking Neural Networks

1 citations · 2 across the 6 of their papers we have counts for

collaborators

6 papers

cs.DC2026

ElastiCo: Elastic Configuration and Interference-Aware Orchestration for GPU Clusters

Jinghao Wang, Yihang Zhou, Xiaoyang Sun +5

Modern GPU clusters must simultaneously serve deep learning training and offline large language model inference workloads, yet existing schedulers treat these as isolated resource…

cs.DC2026

SpecBox: Speculative Sandbox Scheduling for Efficient LLM Agent Serving

Yihui Zhang, Tianyu Wo, Jinghao Wang +7

As LLM agents increasingly rely on the Model Context Protocol (MCP) to invoke isolated external sandboxes, disaggregated sandbox deployment introduces a fundamental tension between…

cs.AI2026

Agentic Service-Oriented Computing: A Manifesto for the Next Frontier of Service-Oriented Computing

Amin Beheshti, Rong N. Chang, Boualem Benatallah +7

The rapid emergence of LLM-powered autonomous and semi-autonomous agents is reshaping software systems from static, request-response components into goal-directed, adaptive, and to…

cs.CE2026

Industrial Data-Service-Knowledge Governance: Toward Integrated and Trusted Intelligence

Hailiang Zhao, Ziqi Wang, Daojiang Hu +9

The convergence of artificial intelligence, cyber-physical systems, and distributed networking has accelerated the evolution of industrial intelligence across edge, cloud, and cros…

cs.LG2025★ 1 cited

Reliable Microservice Tail Latency Prediction via Decoupled Dual-Stream Learning and Gradient Modulation

Wenzhuo Qian, Hailiang Zhao, Jiayi Chen +7

Microservice architectures enable scalable cloud-native applications; however, the distributed nature of these systems complicates the maintenance of strict Service Level Objective…

cs.DC2025★ 1 cited

Edge Intelligence with Spiking Neural Networks

Shuiguang Deng, Di Yu, Changze Lv +10

The convergence of artificial intelligence and edge computing has spurred growing interest in enabling intelligent services directly on resource-constrained devices. While traditio…