On the Tradeoff between Performance and Programmability for Software Defined WiFi Networks

Zahid, Tausif; Hei, Xiaojun; Cheng, Wenqing; Ahmad, Ayyaz; Pasha, Maruf

doi:10.1155/2018/1083575

Cited by 17 publications

(13 citation statements)

References 32 publications

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“…The role of an OpenFlow protocol between the controller and the APs is neglected. A testbed is designed to study the trade-off between programmability and performance in SD-WiFi [50]. Light virtual access points (LVAPs) are created to shift the load from the overloaded APs to the underloaded APs.…”

Section: Load Balancing In Sd-wi-fimentioning

confidence: 99%

Towards QoS-Aware Load Balancing for High Density Software Defined Wi-Fi Networks

et al. 2020

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High density Wi-Fi networks require load balancing in order to ensure quality of service (QoS). In the traditional Wi-Fi networks, the wireless stations learn the access points (APs) load and make the association decisions themselves leading to uneven load distribution among the APs. The new paradigm, software defined networking (SDN), has a centralized architecture, which allows to manage, measure and control high density Wi-Fi networks easily. In this paper we propose a QoS-aware load balancing strategy (QALB) for software defined Wi-Fi networks (SD-Wi-Fi), as a solution to address the problem of Wi-Fi congestion among the OpenFlow enabled APs (OAPs). The SDN controller selects a load level up to which the association decisions are made by the OAPs without consulting the controller. The wireless stations from an overloaded OAP are handed to an underloaded OAP by considering multi-metrics such as the packet loss rate, received signal strength indicator (RSSI) and throughput. An emulation platform and a large-scalelow-cost testbed with the same settings are constructed to evaluate the performance of our load balancing strategy. The results show that in comparison to four non-static schemes such as, channel measurement based access selection scheme (CMAS), (DL-SINR) downlink-signal to interference plus noise ratio AP selection scheme (DASA), mean probe delay scheme (MPD) and RSSI scheme, the proposed QALB, optimizes the throughput up to 16%, reduces the average frame delay up to 19%, minimizes the number of re-transmissions by 49%, reduces the number of handoffs by 15%, improves the degree of load balancing by 22% and minimizes the re-association times by 38%, in high density SD-Wi-Fi. INDEX TERMS Emulation, high density, load balancing, QoS, Wi-Fi, SDN, testbed.

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Section: Load Balancing In Sd-wi-fimentioning

confidence: 99%

Towards QoS-Aware Load Balancing for High Density Software Defined Wi-Fi Networks

et al. 2020

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“…To solve the above problems, many researchers have devoted themselves to researching SDN-based WLAN architecture and terminal handover methods [15][16][17][18][19][20][21][22][23][24][25][26][27][28][29]. Odin [15] enabled the seamless handover of terminals by performing virtual access point (VAP) migration.…”

Section: Related Workmentioning

confidence: 99%

“…Nahida et al [23] introduced a new SDN-based Wi-Fi architecture and proposed an AP load balance based handover algorithm. Zahid et al [24] studied software-defined Wi-Fi networks to understand the ability of SDWN to effectively hide the handover delay between AP of the adoption of the SDWN architecture of Wi-Fi networks. In [25], the authors presented an SDN approach to design and implement a rate/link adaptation (RA) framework of WLAN.…”

Section: Related Workmentioning

confidence: 99%

Terminal handover in software-defined WLANs

Chen

Duan

Zhang

2020

J Wireless Com Network

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With the development of wireless LAN (WLAN) technology, wireless access points (APs) are deployed increasingly more and the number of mobile terminals is increasing. It is normal for a mobile terminal to hand over its AP. The traditional terminal handover method cannot effectively control the handover delay and balance the network load due to the inherent drawbacks such as closed encapsulation and the lack of centralized control. In this paper, we introduce the innovative network architecture of software-defined networking (SDN), propose a software-defined WLAN architecture, and propose a seamless handover method and a load balancing handover method of the softwaredefined WLAN. Experimental results show that the proposed handover method effectively reduces the handover delay, balances the network load, and improves the quality of service (QoS) and resource utilization of the network.

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“…In order to obtain the classification prediction results, each view is propagated by linear domain propagation method. Use the co-training strategy to select unlabeled text between different views to update the classification calculator at any time, with a relatively high classification accuracy [22]. 3Traffic classification: traffic classification method is through the use of a small amount of tag data to support the clustering process to determine the mapping relationship between the cluster and traffic type, and ultimately to achieve the traffic classification of the application layer [23].…”

Section: Improved Semi-supervised Learning Algorithmmentioning

confidence: 99%

Research on semi-supervised multi-graph classification algorithm based on MR-MGSSL for sensor network

Yang

Jin

et al. 2020

J Wireless Com Network

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With the advent of the era of network information, the amount of data in network information is getting larger and larger, and the classification of data becomes particularly important. Current semi-supervised multi-map classification methods cannot quickly and accurately perform automatic classification and calculation of information. Therefore, this paper proposes an MR-MGSSL algorithm and applies it to the classification of semi-supervised multi-graph. By determining the basic idea and calculation framework of MR-MGSSL algorithm, the mining of optimal feature subsets in multi-graphs and the multi-graph vectorization performance time are taken as examples, and the proposed algorithm is compared with other semi-supervised multi-graph classification methods. The performance evaluation results show that compared with other classification calculation methods, MR-MGSSL algorithm has the advantages of low sensitivity to feature subgraph and short vectorization time. The method is used to extract and detect clouds in remote sensing images (GF-1 and GF-2).

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On the Tradeoff between Performance and Programmability for Software Defined WiFi Networks

Cited by 17 publications

References 32 publications

Towards QoS-Aware Load Balancing for High Density Software Defined Wi-Fi Networks

Towards QoS-Aware Load Balancing for High Density Software Defined Wi-Fi Networks

Terminal handover in software-defined WLANs

Research on semi-supervised multi-graph classification algorithm based on MR-MGSSL for sensor network

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