scholarly journals Slice Function Placement Impact on the Performance of URLLC with Multi-Connectivity

Computers ◽  
2021 ◽  
Vol 10 (5) ◽  
pp. 67
Author(s):  
Abdellatif Chagdali ◽  
Salah Eddine Elayoubi ◽  
Antonia Maria Masucci

Network slicing has emerged as a promising technical solution to ensure the coexistence of various 5G services. While the 5G architecture evolution for supporting slicing has been exhaustively studied, the architectural option impacts on RAN resource allocation efficiency remain unclear. This article fills a gap in this area by evaluating the impact of architecture choices on the quality of service of different services in the new 5G ecosystem, focusing on ultra-reliable low-latency communication applications. We propose architectural options based on the placement of the entities responsible for implementing these functions. We then assess their impact on the radio resource allocation flexibility when slices span two radio access technologies with redundant coverage. Our numerical experiments showed that the slice management function placement plays a pivotal role in choosing an adequate radio resource allocation scheme for URLLC slices.

2018 ◽  
Vol 12 (5) ◽  
pp. 1277-1288 ◽  
Author(s):  
Shiyuan Tong ◽  
Yun Liu ◽  
Hsin-Hung Cho ◽  
Hua-Pei Chiang ◽  
Zhenjiang Zhang

PLoS ONE ◽  
2019 ◽  
Vol 14 (1) ◽  
pp. e0210310 ◽  
Author(s):  
Maharazu Mamman ◽  
Zurina Mohd Hanapi ◽  
Azizol Abdullah ◽  
Abdullah Muhammed

2021 ◽  
Author(s):  
Lilatul Ferdouse

Cellular based M2M systems generate massive number of access requests which create congestion in the cellular network. The contention-based random access procedures are designed for cellular networks which cannot accommodate a large number of M2M traffic. Moreover, M2M systems share same radio resources with cellular users. Resource allocation problem becomes a challenging issue in cellular M2M systems. In this thesis, we address these two problems by analyzing a contention-based slotted Aloha random access procedure for M2M networks using different performance metrics. The impact of massive M2M traffic over cellular traffic is studied based on different arrival rate, random access opportunity and throughput. An analytical model of selecting a base station (eNB) along with load balancing is developed. Finally, two methods have been presented and evaluated with M2M traffic. First one is dynamic access class barring method which controls RAN level congestion by selecting an appropriate eNB and applying load balancing method. Second one is relay-assisted radio resource allocation method which maximizes the sum throughput of the system by utilizing the available radio resource blocks and relay nodes to the MTC systems. Numerical results show that frame transmission rate influences the selection probability of the base stations. Moreover, the dynamic access class barring parameter along with frame transmission rate improve the overall throughput and access success probability among base stations as well as avoid overload situation in a particular base station.


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