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Erschienen in: Neural Computing and Applications 7/2020

29.09.2018 | Brain- Inspired computing and Machine learning for Brain Health

An admission control algorithm based on matching game and differentiated service in wireless mesh networks

verfasst von: Fengjun Shang, Dan Zhou, Dexiang He

Erschienen in: Neural Computing and Applications | Ausgabe 7/2020

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Abstract

With the widespread application and popularity of wireless mesh networks, related resource allocation, load balancing and network security issues have attracted the attention of many researchers and scholars. The admission control strategy can effectively solve related problems such as network load balancing and network resource allocation. At present, the majority of admission control related research is mainly aimed at a single factor such as user or access points. Little researches consider both of them at the same time. However, admission control strategies often require decision making based on multiple factors. This paper takes the overall benefit of the game participants as the optimization goal, establishes a reasonable and effective admission control model and completes the new user access control and network resource allocation problems. According to the network’s attribute and system resource allocation, this paper proposes an admission control model based on matching game and multi-attribute decision making. The algorithm proposed in this paper balances the interests of the network and user, reflects the superiority of the balanced decision of both parties, and guarantees the common interests of the network and the user.

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Metadaten
Titel
An admission control algorithm based on matching game and differentiated service in wireless mesh networks
verfasst von
Fengjun Shang
Dan Zhou
Dexiang He
Publikationsdatum
29.09.2018
Verlag
Springer London
Erschienen in
Neural Computing and Applications / Ausgabe 7/2020
Print ISSN: 0941-0643
Elektronische ISSN: 1433-3058
DOI
https://doi.org/10.1007/s00521-018-3751-3

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