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A Multi-Objective Model-Based Vertical Handoff Algorithm for Heterogeneous Wireless Networks
Honggui Deng
Central South University
Corresponding Author
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An optimized algorithm based on multi-objective optimization model is proposed to solve the problem that existing vertical handoff algorithms do not comprehensively consider the impact of users and the network during handoff process. We build Markov chain model of base station to calculate a more accurate network state. Then a multi-objective optimization model is derived to maximize the value of the network state and the user data receiving rate. The multi-objective genetic algorithm NSGA-II is finally employed to turn the model into a final vertical handoffff strategy. The results of the simulation for throughput and blocking rate of networks demonstrate our algorithm significantly increases the system throughput and reduces the blocking rate compared with the existing vertical switching strategy.
Keywords
Vertical handoff, multi-objective optimization, network status value, NSGA-II
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Peer Review Timeline
CURRENT STATUS: Under Review
Version 1
Posted 21 Sep, 2020
No community comments so far
Review #3 received
Received 09 Dec, 2020
Editorial decision: Major revision
On 09 Dec, 2020
Review #1 received
Received 20 Nov, 2020
Review #2 received
Received 18 Nov, 2020
Reviewer #3 agreed
On 13 Nov, 2020
Reviewer #2 agreed
On 11 Nov, 2020
Reviewer #1 agreed
On 26 Oct, 2020
Reviewers invited
Invitations sent on 16 Oct, 2020
Editor assigned
On 23 Sep, 2020
Editor invited
On 22 Sep, 2020
Submission checks complete
On 18 Sep, 2020
First submitted
On 15 Sep, 2020
Metrics
Comments: 0
PDF Downloads: ...
HTML Views: ...
Subject Areas
Technical Communication
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This preprint is under consideration at EURASIP Journal on Wireless Communications and Networking. A preprint is a preliminary version of a manuscript that has not completed peer review at a journal. Research Square does not conduct peer review prior to posting preprints. The posting of a preprint on this server should not be interpreted as an endorsement of its validity or suitability for dissemination as established information or for guiding clinical practice.
Learn more about In Review
Research
A Multi-Objective Model-Based Vertical Handoff Algorithm for Heterogeneous Wireless Networks
Honggui Deng
Central South University
Corresponding Author
Badges
Prescreen
This manuscript passed our Prescreen assessment
Complete author information
Appropriate declaration statements
Potential risks to human health
Prescreen
Peer Review Timeline
CURRENT STATUS: Under Review
Version 1
Posted 21 Sep, 2020
No community comments so far
Review #3 received
Received 09 Dec, 2020
Editorial decision: Major revision
On 09 Dec, 2020
Review #1 received
Received 20 Nov, 2020
Review #2 received
Received 18 Nov, 2020
Reviewer #3 agreed
On 13 Nov, 2020
Reviewer #2 agreed
On 11 Nov, 2020
Reviewer #1 agreed
On 26 Oct, 2020
Reviewers invited
Invitations sent on 16 Oct, 2020
Editor assigned
On 23 Sep, 2020
Editor invited
On 22 Sep, 2020
Submission checks complete
On 18 Sep, 2020
First submitted
On 15 Sep, 2020
Metrics
Comments: 0
PDF Downloads: ...
HTML Views: ...
Subject Areas
Technical Communication
License:
This work is licensed under a CC BY 4.0 License. Read Full License
An optimized algorithm based on multi-objective optimization model is proposed to solve the problem that existing vertical handoff algorithms do not comprehensively consider the impact of users and the network during handoff process. We build Markov chain model of base station to calculate a more accurate network state. Then a multi-objective optimization model is derived to maximize the value of the network state and the user data receiving rate. The multi-objective genetic algorithm NSGA-II is finally employed to turn the model into a final vertical handoffff strategy. The results of the simulation for throughput and blocking rate of networks demonstrate our algorithm significantly increases the system throughput and reduces the blocking rate compared with the existing vertical switching strategy.
Figure 1
Figure 2
Figure 3
Figure 4
Due to technical limitations, full-text HTML conversion of this manuscript could not be completed. However, the manuscript can be downloaded and accessed as a PDF.