Distributed algorithm for AP association with random arrivals and departures of users

Here, the authors study the novel problem of optimising access point (AP) association by maximising the network throughput, subject to the degree bound of AP. The formulated problem is a combinatorial optimisation. They resort to the Markov Chain approximation technique to design a distributed algor...

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Vydáno v:IET communications Ročník 14; číslo 5; s. 846 - 856
Hlavní autoři: Chen, Zhenwei, Zhang, Wenjie, Zheng, Yifeng, Yang, Liwei, Yeo, ChaiKiat
Médium: Journal Article
Jazyk:angličtina
Vydáno: The Institution of Engineering and Technology 17.03.2020
Témata:
access point association
AP association
approximation theory
combinatorial mathematics
combinatorial optimisation
distributed algorithm
distributed algorithms
Log‐Sum‐Exp function
Markov Chain approximation technique
Markov processes
optimisation
random arrivals
Research Article
static problem
steady‐state distribution
user departures
wireless LAN
wireless local area networks
WLAN
approximation theory
combinatorial mathematics
wireless local area networks
user departures
WLAN
combinatorial optimisation
AP association
distributed algorithm
Log-Sum-Exp function
optimisation
access point association
static problem
distributed algorithms
Markov Chain approximation technique
Markov processes
random arrivals
wireless LAN
steady-state distribution
ISSN:1751-8628, 1751-8636
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Popis
Shrnutí:Here, the authors study the novel problem of optimising access point (AP) association by maximising the network throughput, subject to the degree bound of AP. The formulated problem is a combinatorial optimisation. They resort to the Markov Chain approximation technique to design a distributed algorithm. They first approximate their optimal objective via Log-Sum-Exp function. Thereafter, they construct a special class of Markov Chain with steady-state distribution specify to their problem to yield a distributed solution. Furthermore, they extend the static problem setting to a dynamic environment where the users can randomly leave or join the system. Their proposed algorithm has provable performance, achieving an approximation gap of $({1}/{\eta})\log |\mathscr {F}|$(1/η)log⁡|F|. It is simple and can be implemented in a distributed manner. Their extensive simulation results show that the proposed algorithm can converge very fast, and achieve a close-to-optimal performance with a guaranteed loss bound.
ISSN:1751-8628
1751-8636
DOI:10.1049/iet-com.2019.0817