Machine-to-Machine (M2M) Communications in Software-defined and Virtualized Cellular Networks

TL;DR

This paper presents a novel framework for M2M communications in virtualized, software-defined cellular networks, optimizing resource allocation and access processes through decision-theoretic methods and dynamic control.

Contribution

It introduces a new virtualization framework for M2M in SDN-enabled cellular networks, with a decision-theoretic approach for optimizing random access and dynamic resource management.

Findings

Enhanced random access efficiency in virtual M2M networks

Dynamic resource adjustment improves network performance

Simulation results validate the proposed framework's effectiveness

Abstract

Machine-to-machine (M2M) communications have attracted great attention from both academia and industry. In this paper, with recent advances in wireless network virtualization and software-defined networking (SDN), we propose a novel framework for M2M communications in software-defined cellular networks with wireless network virtualization. In the proposed framework, according to different functions and quality of service (QoS) requirements of machine-type communication devices (MTCDs), a hypervisor enables the virtualization of the physical M2M network, which is abstracted and sliced into multiple virtual M2M networks. In addition, we develop a decision-theoretic approach to optimize the random access process of M2M communications. Furthermore, we develop a feedback and control loop to dynamically adjust the number of resource blocks (RBs) that are used in the random access phase in a virtual M2M network by the SDN controller. Extensive simulation results with different system parameters are presented to show the performance of the proposed scheme.