Fairness and Load Balancing in SDWN Using Handoff-Delay-Based Association Control and Load Monitoring

Traffic loads in any 802.11 WLAN are distributed unevenly. This imbalance implies that some access points (APs) suffer from traffic congestions, while others are underutilized. The unbalanced load distributions cause annoying packet delay and throughput degradation which is unacceptable in current a...

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Main Authors: Shirong Lin, Nan Che, Fei Yu, Shouxu Jiang
Format: Article
Language:English
Published: IEEE 2019-01-01
Series:IEEE Access
Subjects:
Online Access:https://ieeexplore.ieee.org/document/8845571/
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author Shirong Lin
Nan Che
Fei Yu
Shouxu Jiang
author_facet Shirong Lin
Nan Che
Fei Yu
Shouxu Jiang
author_sort Shirong Lin
collection DOAJ
description Traffic loads in any 802.11 WLAN are distributed unevenly. This imbalance implies that some access points (APs) suffer from traffic congestions, while others are underutilized. The unbalanced load distributions cause annoying packet delay and throughput degradation which is unacceptable in current and future networks. A load-balancing algorithm should solve two challenges. The first is to accurately identify the APs' loads to timely find traffic imbalances. And the second is to associate clients with APs to achieve optimal proportional fairness intelligently. Network metrics such as throughput, delay, jitter, and client amount cannot be used individually to accurately identify APs' loads, because of the complexities of wireless communications. Which metrics to use and how to combine those network metrics to represent AP load are controversial. For intelligent association control, handoff delay (time to move a station from an AP to another) may last for 6 seconds. If the algorithm designers do not consider this delay in their optimization processes, unnecessary re-associations generated in their algorithm will offset the optimization profits. In this paper, we propose novel learning-based methods to monitor the network load to discover real-time load unbalances. We also model the load balancing problem as a utility maximization problem in which costs caused by handoff delay are considered. Then we utilize discretized linear programming theory and general assignment problem theory to solve it. We also compute the approximation ratio of our algorithm. We implement the whole load balancing system and evaluate the performances which show that our method outperforms a state-of-art algorithm in terms of throughput by up to12.7%, and it outperforms the received signal strength indicator (RSSI) based method by up to 28.13%.
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spelling doaj.art-2c4c38f6e4cb4fcc89ab4c75884c56532022-12-21T23:48:37ZengIEEEIEEE Access2169-35362019-01-01713693413695010.1109/ACCESS.2019.29427178845571Fairness and Load Balancing in SDWN Using Handoff-Delay-Based Association Control and Load MonitoringShirong Lin0https://orcid.org/0000-0002-4597-6600Nan Che1Fei Yu2Shouxu Jiang3School of Computer Science and Technology, Harbin Institute of Technology, Harbin, ChinaSchool of Software, Harbin University of Science and Technology, Harbin, ChinaSchool of Computer Science and Technology, Harbin Institute of Technology, Harbin, ChinaSchool of Computer Science and Technology, Harbin Institute of Technology, Harbin, ChinaTraffic loads in any 802.11 WLAN are distributed unevenly. This imbalance implies that some access points (APs) suffer from traffic congestions, while others are underutilized. The unbalanced load distributions cause annoying packet delay and throughput degradation which is unacceptable in current and future networks. A load-balancing algorithm should solve two challenges. The first is to accurately identify the APs' loads to timely find traffic imbalances. And the second is to associate clients with APs to achieve optimal proportional fairness intelligently. Network metrics such as throughput, delay, jitter, and client amount cannot be used individually to accurately identify APs' loads, because of the complexities of wireless communications. Which metrics to use and how to combine those network metrics to represent AP load are controversial. For intelligent association control, handoff delay (time to move a station from an AP to another) may last for 6 seconds. If the algorithm designers do not consider this delay in their optimization processes, unnecessary re-associations generated in their algorithm will offset the optimization profits. In this paper, we propose novel learning-based methods to monitor the network load to discover real-time load unbalances. We also model the load balancing problem as a utility maximization problem in which costs caused by handoff delay are considered. Then we utilize discretized linear programming theory and general assignment problem theory to solve it. We also compute the approximation ratio of our algorithm. We implement the whole load balancing system and evaluate the performances which show that our method outperforms a state-of-art algorithm in terms of throughput by up to12.7%, and it outperforms the received signal strength indicator (RSSI) based method by up to 28.13%.https://ieeexplore.ieee.org/document/8845571/Load balancingassociation controlload monitoringgeneral assignment problems
spellingShingle Shirong Lin
Nan Che
Fei Yu
Shouxu Jiang
Fairness and Load Balancing in SDWN Using Handoff-Delay-Based Association Control and Load Monitoring
IEEE Access
Load balancing
association control
load monitoring
general assignment problems
title Fairness and Load Balancing in SDWN Using Handoff-Delay-Based Association Control and Load Monitoring
title_full Fairness and Load Balancing in SDWN Using Handoff-Delay-Based Association Control and Load Monitoring
title_fullStr Fairness and Load Balancing in SDWN Using Handoff-Delay-Based Association Control and Load Monitoring
title_full_unstemmed Fairness and Load Balancing in SDWN Using Handoff-Delay-Based Association Control and Load Monitoring
title_short Fairness and Load Balancing in SDWN Using Handoff-Delay-Based Association Control and Load Monitoring
title_sort fairness and load balancing in sdwn using handoff delay based association control and load monitoring
topic Load balancing
association control
load monitoring
general assignment problems
url https://ieeexplore.ieee.org/document/8845571/
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