QoS-Based Data Aggregation and Resource Allocation Algorithm for Machine Type Communication Devices in Next-Generation Networks

IEEE Access

Nasser Mohammed Ahmed¹  Nasser-Eddine Rikli¹ 

[1]Department of Computer Engineering, College of Computer Science and Information System (CCIS), King Saud University, Riyadh, Saudi Arabia

关键词: 5G networks;    data aggregation;    Internet of Things (IoT);    MTC;    resource allocation;    quality of service (QoS);   

DOI  :  10.1109/ACCESS.2021.3107624

来源: DOAJ

【 摘 要 】

Machine Type Communication (MTC) becomes one of enablers of the internet of things, it faces many challenges in its integration with human-to-human (H2H) communication methods. To this aim, the Long Term Evolution (LTE) needs some adaptation in the scheduling algorithms that assign resources efficiently to both MTC devices (MTCDs) and H2H users. The minimum amount of LTE resources that can be assigned to one user is much larger than the requirements of a single MTCD. In this paper, a QoS-enabled algorithm is proposed to aggregate MTCD traffic coming from many sources at the Relay Node (RN) that classifies and aggregates the MTCD traffic based on the source type and delay requirements. In this study, three types of MTCD and one H2H sources will be considered. Each type of MTCD traffic will be grouped into a separate queue, and will be served with the appropriate priority. Resources are then assigned to the aggregated MTC traffic instead of an individual assignment for each MTCD, while the H2H users will be directly connected to the LTE. Two schemes of resource partitioning and sharing between the MTCDs and the H2H users will be considered: one proportional and the other moving-boundary. Simulation models will be built to evaluate the proposed algorithms. While the obtained results for the first scheme showed a clear improvement in LTE resource utilization for the MTCDs, a negative effect was noticed in the performance of the H2H users. The second scheme achieved a positive improvement for both MTCDs and H2H users.

【 授权许可】

Unknown