Title
Leveraging mobility and content caching for proactive load balancing in heterogeneous cellular networks
Abstract
AbstractAbstractEvolution of cellular networks into dynamic, dense, and heterogeneous networks have introduced new challenges for cell resource optimization, especially in the imbalanced traffic load regions. Numerous load balancing schemes have been proposed to tackle this issue; however, they operate in a reactive manner that confines their ability to meet the top‐notch quality of experience demands. To address this challenge, we propose a novel proactive load balancing scheme. Our framework learns users' mobility and demands statistics jointly to proactively cache future contents during their stay at lightly loaded cells, which results in quality of experience maximization and load minimization. System level simulations are performed and compared with the state‐of‐the‐art reactive schemes. View Figure A novel proactive load balancing framework is proposed, which leverages user mobility and content demand statistics jointly to maximize downlink throughput and minimize cell loads. This framework models user mobility patterns through Semi‐Markov renewal process and exploits content demand history for proactive content caching.
Year
DOI
Venue
2020
10.1002/ett.3739
Periodicals
Field
DocType
Volume
Load balancing (computing),Computer science,Computer network,Cellular network
Journal
31
Issue
ISSN
Citations 
2
2161-3915
1
PageRank 
References 
Authors
0.35
0
6
Name
Order
Citations
PageRank
Sanaullah Manzoor110.35
Suleman Mazhar210.35
Ahmad Asghar310.35
Adnan Noor Mian48512.39
Ali Imran538240.89
Jon Crowcroft6120851252.50