Call Admission Control Using Bio-Geography Based Optimization
The chapter proposes a new approach to call admission control in a mobile cellular network using Bio-geography based optimization. Existing algorithms on call admission control either ignore both variation in traffic conditions or velocity of mobile devices, or at most consider one of them. This cha...
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| Autor*in: |
Ghosh, Sanchita [verfasserIn] Konar, Amit [verfasserIn] |
|---|
| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2015 |
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| Umfang: |
1 Online-Ressource |
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| Übergeordnetes Werk: |
Enthalten in: International journal of applied evolutionary computation - Hershey, Pa : IGI Global, 2010, 6(2015), 1, Seite 49-71 |
|---|---|
| Übergeordnetes Werk: |
volume:6 ; year:2015 ; number:1 ; pages:49-71 |
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| DOI / URN: |
10.4018/IJAEC.2015010103 |
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NLEJ251784142 |
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| 520 | |a The chapter proposes a new approach to call admission control in a mobile cellular network using Bio-geography based optimization. Existing algorithms on call admission control either ignore both variation in traffic conditions or velocity of mobile devices, or at most consider one of them. This chapter overcomes the above problems jointly by formulating call admission control as a constrained optimization problem, where the primary objective is to minimize the call drop under dynamic condition of the mobile stations, satisfying the constraints to maximize the channel assignment and minimize the dynamic traffic load in the network. The constrained objective function has been minimized using Bio-geography based optimization. Experimental results and computer simulations envisage that the proposed algorithm outperforms most of the existing approaches on call admission control, considering either of the two issues addressed above | ||
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10.4018/IJAEC.2015010103 doi (DE-627)NLEJ251784142 (VZGNL)10.4018/IJAEC.2015010103 DE-627 ger DE-627 rakwb eng Ghosh, Sanchita verfasserin aut Call Admission Control Using Bio-Geography Based Optimization 2015 1 Online-Ressource Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier The chapter proposes a new approach to call admission control in a mobile cellular network using Bio-geography based optimization. Existing algorithms on call admission control either ignore both variation in traffic conditions or velocity of mobile devices, or at most consider one of them. This chapter overcomes the above problems jointly by formulating call admission control as a constrained optimization problem, where the primary objective is to minimize the call drop under dynamic condition of the mobile stations, satisfying the constraints to maximize the channel assignment and minimize the dynamic traffic load in the network. The constrained objective function has been minimized using Bio-geography based optimization. Experimental results and computer simulations envisage that the proposed algorithm outperforms most of the existing approaches on call admission control, considering either of the two issues addressed above Biogeography Call Admission Control Emigration Immigration Migration Konar, Amit verfasserin aut Enthalten in International journal of applied evolutionary computation Hershey, Pa : IGI Global, 2010 6(2015), 1, Seite 49-71 Online-Ressource (DE-627)NLEJ24441856X (DE-600)2696101-5 1942-3608 nnns volume:6 year:2015 number:1 pages:49-71 http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/IJAEC.2015010103 X:IGIG Verlag Deutschlandweit zugänglich http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/IJAEC.2015010103&buylink=true Abstract ZDB-1-GIS GBV_NL_ARTICLE AR 6 2015 1 49-71 |
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The chapter proposes a new approach to call admission control in a mobile cellular network using Bio-geography based optimization. Existing algorithms on call admission control either ignore both variation in traffic conditions or velocity of mobile devices, or at most consider one of them. This chapter overcomes the above problems jointly by formulating call admission control as a constrained optimization problem, where the primary objective is to minimize the call drop under dynamic condition of the mobile stations, satisfying the constraints to maximize the channel assignment and minimize the dynamic traffic load in the network. The constrained objective function has been minimized using Bio-geography based optimization. Experimental results and computer simulations envisage that the proposed algorithm outperforms most of the existing approaches on call admission control, considering either of the two issues addressed above |
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<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000caa a22002652 4500</leader><controlfield tag="001">NLEJ251784142</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20231205143824.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">231128s2015 xx |||||o 00| ||eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.4018/IJAEC.2015010103</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)NLEJ251784142</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(VZGNL)10.4018/IJAEC.2015010103</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rakwb</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Ghosh, Sanchita</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Call Admission Control Using Bio-Geography Based Optimization</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2015</subfield></datafield><datafield tag="300" ind1=" " ind2=" "><subfield code="a">1 Online-Ressource</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">Text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">Computermedien</subfield><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Online-Ressource</subfield><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">The chapter proposes a new approach to call admission control in a mobile cellular network using Bio-geography based optimization. Existing algorithms on call admission control either ignore both variation in traffic conditions or velocity of mobile devices, or at most consider one of them. This chapter overcomes the above problems jointly by formulating call admission control as a constrained optimization problem, where the primary objective is to minimize the call drop under dynamic condition of the mobile stations, satisfying the constraints to maximize the channel assignment and minimize the dynamic traffic load in the network. The constrained objective function has been minimized using Bio-geography based optimization. Experimental results and computer simulations envisage that the proposed algorithm outperforms most of the existing approaches on call admission control, considering either of the two issues addressed above</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">Biogeography</subfield><subfield code="a">Call Admission Control</subfield><subfield code="a">Emigration</subfield><subfield code="a">Immigration</subfield><subfield code="a">Migration</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Konar, Amit</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="773" ind1="0" ind2="8"><subfield code="i">Enthalten in</subfield><subfield code="t">International journal of applied evolutionary computation</subfield><subfield code="d">Hershey, Pa : IGI Global, 2010</subfield><subfield code="g">6(2015), 1, Seite 49-71</subfield><subfield code="h">Online-Ressource</subfield><subfield code="w">(DE-627)NLEJ24441856X</subfield><subfield code="w">(DE-600)2696101-5</subfield><subfield code="x">1942-3608</subfield><subfield code="7">nnns</subfield></datafield><datafield tag="773" ind1="1" ind2="8"><subfield code="g">volume:6</subfield><subfield code="g">year:2015</subfield><subfield code="g">number:1</subfield><subfield code="g">pages:49-71</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/IJAEC.2015010103</subfield><subfield code="m">X:IGIG</subfield><subfield code="x">Verlag</subfield><subfield code="z">Deutschlandweit zugänglich</subfield></datafield><datafield tag="856" ind1="4" ind2="2"><subfield code="u">http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/IJAEC.2015010103&buylink=true</subfield><subfield code="3">Abstract</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">ZDB-1-GIS</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_NL_ARTICLE</subfield></datafield><datafield tag="951" ind1=" " ind2=" "><subfield code="a">AR</subfield></datafield><datafield tag="952" ind1=" " ind2=" "><subfield code="d">6</subfield><subfield code="j">2015</subfield><subfield code="e">1</subfield><subfield code="h">49-71</subfield></datafield></record></collection>
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