Delay efficient opportunistic routing in asynchronous multi-channel cognitive radio networks

Abstract In this paper, we are interested in designing efficient distributed opportunistic routing protocols for multi-hop multi-channel cognitive radio networks (CRNs). In CRNs, secondary users (SUs) access unused primary channels opportunistically, which induces considerable end-to-end delays for...
Ausführliche Beschreibung

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Autor*in:	Cai, Zhipeng [verfasserIn] Duan, Yueming [verfasserIn] Bourgeois, Anu G. [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2013

Schlagwörter:	Cross-layer routing Forwarding set Cognitive radio network Opportunistic routing

Übergeordnetes Werk:	Enthalten in: Journal of combinatorial optimization - Dordrecht [u.a.] : Springer Science + Business Media B.V, 1997, 29(2013), 4 vom: 16. Mai, Seite 815-835
Übergeordnetes Werk:	volume:29 ; year:2013 ; number:4 ; day:16 ; month:05 ; pages:815-835

Links:	Volltext

DOI / URN:	10.1007/s10878-013-9623-y

Katalog-ID:	SPR014286793

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520			\|a Abstract In this paper, we are interested in designing efficient distributed opportunistic routing protocols for multi-hop multi-channel cognitive radio networks (CRNs). In CRNs, secondary users (SUs) access unused primary channels opportunistically, which induces considerable end-to-end delays for multi-hop routing. The primary cause of the delay overhead is that the set of available channels change dynamically over time due to the activities of primary users, making it challenging to effectively explore the spectrum diversity. Our approach towards working with such a dynamic network is to construct a cross-layer distributed opportunistic routing protocol. Our protocol jointly considers the channel sensing strategy, the forwarder selection for each SU, and the package division scheme on each link. We mathematically model the expected delay of each hop along the routing path. This delay model sheds lights on our expected end-to-end delay analysis, from which we develop a distributed algorithm to derive the system parameters for the opportunistic routing protocol. Extensive simulation results indicate the improved performance of our opportunistic routing protocol in terms of end-to-end delay, especially for CRNs with highly dynamic channel conditions.
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matchkey_str	article:15732886:2013----::eaefcetpotnsiruignsnhoosutcanl
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allfields	10.1007/s10878-013-9623-y doi (DE-627)SPR014286793 (SPR)s10878-013-9623-y-e DE-627 ger DE-627 rakwb eng 510 ASE 31.12 bkl 31.80 bkl Cai, Zhipeng verfasserin aut Delay efficient opportunistic routing in asynchronous multi-channel cognitive radio networks 2013 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract In this paper, we are interested in designing efficient distributed opportunistic routing protocols for multi-hop multi-channel cognitive radio networks (CRNs). In CRNs, secondary users (SUs) access unused primary channels opportunistically, which induces considerable end-to-end delays for multi-hop routing. The primary cause of the delay overhead is that the set of available channels change dynamically over time due to the activities of primary users, making it challenging to effectively explore the spectrum diversity. Our approach towards working with such a dynamic network is to construct a cross-layer distributed opportunistic routing protocol. Our protocol jointly considers the channel sensing strategy, the forwarder selection for each SU, and the package division scheme on each link. We mathematically model the expected delay of each hop along the routing path. This delay model sheds lights on our expected end-to-end delay analysis, from which we develop a distributed algorithm to derive the system parameters for the opportunistic routing protocol. Extensive simulation results indicate the improved performance of our opportunistic routing protocol in terms of end-to-end delay, especially for CRNs with highly dynamic channel conditions. Cross-layer routing (dpeaa)DE-He213 Forwarding set (dpeaa)DE-He213 Cognitive radio network (dpeaa)DE-He213 Opportunistic routing (dpeaa)DE-He213 Duan, Yueming verfasserin aut Bourgeois, Anu G. verfasserin aut Enthalten in Journal of combinatorial optimization Dordrecht [u.a.] : Springer Science + Business Media B.V, 1997 29(2013), 4 vom: 16. Mai, Seite 815-835 (DE-627)313324085 (DE-600)2005418-X 1573-2886 nnns volume:29 year:2013 number:4 day:16 month:05 pages:815-835 https://dx.doi.org/10.1007/s10878-013-9623-y lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OPC-MAT SSG-OPC-ASE GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 31.12 ASE 31.80 ASE AR 29 2013 4 16 05 815-835
