Processor-Network Speed Scaling for Energy-Delay Tradeoff in Smartphone Applications
Many smartphone applications, e.g., file backup, are intrinsically delay-tolerant so that data processing and transfer can be delayed to reduce smartphone battery usage. In the literature, these energy-delay tradeoff issues have been addressed independently in the forms of Dynamic Voltage and Freque...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Kwak, Jeongho [verfasserIn] |
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| Format: |
Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2016 |
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| Schlagwörter: |
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| Übergeordnetes Werk: |
Enthalten in: IEEE ACM transactions on networking - New York, NY : IEEE, 1993, 24(2016), 3, Seite 1647-1660 |
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| Übergeordnetes Werk: |
volume:24 ; year:2016 ; number:3 ; pages:1647-1660 |
| Links: |
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| DOI / URN: |
10.1109/TNET.2015.2419219 |
|---|
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OLC197836637X |
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| 520 | |a Many smartphone applications, e.g., file backup, are intrinsically delay-tolerant so that data processing and transfer can be delayed to reduce smartphone battery usage. In the literature, these energy-delay tradeoff issues have been addressed independently in the forms of Dynamic Voltage and Frequency Scaling (DVFS) problems and network selection problems when smartphones have multiple wireless interfaces. In this paper, we jointly optimize the CPU speed and network speed to determine how much more energy can be saved through the joint optimization when applications can tolerate delays. We propose a dynamic speed scaling scheme called SpeedControl that jointly adjusts the processing and networking speeds using four controls: application scheduling, CPU speed control, wireless interface selection, and transmit power control. Through invoking the "Lyapunov drift-plus-penalty" technique, the scheme is demonstrated to be near optimal because it substantially reduces energy consumption for a given delay constraint. This paper is the first to reveal the energy-delay tradeoff relationship from a holistic perspective for smartphones with multiple wireless interfaces, DVFS, and multitasking capabilities. The trace-driven simulations based on real measurements of CPU power, network power, WiFi/3G throughput, and CPU workload demonstrate that SpeedControl can reduce battery usage by more than 42% through trading a 10 minutes delay when compared with the same delay in existing schemes; moreover, this energy conservation level increases as the WiFi coverage extends. | ||
| 650 | 4 | |a IEEE 802.11 Standards | |
| 650 | 4 | |a CPU speed scaling | |
| 650 | 4 | |a network interface selection | |
| 650 | 4 | |a Artificial neural networks | |
| 650 | 4 | |a heterogeneous wireless networks | |
| 650 | 4 | |a Delays | |
| 650 | 4 | |a energy-delay tradeoff | |
| 650 | 4 | |a multitasking | |
| 650 | 4 | |a Power demand | |
| 650 | 4 | |a transmit power control | |
| 650 | 4 | |a Wireless communication | |
| 650 | 4 | |a Network interfaces | |
| 650 | 4 | |a Power control | |
| 700 | 1 | |a Choi, Okyoung |4 oth | |
| 700 | 1 | |a Chong, Song |4 oth | |
| 700 | 1 | |a Mohapatra, Prasant |4 oth | |
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10.1109/TNET.2015.2419219 doi PQ20160719 (DE-627)OLC197836637X (DE-599)GBVOLC197836637X (PRQ)c953-99f5225ac72e83c1c32a511e7370653e4efbb9c2275e6b50978532ad9a51a6770 (KEY)0226258420160000024000301647processornetworkspeedscalingforenergydelaytradeoff DE-627 ger DE-627 rakwb eng 620 004 DNB 54.00 bkl 05.00 bkl Kwak, Jeongho verfasserin aut Processor-Network Speed Scaling for Energy-Delay Tradeoff in Smartphone Applications 2016 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier Many smartphone applications, e.g., file backup, are intrinsically delay-tolerant so that data processing and transfer can be delayed to reduce smartphone battery usage. In the literature, these energy-delay tradeoff issues have been addressed independently in the forms of Dynamic Voltage and Frequency Scaling (DVFS) problems and network selection problems when smartphones have multiple wireless interfaces. In this paper, we jointly optimize the CPU speed and network speed to determine how much more energy can be saved through the joint optimization when applications can tolerate delays. We propose a dynamic speed scaling scheme called SpeedControl that jointly adjusts the processing and networking speeds using four controls: application scheduling, CPU speed control, wireless interface selection, and transmit power control. Through invoking the "Lyapunov drift-plus-penalty" technique, the scheme is demonstrated to be near optimal because it substantially reduces energy consumption for a given delay constraint. This paper is the first to reveal the energy-delay tradeoff relationship from a holistic perspective for smartphones with multiple wireless interfaces, DVFS, and multitasking capabilities. The trace-driven simulations based on real measurements of CPU power, network power, WiFi/3G throughput, and CPU workload demonstrate that SpeedControl can reduce battery usage by more than 42% through trading a 10 minutes delay when compared with the same delay in existing schemes; moreover, this energy conservation level increases as the WiFi coverage extends. IEEE 802.11 Standards CPU speed scaling network interface selection Artificial neural networks heterogeneous wireless networks Delays energy-delay tradeoff multitasking Power demand transmit power control Wireless communication Network interfaces Power control Choi, Okyoung oth Chong, Song oth Mohapatra, Prasant oth Enthalten in IEEE ACM transactions on networking New York, NY : IEEE, 1993 24(2016), 3, Seite 1647-1660 (DE-627)165670215 (DE-600)1150634-9 (DE-576)034200843 1063-6692 nnns volume:24 year:2016 number:3 pages:1647-1660 http://dx.doi.org/10.1109/TNET.2015.2419219 Volltext http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=7091048 GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-TEC SSG-OLC-MAT GBV_ILN_70 GBV_ILN_151 GBV_ILN_2021 GBV_ILN_2190 GBV_ILN_4125 54.00 AVZ 05.00 AVZ AR 24 2016 3 1647-1660 |
