Joint Traffic Offloading and Aging Control in 5G IoT Networks

TL;DR

This paper proposes a pricing mechanism based on Age of Information to optimize traffic offloading and resource allocation in 5G IoT networks, reducing costs while maintaining QoS.

Contribution

It introduces an AoI-based pricing scheme with a two-stage decision process for traffic offloading and resource slicing in 5G IoT networks.

Findings

Cost reductions achieved through the proposed scheme.

Traffic smoothing by shifting load to less expensive locations.

Trade-off between slicing costs and AoI demonstrated in simulations.

Abstract

The widespread adoption of 5G cellular technology will evolve as one of the major drivers for the growth of IoT-based applications. In this paper, we consider a Service Provider (SP) that launches a smart city service based on IoT data readings: in order to serve IoT data collected across different locations, the SP dynamically negotiates and rescales bandwidth and service functions. 5G network slicing functions are key to lease an appropriate amount of resources over heterogeneous access technologies and different site types. Also, different infrastructure providers will charge slicing service depending on specific access technology supported across sites and IoT data collection patterns. We introduce a pricing mechanism based on Age of Information (AoI) to reduce the cost of SPs. It provides incentives for devices to smooth traffic by shifting part of the traffic load from highly congested and more expensive locations to lesser charged ones, while meeting QoS requirements of the IoT service. The proposed optimal pricing scheme comprises a two-stage decision process, where the SP determines the pricing of each location and devices schedule uploads of collected data based on the optimal uploading policy. Simulations show that the SP attains consistent cost reductions tuning the trade-off between slicing costs and the AoI of uploaded IoT data.