An OMA Lightweight M2M-compliant MEC Framework to Track Multi-modal Commuters for MaaS Applications

Abstract

Mobility as a Service (MaaS) implies the integration of different transport services in a unique platform accessible by commuters on demand. Collection and processing of data concerning the mobility of customers is crucial to calculate trips options satisfying users’ needs and preferences. In this paper, we propose to exploit Multi-access Edge Computing (MEC) facilities to more efficiently deploy MaaS solutions. Specifically, we design a MEC-based MaaS framework that is fully compliant with the Open Mobile Alliance (OMA) Lightweight Machine-to-Machine (LwM2M) protocol. The OMA LwM2M server hosted in the MEC platform continuously collects data from the commuters, and uses native MEC applications to provide value-added services. The OBSERVE extension of the Constrained Application Protocol (CoAP) is used to reduce energy consumption during data collection from the OMA LwM2M clients installed in the mobile user devices. Preliminary results are collected that show the performance of the proposed MaaS framework, integrated with a mobility generator tool (i.e., SUMO) that emulates the commuter paths.