Skip navigation
Skip navigation

Delay-Minimized Routing in Mobile Cognitive Networks for Time-Critical Applications

Tang, Feilong; Tang, Can; Yang, Yanqin; Yang, L T; Zhou, Tong; Li, Jie; Guo, Minyi

Description

Cognitive radio significantly mitigates the spectrum scarcity for various applications built on wireless communication. Current techniques on mobile cognitive ad hoc networks (MCADNs), however, cannot be directly applied to time-critical applications due to channel interference, node mobility as well as unexpected primary user activities. In multichannel multiflow MCADNs, it becomes even worse because multiple links potentially interfere with each other. In this paper, we propose a...[Show more]

dc.contributor.authorTang, Feilong
dc.contributor.authorTang, Can
dc.contributor.authorYang, Yanqin
dc.contributor.authorYang, L T
dc.contributor.authorZhou, Tong
dc.contributor.authorLi, Jie
dc.contributor.authorGuo, Minyi
dc.date.accessioned2021-06-04T01:34:08Z
dc.identifier.issn1551-3203
dc.identifier.urihttp://hdl.handle.net/1885/236752
dc.description.abstractCognitive radio significantly mitigates the spectrum scarcity for various applications built on wireless communication. Current techniques on mobile cognitive ad hoc networks (MCADNs), however, cannot be directly applied to time-critical applications due to channel interference, node mobility as well as unexpected primary user activities. In multichannel multiflow MCADNs, it becomes even worse because multiple links potentially interfere with each other. In this paper, we propose a delay-minimized routing (DMR) protocol for multichannel multiflow MCADNs. First, we formulate the DMR problem with the objective of delay minimization. Next, we propose a delay prediction model based on a conflict probability. Finally, we design the minimized path delay as a routing metric, and propose a heuristic joint routing and channel assignment algorithm to solve the DMR problem. Our DMR can find out the path with a minimal end-to-end (e2e) delay for time-critical data transmission. NS2-based simulation results demonstrate that our DMR protocol significantly outperforms related proposals in terms of average e2e delay, throughput, and packet loss rate.
dc.description.sponsorshipThis work was supported in part by the National Natural Science Foundation of China projects under Grant 91438121, Grant 61373156, Grant 61672351, and Grant 61532013, in part by the National Basic Research Program (973 Program) under Grant 2015CB352403, and in part by the Huawei Technologies Co., Ltd., projects under Grant YB2015090040, Grant YBN2016090103 and Grant YB2015080089. Paper no. TII-15- 1713. (Corresponding author: F. Tang.)
dc.format.mimetypeapplication/pdf
dc.language.isoen_AU
dc.publisherIEEE Computer Society
dc.rights© 2016 IEEE.
dc.sourceIEEE Transactions on Industrial Informatics
dc.subjectChannel assignment
dc.subjectdelay prediction
dc.subjectmobile cognitive radio network
dc.subjectrouting
dc.subjectsignal collision
dc.titleDelay-Minimized Routing in Mobile Cognitive Networks for Time-Critical Applications
dc.typeJournal article
local.description.notesImported from ARIES
local.identifier.citationvolume13
dc.date.issued2017
local.identifier.absfor080607 - Information Engineering and Theory
local.identifier.ariespublicationu4485658xPUB879
local.publisher.urlhttps://www.ieee.org/
local.type.statusPublished Version
local.contributor.affiliationTang, Feilong, Shanghai Jiao Tong University
local.contributor.affiliationTang, Can, College of Business and Economics, ANU
local.contributor.affiliationYang, Yanqin, East China Normal University
local.contributor.affiliationYang, L T, St Francis Xavier University
local.contributor.affiliationZhou, Tong, Shanghai Jiao Tong University
local.contributor.affiliationLi, Jie, University of Tsukuba
local.contributor.affiliationGuo, Minyi, Shanghai Jiao Tong University
local.description.embargo2099-12-31
local.bibliographicCitation.issue3
local.bibliographicCitation.startpage1398
local.bibliographicCitation.lastpage1409
local.identifier.doi10.1109/TII.2016.2610408
local.identifier.absseo890205 - Information Processing Services (incl. Data Entry and Capture)
dc.date.updated2020-11-23T10:24:12Z
local.identifier.scopusID2-s2.0-85020637892
local.identifier.thomsonID000402929700047
CollectionsANU Research Publications

Download

File Description SizeFormat Image
01_Tang_Delay-Minimized_Routing_in_2017.pdf1.19 MBAdobe PDF    Request a copy


Items in Open Research are protected by copyright, with all rights reserved, unless otherwise indicated.

Updated:  17 November 2022/ Responsible Officer:  University Librarian/ Page Contact:  Library Systems & Web Coordinator