Surveying Best Suitable Scheduling Algorithm for Wimax- Wi-Fi Integrated Heterogeneous Network

Das, Poulomi; Sen, Siladitya; Banerjee, Arindam

doi:10.5121/csit.2013.3231

Cited by 2 publications

(3 citation statements)

References 17 publications

(26 reference statements)

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“…In (Gabale et al, 2013), on the other hand, an overview of scheduling algorithms in wireless mesh networks was given. In (Das et al, 2013), an overview of the most suitable scheduling algorithm for WIMAX-Wi-Fi was also given. Here in (Kathrine & Raj, 2012) an overview of packet scheduling in different networks has been done.…”

Section: Packet Schedulingmentioning

confidence: 99%

Developing A New Scheduling Algorithm for Wi-Fi 6 Technology Based on Machine Learning

MASRİ¹,

ERDAL²

2022

Uluslararası Muhendislik Arastirma Ve Gelistirme Dergisi

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Wireless mobile communications have experienced tremendous growth in the number of users, data rate requirements, and coverage in recent years. As the data rate and system throughput requirements increase, researchers and system designers need to develop efficient methods to meet these requirements with reasonable effort and cost. In this paper, we discuss an efficient approach to deal with diminishing the overhead of Downlink (DL) and feedback using Machine Learning (ML) for 802.11ax. In particular, the antennas that are related to the router were divided into two gatherings. We used good samples of Channel State Information (CSI) that were taken from an open-access dataset and used it to train our linear regression model. The first group of antennas was used as input to our model and the second group was used as the output of the model. In the online mode, we need to estimate only one group of antennas and for the second group, we can predict it using the trained linear regression model by using the estimated CSI group as input to the model. Therefore, the output of the model using as the CSI for the second group. In this way, we can reduce the overhead of the DL in the router as shown in the result table so the router will work more efficiently compared to the existing systems. From the results table in the last section, the average sum rate has increased between 20% and 30%.

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Section: Packet Schedulingmentioning

confidence: 99%

Developing A New Scheduling Algorithm for Wi-Fi 6 Technology Based on Machine Learning

MASRİ¹,

ERDAL²

2022

Uluslararası Muhendislik Arastirma Ve Gelistirme Dergisi

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“…And route discovery for DYM AODV routing algorithm. Route maintenan efficient route, avoid the routes which does to reduce the packet dropping [5], [7], [9]. R DYMO takes less memory space when comp routing algorithm.…”

Section: B Dynamic Manet On-demand (Dymo) Ro Algorithmmentioning

confidence: 99%

“…The Bellman-Ford is a proactive algorith the shortest path from the single source no other nodes in the network [9]. Each node distances between itself and all other no network and stores this information in its rou node sends its routing …”

Section: Bellman-ford Algorithmmentioning

confidence: 99%

An analysis and comparison of different routing algorithms in WiMAX networks

Sangeetha

Balipadi

Ismail

et al. 2015

2015 IEEE International Advance Computing Conference (IACC)

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World-wide interoperability for Microwave Access(WiMAX) is a wireless metropolitan area networks (WMANs). Routing and multimedia application plays an important role in the WiMAX networks. In this study, the main focus is on analyzing and comparing the different routing algorithms such as AODV, DYMO, DSR, Bellman-Ford and Fish-Eye for the WiMAX networks. We have considered few QoS parameters such as total data received, average end-to-end delay, average jitter and throughput. Here, we have considered the CBR application. From the obtained result DSR routing algorithm outperforms high throughput and total data received. Bellman-Ford and Fish-Eye provides less average end-to-end delay. Bellman-Ford routing algorithm also provides less average jitter.

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Surveying Best Suitable Scheduling Algorithm for Wimax- Wi-Fi Integrated Heterogeneous Network

Abstract: ABSTRACT

Cited by 2 publications

References 17 publications

Developing A New Scheduling Algorithm for Wi-Fi 6 Technology Based on Machine Learning

Developing A New Scheduling Algorithm for Wi-Fi 6 Technology Based on Machine Learning

An analysis and comparison of different routing algorithms in WiMAX networks

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