Fog Computing has emerged as a pivotal technology for enabling low-latency, context-
aware, and efficient computing at the edge of the network. Effective task scheduling plays a …

Multi-edge cooperative computing that combines constrained resources of multiple edges
into a powerful resource pool has the potential to deliver great benefits, such as a …

Deep learning (DL) has become a dominating type of workloads on AI computing platforms.
The performance of such platforms highly depends on how distributed DL jobs are …

Due to the rapid expansion of heterogeneous mobile networks, there has been a significant
increase in the need for a network, processing, and caching resources. A dynamic vehicular …

We present a framework for achieving end-to-end management objectives for multiple
services that concurrently execute on a service mesh. We apply reinforcement learning (RL) …

算力网络需要在满足用户业务需求的基础上最大化系统性能指标, 现有方法主要通过多目标加权
进行转换和求解, 存在超参数难以确定, 跨场景适用性差等问题. 在分析算网目标特性的基础上 …

The Industrial Internet of Things (IIoT) generally uses cloud computing mode to process
tasks. However, in cases of excessive task volume, a high workload will lead to significant …

Complex equipment disassembly tasks often require a group of people to complete, and the
same time satisfying various resource constraints. This paper proposes an improved elite …

Container technology has been widely used in industrial development, including system
deployment and program management, and has achieved very good results. However, in …

In the era of global services, low-latency analytics on large-volume geo-distributed data has
been a regular demand for application decision-making. Serverless computing facilitates …