TY - JOUR
T1 - HSDRAN
T2 - Hierarchical software-defined radio access network for distributed optimization
AU - Yu, Ruozhou
AU - Xue, Guoliang
AU - Bennis, Mehdi
AU - Chen, Xianfu
AU - Han, Zhu
N1 - Funding Information:
Manuscript received September 29, 2016; revised January 31, 2017; accepted March 12, 2017. Date of publication April 6, 2017; date of current version September 17, 2018. This work was supported in part by the NSF Grants 1646607, 1547201, 1456921, 1443917, 1405121, 1457262, and 1461886, and in part by the TEKES Grants 2364/31/2014 and 2368/31/2014. The review of this paper was coordinated by Prof. H. Nishiyama. (Corresponding author: Guoliang Xue.) R. Yu and G. Xue are with Arizona State University, Tempe, AZ 85287 USA (e-mail: ruozhouy@asu.edu; xue@asu.edu).
Publisher Copyright:
© 1967-2012 IEEE.
Copyright:
Copyright 2018 Elsevier B.V., All rights reserved.
PY - 2018/9/1
Y1 - 2018/9/1
N2 - The drastic growth of mobile traffic greatly challenges the capacity of mobile infrastructures. Dense deployment of low-power small cells helps alleviate the congestion in the radio access network, yet it also introduces large complexity for network management. Software-defined radio access network has been proposed to tackle the added complexity. However, existing software-defined solutions rely on a fully centralized control plane to make decisions for the whole network, which greatly limits the scalability and responsiveness of the control plane. In this paper, we propose a hierarchical software-defined radio access network architecture. The proposed architecture leverages the hierarchical structure of radio access networks, deploying additional local controllers near the network edge. Utilizing the intrinsic locality in radio access networks, it offloads control tasks from the central controller to local controllers with limited overhead introduced. Under the architecture, a distributed optimization framework is proposed, and a typical optimization problem is studied to illustrate the effectiveness of the proposed architecture and framework. Both analysis and experiments validate that the proposed architecture and framework can improve the network objective during the optimization, meanwhile balancing load and improving scalability and responsiveness.
AB - The drastic growth of mobile traffic greatly challenges the capacity of mobile infrastructures. Dense deployment of low-power small cells helps alleviate the congestion in the radio access network, yet it also introduces large complexity for network management. Software-defined radio access network has been proposed to tackle the added complexity. However, existing software-defined solutions rely on a fully centralized control plane to make decisions for the whole network, which greatly limits the scalability and responsiveness of the control plane. In this paper, we propose a hierarchical software-defined radio access network architecture. The proposed architecture leverages the hierarchical structure of radio access networks, deploying additional local controllers near the network edge. Utilizing the intrinsic locality in radio access networks, it offloads control tasks from the central controller to local controllers with limited overhead introduced. Under the architecture, a distributed optimization framework is proposed, and a typical optimization problem is studied to illustrate the effectiveness of the proposed architecture and framework. Both analysis and experiments validate that the proposed architecture and framework can improve the network objective during the optimization, meanwhile balancing load and improving scalability and responsiveness.
KW - Distributed optimization
KW - mobile 5G HetNets
KW - radio access network
KW - software-defined networking
UR - http://www.scopus.com/inward/record.url?scp=85053781369&partnerID=8YFLogxK
U2 - 10.1109/TVT.2017.2691735
DO - 10.1109/TVT.2017.2691735
M3 - Article
AN - SCOPUS:85053781369
VL - 67
SP - 8623
EP - 8636
JO - IEEE Transactions on Vehicular Technology
JF - IEEE Transactions on Vehicular Technology
SN - 0018-9545
IS - 9
M1 - 7893766
ER -