Offloading Optimization and Time Allocation for Multiuser Wireless Energy Transfer Based Mobile Edge Computing System
Abstract This paper considers a wireless energy transfer based mobile edge computing system, where wireless devices can be charged by the radio-frequency signals broadcast by hybrid access point. With Mobile Edge Computing (MEC), wireless devices can execute their computation tasks locally or offloa...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Li, Chunlin [verfasserIn] |
|---|
| Format: |
Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2020 |
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| Schlagwörter: |
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| Anmerkung: |
© Springer Science+Business Media, LLC, part of Springer Nature 2020 |
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| Übergeordnetes Werk: |
Enthalten in: Mobile networks and applications - Springer US, 1996, 27(2020), 5 vom: 09. Jan., Seite 1783-1791 |
|---|---|
| Übergeordnetes Werk: |
volume:27 ; year:2020 ; number:5 ; day:09 ; month:01 ; pages:1783-1791 |
| Links: |
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| DOI / URN: |
10.1007/s11036-019-01396-3 |
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OLC2079830090 |
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| 520 | |a Abstract This paper considers a wireless energy transfer based mobile edge computing system, where wireless devices can be charged by the radio-frequency signals broadcast by hybrid access point. With Mobile Edge Computing (MEC), wireless devices can execute their computation tasks locally or offload them to the MEC server by time division multiple access protocol. Based on this system, this paper studies the problem of system energy efficiency maximization by joint optimization of computing time allocation, energy consumption, capacity of local computing and task offloading. A Tabu search based system energy efficiency maximization algorithm is proposed for solving the optimization problems. Finally, the performance of the proposed algorithm is valued by extensive simulation experiments. Simulation results verify the effectiveness of the proposed algorithm. | ||
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| 700 | 1 | |a Luo, Youlong |4 aut | |
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10.1007/s11036-019-01396-3 doi (DE-627)OLC2079830090 (DE-He213)s11036-019-01396-3-p DE-627 ger DE-627 rakwb eng 004 VZ Li, Chunlin verfasserin aut Offloading Optimization and Time Allocation for Multiuser Wireless Energy Transfer Based Mobile Edge Computing System 2020 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer Science+Business Media, LLC, part of Springer Nature 2020 Abstract This paper considers a wireless energy transfer based mobile edge computing system, where wireless devices can be charged by the radio-frequency signals broadcast by hybrid access point. With Mobile Edge Computing (MEC), wireless devices can execute their computation tasks locally or offload them to the MEC server by time division multiple access protocol. Based on this system, this paper studies the problem of system energy efficiency maximization by joint optimization of computing time allocation, energy consumption, capacity of local computing and task offloading. A Tabu search based system energy efficiency maximization algorithm is proposed for solving the optimization problems. Finally, the performance of the proposed algorithm is valued by extensive simulation experiments. Simulation results verify the effectiveness of the proposed algorithm. Offloading optimization Time allocation Task offloading Mobile edge computing Song, Mingyang aut Zhang, Lei aut Chen, Weining aut Luo, Youlong aut Enthalten in Mobile networks and applications Springer US, 1996 27(2020), 5 vom: 09. Jan., Seite 1783-1791 (DE-627)215279522 (DE-600)1342049-5 (DE-576)063244756 1383-469X nnns volume:27 year:2020 number:5 day:09 month:01 pages:1783-1791 https://doi.org/10.1007/s11036-019-01396-3 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-MAT AR 27 2020 5 09 01 1783-1791 |
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10.1007/s11036-019-01396-3 doi (DE-627)OLC2079830090 (DE-He213)s11036-019-01396-3-p DE-627 ger DE-627 rakwb eng 004 VZ Li, Chunlin verfasserin aut Offloading Optimization and Time Allocation for Multiuser Wireless Energy Transfer Based Mobile Edge Computing System 2020 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer Science+Business Media, LLC, part of Springer Nature 2020 Abstract This paper considers a wireless energy transfer based mobile edge computing system, where wireless devices can be charged by the radio-frequency signals broadcast by hybrid access point. With Mobile Edge Computing (MEC), wireless devices can execute their computation tasks locally or offload them to the MEC server by time division multiple access protocol. Based on this system, this paper studies the problem of system energy efficiency maximization by joint optimization of computing time allocation, energy consumption, capacity of local computing and task offloading. A Tabu search based system energy efficiency maximization algorithm is proposed for solving the optimization problems. Finally, the performance of the proposed algorithm is valued by extensive simulation experiments. Simulation results verify the effectiveness of the proposed algorithm. Offloading optimization Time allocation Task offloading Mobile edge computing Song, Mingyang aut Zhang, Lei aut Chen, Weining aut Luo, Youlong aut Enthalten in Mobile networks and applications Springer US, 1996 27(2020), 5 vom: 09. Jan., Seite 1783-1791 (DE-627)215279522 (DE-600)1342049-5 (DE-576)063244756 1383-469X nnns volume:27 year:2020 number:5 day:09 month:01 pages:1783-1791 https://doi.org/10.1007/s11036-019-01396-3 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-MAT AR 27 2020 5 09 01 1783-1791 |
