SMOTEC: An Edge Computing Testbed for Adaptive Smart Mobility Experimentation

TL;DR

SMOTEC is an open-source, modular testbed that enables adaptive experimentation with edge computing for smart mobility, supporting real-time service placement and load balancing across edge and cloud devices.

Contribution

It introduces SMOTEC, a comprehensive, end-to-end platform for prototyping and optimizing intelligent service placement in edge computing for smart mobility applications.

Findings

Demonstrated cost-effective, self-optimized traffic monitoring in Munich.

Validated the integration of Docker, ZeroMQ, EPOS, and Kubernetes in edge scenarios.

Showcased the flexibility of SMOTEC for urban mobility experimentation.

Abstract

Smart mobility becomes paramount for meeting net-zero targets. However, autonomous, self-driving and electric vehicles require more than ever before an efficient, resilient and trustworthy computational offloading backbone that expands throughout the edge-to-cloud continuum. Utilizing on-demand heterogeneous computational resources for smart mobility is challenging and often cost-ineffective. This paper introduces SMOTEC, a novel open-source testbed for adaptive smart mobility experimentation with edge computing. SMOTEC provides for the first time a modular end-to-end instrumentation for prototyping and optimizing placement of intelligence services on edge devices such as augmented reality and real-time traffic monitoring. SMOTEC supports a plug-and-play Docker container integration of the SUMO simulator for urban mobility, Raspberry Pi edge devices communicating via ZeroMQ and EPOS for an AI-based decentralized load balancing across edge-to-cloud. All components are orchestrated by the K3s lightweight Kubernetes. A proof-of-concept of self-optimized service placements for traffic monitoring from Munich demonstrates in practice the applicability and cost-effectiveness of SMOTEC.