Machine-to-Machine (M2M) Communications in Virtualized Cellular Networks with MEC

TL;DR

This paper explores integrating mobile edge computing and software-defined networking into virtualized cellular networks to enhance M2M communications, reduce energy use, and optimize resource allocation in IoT environments.

Contribution

It introduces a novel framework combining MEC, SDN, and virtualization for M2M communications, with a POMDP-based access scheme to minimize system costs.

Findings

Significant performance improvements over existing schemes.

Effective energy and time optimization in M2M communications.

Enhanced network flexibility and resource management.

Abstract

As an important part of the Internet-of-Things (IoT), machine-to-machine (M2M) communications have attracted great attention. In this paper, we introduce mobile edge computing (MEC) into virtualized cellular networks with M2M communications, to decrease the energy consumption and optimize the computing resource allocation as well as improve computing capability. Moreover, based on different functions and quality of service (QoS) requirements, the physical network can be virtualized into several virtual networks, and then each MTCD selects the corresponding virtual network to access. Meanwhile, the random access process of MTCDs is formulated as a partially observable Markov decision process (POMDP) to minimize the system cost, which consists of both the energy consumption and execution time of computing tasks. Furthermore, to facilitate the network architecture integration, software-defined networking (SDN) is introduced to deal with the diverse protocols and standards in the networks. Extensive simulation results with different system parameters reveal that the proposed scheme could significantly improve the system performance compared to the existing schemes.