Title
When QoE Meets Learning: A Distributed Traffic-Processing Framework for Elastic Resource Provisioning in HetNets
Abstract
In heterogeneous networks (HetNets), dynamics of user requirements across the temporal domain lead to the order of magnitude traffic to be processed by macro cells. To achieve high quality of experience (QoE) for users and to perform resource allocation for cells intelligently, we first propose a distributed traffic-processing framework (SDVTS) for elastic resource partitioning, to accommodate dynamics from the user-centric and resource-oriented perspectives respectively. Assisted by a software defined infrastructure, SDVTS fulfills the responsibilities of the request-based and push-based services in an interactive loop. Second, we formulate a traffic-processing time model that computes the delay of handling traffic. The non-convex model is decomposed and a dual evolution algorithm is explored to approximate the optimal solution. Furthermore, we introduce a low-complexity reinforcement learning algorithm with the personalized QoE profiling. A distributed algorithm in coalition between user and cell is designed for seamless connection of an advanced reinforcement learning system (ARLS) components and engines embedded in SDVTS. Extensive simulation results with thorough analysis demonstrate that our framework SDVTS dominates in terms of QoE and cell′s system performance when compared with competing approaches.
Year
DOI
Venue
2020
10.1016/j.comnet.2019.106904
Computer Networks
Keywords
Field
DocType
Reinforcement learning,Resource provisioning,Software defined infrastructure,QoE,Traffic-processing framework
Computer science,Computer network,Provisioning,Distributed algorithm,Resource allocation,Quality of experience,Heterogeneous network,Software-defined data center,User requirements document,Distributed computing,Reinforcement learning
Journal
Volume
ISSN
Citations 
167
1389-1286
0
PageRank 
References 
Authors
0.34
0
5
Name
Order
Citations
PageRank
Li Yu120.71
Zongpeng Li22054153.21
Yucun Zhong300.34
Zhenzhou Ji410720.11
Jiangchuan Liu54340310.86