spelling	10.1007/s10878-013-9623-y doi (DE-627)SPR014286793 (SPR)s10878-013-9623-y-e DE-627 ger DE-627 rakwb eng 510 ASE 31.12 bkl 31.80 bkl Cai, Zhipeng verfasserin aut Delay efficient opportunistic routing in asynchronous multi-channel cognitive radio networks 2013 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract In this paper, we are interested in designing efficient distributed opportunistic routing protocols for multi-hop multi-channel cognitive radio networks (CRNs). In CRNs, secondary users (SUs) access unused primary channels opportunistically, which induces considerable end-to-end delays for multi-hop routing. The primary cause of the delay overhead is that the set of available channels change dynamically over time due to the activities of primary users, making it challenging to effectively explore the spectrum diversity. Our approach towards working with such a dynamic network is to construct a cross-layer distributed opportunistic routing protocol. Our protocol jointly considers the channel sensing strategy, the forwarder selection for each SU, and the package division scheme on each link. We mathematically model the expected delay of each hop along the routing path. This delay model sheds lights on our expected end-to-end delay analysis, from which we develop a distributed algorithm to derive the system parameters for the opportunistic routing protocol. Extensive simulation results indicate the improved performance of our opportunistic routing protocol in terms of end-to-end delay, especially for CRNs with highly dynamic channel conditions. Cross-layer routing (dpeaa)DE-He213 Forwarding set (dpeaa)DE-He213 Cognitive radio network (dpeaa)DE-He213 Opportunistic routing (dpeaa)DE-He213 Duan, Yueming verfasserin aut Bourgeois, Anu G. verfasserin aut Enthalten in Journal of combinatorial optimization Dordrecht [u.a.] : Springer Science + Business Media B.V, 1997 29(2013), 4 vom: 16. Mai, Seite 815-835 (DE-627)313324085 (DE-600)2005418-X 1573-2886 nnns volume:29 year:2013 number:4 day:16 month:05 pages:815-835 https://dx.doi.org/10.1007/s10878-013-9623-y lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OPC-MAT SSG-OPC-ASE GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 31.12 ASE 31.80 ASE AR 29 2013 4 16 05 815-835
allfields_unstemmed	10.1007/s10878-013-9623-y doi (DE-627)SPR014286793 (SPR)s10878-013-9623-y-e DE-627 ger DE-627 rakwb eng 510 ASE 31.12 bkl 31.80 bkl Cai, Zhipeng verfasserin aut Delay efficient opportunistic routing in asynchronous multi-channel cognitive radio networks 2013 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract In this paper, we are interested in designing efficient distributed opportunistic routing protocols for multi-hop multi-channel cognitive radio networks (CRNs). In CRNs, secondary users (SUs) access unused primary channels opportunistically, which induces considerable end-to-end delays for multi-hop routing. The primary cause of the delay overhead is that the set of available channels change dynamically over time due to the activities of primary users, making it challenging to effectively explore the spectrum diversity. Our approach towards working with such a dynamic network is to construct a cross-layer distributed opportunistic routing protocol. Our protocol jointly considers the channel sensing strategy, the forwarder selection for each SU, and the package division scheme on each link. We mathematically model the expected delay of each hop along the routing path. This delay model sheds lights on our expected end-to-end delay analysis, from which we develop a distributed algorithm to derive the system parameters for the opportunistic routing protocol. Extensive simulation results indicate the improved performance of our opportunistic routing protocol in terms of end-to-end delay, especially for CRNs with highly dynamic channel conditions. Cross-layer routing (dpeaa)DE-He213 Forwarding set (dpeaa)DE-He213 Cognitive radio network (dpeaa)DE-He213 Opportunistic routing (dpeaa)DE-He213 Duan, Yueming verfasserin aut Bourgeois, Anu G. verfasserin aut Enthalten in Journal of combinatorial optimization Dordrecht [u.a.] : Springer Science + Business Media B.V, 1997 29(2013), 4 vom: 16. Mai, Seite 815-835 (DE-627)313324085 (DE-600)2005418-X 1573-2886 nnns volume:29 year:2013 number:4 day:16 month:05 pages:815-835 https://dx.doi.org/10.1007/s10878-013-9623-y lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OPC-MAT SSG-OPC-ASE GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 31.12 ASE 31.80 ASE AR 29 2013 4 16 05 815-835
allfieldsGer	10.1007/s10878-013-9623-y doi (DE-627)SPR014286793 (SPR)s10878-013-9623-y-e DE-627 ger DE-627 rakwb eng 510 ASE 31.12 bkl 31.80 bkl Cai, Zhipeng verfasserin aut Delay efficient opportunistic routing in asynchronous multi-channel cognitive radio networks 2013 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract In this paper, we are interested in designing efficient distributed opportunistic routing protocols for multi-hop multi-channel cognitive radio networks (CRNs). In CRNs, secondary users (SUs) access unused primary channels opportunistically, which induces considerable end-to-end delays for multi-hop routing. The primary cause of the delay overhead is that the set of available channels change dynamically over time due to the activities of primary users, making it challenging to effectively explore the spectrum diversity. Our approach towards working with such a dynamic network is to construct a cross-layer distributed opportunistic routing protocol. Our protocol jointly considers the channel sensing strategy, the forwarder selection for each SU, and the package division scheme on each link. We mathematically model the expected delay of each hop along the routing path. This delay model sheds lights on our expected end-to-end delay analysis, from which we develop a distributed algorithm to derive the system parameters for the opportunistic routing protocol. Extensive simulation results indicate the improved performance of our opportunistic routing protocol in terms of end-to-end delay, especially for CRNs with highly dynamic channel conditions. Cross-layer routing (dpeaa)DE-He213 Forwarding set (dpeaa)DE-He213 Cognitive radio network (dpeaa)DE-He213 Opportunistic routing (dpeaa)DE-He213 Duan, Yueming verfasserin aut Bourgeois, Anu G. verfasserin aut Enthalten in Journal of combinatorial optimization Dordrecht [u.a.] : Springer Science + Business Media B.V, 1997 29(2013), 4 vom: 16. Mai, Seite 815-835 (DE-627)313324085 (DE-600)2005418-X 1573-2886 nnns volume:29 year:2013 number:4 day:16 month:05 pages:815-835 https://dx.doi.org/10.1007/s10878-013-9623-y lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OPC-MAT SSG-OPC-ASE GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 31.12 ASE 31.80 ASE AR 29 2013 4 16 05 815-835
allfieldsSound	10.1007/s10878-013-9623-y doi (DE-627)SPR014286793 (SPR)s10878-013-9623-y-e DE-627 ger DE-627 rakwb eng 510 ASE 31.12 bkl 31.80 bkl Cai, Zhipeng verfasserin aut Delay efficient opportunistic routing in asynchronous multi-channel cognitive radio networks 2013 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract In this paper, we are interested in designing efficient distributed opportunistic routing protocols for multi-hop multi-channel cognitive radio networks (CRNs). In CRNs, secondary users (SUs) access unused primary channels opportunistically, which induces considerable end-to-end delays for multi-hop routing. The primary cause of the delay overhead is that the set of available channels change dynamically over time due to the activities of primary users, making it challenging to effectively explore the spectrum diversity. Our approach towards working with such a dynamic network is to construct a cross-layer distributed opportunistic routing protocol. Our protocol jointly considers the channel sensing strategy, the forwarder selection for each SU, and the package division scheme on each link. We mathematically model the expected delay of each hop along the routing path. This delay model sheds lights on our expected end-to-end delay analysis, from which we develop a distributed algorithm to derive the system parameters for the opportunistic routing protocol. Extensive simulation results