SimDC: A High-Fidelity Device Simulation Platform for Device-Cloud Collaborative Computing

TL;DR

SimDC tackles the gap between HPC-based device emulation and real-world edge devices in device-cloud collaboration by integrating a hybrid heterogeneous resource framework with a programmable DeviceFlow traffic controller. It enables large-scale functional testing with physical devices while collecting authentic performance metrics, and it introduces an optimization-based allocation strategy to minimize task duration. The platform demonstrates high scalability, maintains accuracy under hybrid configurations, and faithfully reproduces real-world device traffic patterns, making it practical for evaluating edge-side algorithms and cloud-side services. Overall, SimDC offers a cost-effective, realistic, end-to-end simulation environment that bridges the gap between theoretical device-cloud methods and real deployment scenarios.

Abstract

The advent of edge intelligence and escalating concerns for data privacy protection have sparked a surge of interest in device-cloud collaborative computing. Large-scale device deployments to validate prototype solutions are often prohibitively expensive and practically challenging, resulting in a pronounced demand for simulation tools that can emulate realworld scenarios. However, existing simulators predominantly rely solely on high-performance servers to emulate edge computing devices, overlooking (1) the discrepancies between virtual computing units and actual heterogeneous computing devices and (2) the simulation of device behaviors in real-world environments. In this paper, we propose a high-fidelity device simulation platform, called SimDC, which uses a hybrid heterogeneous resource and integrates high-performance servers and physical mobile phones. Utilizing this platform, developers can simulate numerous devices for functional testing cost-effectively and capture precise operational responses from varied real devices. To simulate real behaviors of heterogeneous devices, we offer a configurable device behavior traffic controller that dispatches results on devices to the cloud using a user-defined operation strategy. Comprehensive experiments on the public dataset show the effectiveness of our simulation platform and its great potential for application. The code is available at https://github.com/opas-lab/olearning-sim.

Figures (11)

• Figure 1: Architectural schematic of the SimDC platform.
• Figure 2: PhoneMgr manages the physical devices cluster and performance measurement.
• Figure 3: Real-world applications and DeviceFlow in device-cloud collaboration.
• Figure 4: The framework of DeviceFlow.
• Figure 5: Measurement of CPU and memory usage during the first three rounds.