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10.1007/s11036-019-01396-3 doi (DE-627)OLC2079830090 (DE-He213)s11036-019-01396-3-p DE-627 ger DE-627 rakwb eng 004 VZ Li, Chunlin verfasserin aut Offloading Optimization and Time Allocation for Multiuser Wireless Energy Transfer Based Mobile Edge Computing System 2020 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer Science+Business Media, LLC, part of Springer Nature 2020 Abstract This paper considers a wireless energy transfer based mobile edge computing system, where wireless devices can be charged by the radio-frequency signals broadcast by hybrid access point. With Mobile Edge Computing (MEC), wireless devices can execute their computation tasks locally or offload them to the MEC server by time division multiple access protocol. Based on this system, this paper studies the problem of system energy efficiency maximization by joint optimization of computing time allocation, energy consumption, capacity of local computing and task offloading. A Tabu search based system energy efficiency maximization algorithm is proposed for solving the optimization problems. Finally, the performance of the proposed algorithm is valued by extensive simulation experiments. Simulation results verify the effectiveness of the proposed algorithm. Offloading optimization Time allocation Task offloading Mobile edge computing Song, Mingyang aut Zhang, Lei aut Chen, Weining aut Luo, Youlong aut Enthalten in Mobile networks and applications Springer US, 1996 27(2020), 5 vom: 09. Jan., Seite 1783-1791 (DE-627)215279522 (DE-600)1342049-5 (DE-576)063244756 1383-469X nnns volume:27 year:2020 number:5 day:09 month:01 pages:1783-1791 https://doi.org/10.1007/s11036-019-01396-3 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-MAT AR 27 2020 5 09 01 1783-1791 |
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Abstract This paper considers a wireless energy transfer based mobile edge computing system, where wireless devices can be charged by the radio-frequency signals broadcast by hybrid access point. With Mobile Edge Computing (MEC), wireless devices can execute their computation tasks locally or offload them to the MEC server by time division multiple access protocol. Based on this system, this paper studies the problem of system energy efficiency maximization by joint optimization of computing time allocation, energy consumption, capacity of local computing and task offloading. A Tabu search based system energy efficiency maximization algorithm is proposed for solving the optimization problems. Finally, the performance of the proposed algorithm is valued by extensive simulation experiments. Simulation results verify the effectiveness of the proposed algorithm. © Springer Science+Business Media, LLC, part of Springer Nature 2020 |
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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">OLC2079830090</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20230506081005.0</controlfield><controlfield tag="007">tu</controlfield><controlfield tag="008">230131s2020 xx ||||| 00| ||eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1007/s11036-019-01396-3</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)OLC2079830090</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-He213)s11036-019-01396-3-p</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="082" ind1="0" ind2="4"><subfield code="a">004</subfield><subfield code="q">VZ</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Li, Chunlin</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Offloading Optimization and Time Allocation for Multiuser Wireless Energy Transfer Based Mobile Edge Computing System</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2020</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">ohne Hilfsmittel zu benutzen</subfield><subfield code="b">n</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Band</subfield><subfield code="b">nc</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="500" ind1=" " ind2=" "><subfield code="a">© Springer Science+Business Media, LLC, part of Springer Nature 2020</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Abstract This paper considers a wireless energy transfer based mobile edge computing system, where wireless devices can be charged by the radio-frequency signals broadcast by hybrid access point. With Mobile Edge Computing (MEC), wireless devices can execute their computation tasks locally or offload them to the MEC server by time division multiple access protocol. Based on this system, this paper studies the problem of system energy efficiency maximization by joint optimization of computing time allocation, energy consumption, capacity of local computing and task offloading. A Tabu search based system energy efficiency maximization algorithm is proposed for solving the optimization problems. Finally, the performance of the proposed algorithm is valued by extensive simulation experiments. 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Jan., Seite 1783-1791</subfield><subfield code="w">(DE-627)215279522</subfield><subfield code="w">(DE-600)1342049-5</subfield><subfield code="w">(DE-576)063244756</subfield><subfield code="x">1383-469X</subfield><subfield code="7">nnns</subfield></datafield><datafield tag="773" ind1="1" ind2="8"><subfield code="g">volume:27</subfield><subfield code="g">year:2020</subfield><subfield code="g">number:5</subfield><subfield code="g">day:09</subfield><subfield code="g">month:01</subfield><subfield code="g">pages:1783-1791</subfield></datafield><datafield tag="856" ind1="4" ind2="1"><subfield code="u">https://doi.org/10.1007/s11036-019-01396-3</subfield><subfield code="z">lizenzpflichtig</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_USEFLAG_A</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SYSFLAG_A</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_OLC</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SSG-OLC-MAT</subfield></datafield><datafield tag="951" ind1=" " ind2=" "><subfield code="a">AR</subfield></datafield><datafield tag="952" ind1=" " ind2=" "><subfield code="d">27</subfield><subfield code="j">2020</subfield><subfield code="e">5</subfield><subfield code="b">09</subfield><subfield code="c">01</subfield><subfield code="h">1783-1791</subfield></datafield></record></collection>
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