indicate the improved performance of our opportunistic routing protocol in terms of end-to-end delay, especially for CRNs with highly dynamic channel conditions. Cross-layer routing (dpeaa)DE-He213 Forwarding set (dpeaa)DE-He213 Cognitive radio network (dpeaa)DE-He213 Opportunistic routing (dpeaa)DE-He213 Duan, Yueming verfasserin aut Bourgeois, Anu G. verfasserin aut Enthalten in Journal of combinatorial optimization Dordrecht [u.a.] : Springer Science + Business Media B.V, 1997 29(2013), 4 vom: 16. Mai, Seite 815-835 (DE-627)313324085 (DE-600)2005418-X 1573-2886 nnns volume:29 year:2013 number:4 day:16 month:05 pages:815-835 https://dx.doi.org/10.1007/s10878-013-9623-y lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OPC-MAT SSG-OPC-ASE GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 31.12 ASE 31.80 ASE AR 29 2013 4 16 05 815-835
language	English
source	Enthalten in Journal of combinatorial optimization 29(2013), 4 vom: 16. Mai, Seite 815-835 volume:29 year:2013 number:4 day:16 month:05 pages:815-835
sourceStr	Enthalten in Journal of combinatorial optimization 29(2013), 4 vom: 16. Mai, Seite 815-835 volume:29 year:2013 number:4 day:16 month:05 pages:815-835
format_phy_str_mv	Article
institution	findex.gbv.de
topic_facet	Cross-layer routing Forwarding set Cognitive radio network Opportunistic routing
dewey-raw	510
isfreeaccess_bool	false
container_title	Journal of combinatorial optimization
authorswithroles_txt_mv	Cai, Zhipeng @@aut@@ Duan, Yueming @@aut@@ Bourgeois, Anu G. @@aut@@
publishDateDaySort_date	2013-05-16T00:00:00Z
hierarchy_top_id	313324085
dewey-sort	3510
id	SPR014286793
language_de	englisch
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In CRNs, secondary users (SUs) access unused primary channels opportunistically, which induces considerable end-to-end delays for multi-hop routing. The primary cause of the delay overhead is that the set of available channels change dynamically over time due to the activities of primary users, making it challenging to effectively explore the spectrum diversity. Our approach towards working with such a dynamic network is to construct a cross-layer distributed opportunistic routing protocol. Our protocol jointly considers the channel sensing strategy, the forwarder selection for each SU, and the package division scheme on each link. We mathematically model the expected delay of each hop along the routing path. This delay model sheds lights on our expected end-to-end delay analysis, from which we develop a distributed algorithm to derive the system parameters for the opportunistic routing protocol. 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author	Cai, Zhipeng
spellingShingle	Cai, Zhipeng ddc 510 bkl 31.12 bkl 31.80 misc Cross-layer routing misc Forwarding set misc Cognitive radio network misc Opportunistic routing Delay efficient opportunistic routing in asynchronous multi-channel cognitive radio networks
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topic_title	510 ASE 31.12 bkl 31.80 bkl Delay efficient opportunistic routing in asynchronous multi-channel cognitive radio networks Cross-layer routing (dpeaa)DE-He213 Forwarding set (dpeaa)DE-He213 Cognitive radio network (dpeaa)DE-He213 Opportunistic routing (dpeaa)DE-He213
topic	ddc 510 bkl 31.12 bkl 31.80 misc Cross-layer routing misc Forwarding set misc Cognitive radio network misc Opportunistic routing
topic_unstemmed	ddc 510 bkl 31.12 bkl 31.80 misc Cross-layer routing misc Forwarding set misc Cognitive radio network misc Opportunistic routing
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title	Delay efficient opportunistic routing in asynchronous multi-channel cognitive radio networks
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title_full	Delay efficient opportunistic routing in asynchronous multi-channel cognitive radio networks
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author_browse	Cai, Zhipeng Duan, Yueming Bourgeois, Anu G.
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title_sort	delay efficient opportunistic routing in asynchronous multi-channel cognitive radio networks
title_auth	Delay efficient opportunistic routing in asynchronous multi-channel cognitive radio networks
