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Distributed algorithm for AP association with random arrivals and departures of users
Author(s) -
Chen Zhenwei,
Zhang Wenjie,
Zheng Yifeng,
Yang Liwei,
Yeo Chai Kiat
Publication year - 2020
Publication title -
iet communications
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.355
H-Index - 62
eISSN - 1751-8636
pISSN - 1751-8628
DOI - 10.1049/iet-com.2019.0817
Subject(s) - computer science , association (psychology) , algorithm , psychology , psychotherapist
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 / 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.

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