abstract	Abstract In this paper, we are interested in designing efficient distributed opportunistic routing protocols for multi-hop multi-channel cognitive radio networks (CRNs). In CRNs, secondary users (SUs) access unused primary channels opportunistically, which induces considerable end-to-end delays for multi-hop routing. The primary cause of the delay overhead is that the set of available channels change dynamically over time due to the activities of primary users, making it challenging to effectively explore the spectrum diversity. Our approach towards working with such a dynamic network is to construct a cross-layer distributed opportunistic routing protocol. Our protocol jointly considers the channel sensing strategy, the forwarder selection for each SU, and the package division scheme on each link. We mathematically model the expected delay of each hop along the routing path. This delay model sheds lights on our expected end-to-end delay analysis, from which we develop a distributed algorithm to derive the system parameters for the opportunistic routing protocol. Extensive simulation results indicate the improved performance of our opportunistic routing protocol in terms of end-to-end delay, especially for CRNs with highly dynamic channel conditions.
abstractGer	Abstract In this paper, we are interested in designing efficient distributed opportunistic routing protocols for multi-hop multi-channel cognitive radio networks (CRNs). In CRNs, secondary users (SUs) access unused primary channels opportunistically, which induces considerable end-to-end delays for multi-hop routing. The primary cause of the delay overhead is that the set of available channels change dynamically over time due to the activities of primary users, making it challenging to effectively explore the spectrum diversity. Our approach towards working with such a dynamic network is to construct a cross-layer distributed opportunistic routing protocol. Our protocol jointly considers the channel sensing strategy, the forwarder selection for each SU, and the package division scheme on each link. We mathematically model the expected delay of each hop along the routing path. This delay model sheds lights on our expected end-to-end delay analysis, from which we develop a distributed algorithm to derive the system parameters for the opportunistic routing protocol. Extensive simulation results indicate the improved performance of our opportunistic routing protocol in terms of end-to-end delay, especially for CRNs with highly dynamic channel conditions.
abstract_unstemmed	Abstract In this paper, we are interested in designing efficient distributed opportunistic routing protocols for multi-hop multi-channel cognitive radio networks (CRNs). In CRNs, secondary users (SUs) access unused primary channels opportunistically, which induces considerable end-to-end delays for multi-hop routing. The primary cause of the delay overhead is that the set of available channels change dynamically over time due to the activities of primary users, making it challenging to effectively explore the spectrum diversity. Our approach towards working with such a dynamic network is to construct a cross-layer distributed opportunistic routing protocol. Our protocol jointly considers the channel sensing strategy, the forwarder selection for each SU, and the package division scheme on each link. We mathematically model the expected delay of each hop along the routing path. This delay model sheds lights on our expected end-to-end delay analysis, from which we develop a distributed algorithm to derive the system parameters for the opportunistic routing protocol. Extensive simulation results indicate the improved performance of our opportunistic routing protocol in terms of end-to-end delay, especially for CRNs with highly dynamic channel conditions.
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container_issue	4
title_short	Delay efficient opportunistic routing in asynchronous multi-channel cognitive radio networks
url	https://dx.doi.org/10.1007/s10878-013-9623-y
remote_bool	true
author2	Duan, Yueming Bourgeois, Anu G.
author2Str	Duan, Yueming Bourgeois, Anu G.
ppnlink	313324085
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hochschulschrift_bool	false
doi_str	10.1007/s10878-013-9623-y
up_date	2024-07-04T01:02:18.240Z
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Delay efficient opportunistic routing in asynchronous multi-channel cognitive radio networks

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