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10.1109/TNET.2015.2419219 doi PQ20160719 (DE-627)OLC197836637X (DE-599)GBVOLC197836637X (PRQ)c953-99f5225ac72e83c1c32a511e7370653e4efbb9c2275e6b50978532ad9a51a6770 (KEY)0226258420160000024000301647processornetworkspeedscalingforenergydelaytradeoff DE-627 ger DE-627 rakwb eng 620 004 DNB 54.00 bkl 05.00 bkl Kwak, Jeongho verfasserin aut Processor-Network Speed Scaling for Energy-Delay Tradeoff in Smartphone Applications 2016 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier Many smartphone applications, e.g., file backup, are intrinsically delay-tolerant so that data processing and transfer can be delayed to reduce smartphone battery usage. In the literature, these energy-delay tradeoff issues have been addressed independently in the forms of Dynamic Voltage and Frequency Scaling (DVFS) problems and network selection problems when smartphones have multiple wireless interfaces. In this paper, we jointly optimize the CPU speed and network speed to determine how much more energy can be saved through the joint optimization when applications can tolerate delays. We propose a dynamic speed scaling scheme called SpeedControl that jointly adjusts the processing and networking speeds using four controls: application scheduling, CPU speed control, wireless interface selection, and transmit power control. Through invoking the "Lyapunov drift-plus-penalty" technique, the scheme is demonstrated to be near optimal because it substantially reduces energy consumption for a given delay constraint. This paper is the first to reveal the energy-delay tradeoff relationship from a holistic perspective for smartphones with multiple wireless interfaces, DVFS, and multitasking capabilities. The trace-driven simulations based on real measurements of CPU power, network power, WiFi/3G throughput, and CPU workload demonstrate that SpeedControl can reduce battery usage by more than 42% through trading a 10 minutes delay when compared with the same delay in existing schemes; moreover, this energy conservation level increases as the WiFi coverage extends. IEEE 802.11 Standards CPU speed scaling network interface selection Artificial neural networks heterogeneous wireless networks Delays energy-delay tradeoff multitasking Power demand transmit power control Wireless communication Network interfaces Power control Choi, Okyoung oth Chong, Song oth Mohapatra, Prasant oth Enthalten in IEEE ACM transactions on networking New York, NY : IEEE, 1993 24(2016), 3, Seite 1647-1660 (DE-627)165670215 (DE-600)1150634-9 (DE-576)034200843 1063-6692 nnns volume:24 year:2016 number:3 pages:1647-1660 http://dx.doi.org/10.1109/TNET.2015.2419219 Volltext http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=7091048 GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-TEC SSG-OLC-MAT GBV_ILN_70 GBV_ILN_151 GBV_ILN_2021 GBV_ILN_2190 GBV_ILN_4125 54.00 AVZ 05.00 AVZ AR 24 2016 3 1647-1660 |
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10.1109/TNET.2015.2419219 doi PQ20160719 (DE-627)OLC197836637X (DE-599)GBVOLC197836637X (PRQ)c953-99f5225ac72e83c1c32a511e7370653e4efbb9c2275e6b50978532ad9a51a6770 (KEY)0226258420160000024000301647processornetworkspeedscalingforenergydelaytradeoff DE-627 ger DE-627 rakwb eng 620 004 DNB 54.00 bkl 05.00 bkl Kwak, Jeongho verfasserin aut Processor-Network Speed Scaling for Energy-Delay Tradeoff in Smartphone Applications 2016 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier Many smartphone applications, e.g., file backup, are intrinsically delay-tolerant so that data processing and transfer can be delayed to reduce smartphone battery usage. In the literature, these energy-delay tradeoff issues have been addressed independently in the forms of Dynamic Voltage and Frequency Scaling (DVFS) problems and network selection problems when smartphones have multiple wireless interfaces. In this paper, we jointly optimize the CPU speed and network speed to determine how much more energy can be saved through the joint optimization when applications can tolerate delays. We propose a dynamic speed scaling scheme called SpeedControl that jointly adjusts the processing and networking speeds using four controls: application scheduling, CPU speed control, wireless interface selection, and transmit power control. Through invoking the "Lyapunov drift-plus-penalty" technique, the scheme is demonstrated to be near optimal because it substantially reduces energy consumption for a given delay constraint. This paper is the first to reveal the energy-delay tradeoff relationship from a holistic perspective for smartphones with multiple wireless interfaces, DVFS, and multitasking capabilities. The trace-driven simulations based on real measurements of CPU power, network power, WiFi/3G throughput, and CPU workload demonstrate that SpeedControl can reduce battery usage by more than 42% through trading a 10 minutes delay when compared with the same delay in existing schemes; moreover, this energy conservation level increases as the WiFi coverage extends. IEEE 802.11 Standards CPU speed scaling network interface selection Artificial neural networks heterogeneous wireless networks Delays energy-delay tradeoff multitasking Power demand transmit power control Wireless communication Network interfaces Power control Choi, Okyoung oth Chong, Song oth Mohapatra, Prasant oth Enthalten in IEEE ACM transactions on networking New York, NY : IEEE, 1993 24(2016), 3, Seite 1647-1660 (DE-627)165670215 (DE-600)1150634-9 (DE-576)034200843 1063-6692 nnns volume:24 year:2016 number:3 pages:1647-1660 http://dx.doi.org/10.1109/TNET.2015.2419219 Volltext http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=7091048 GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-TEC SSG-OLC-MAT GBV_ILN_70 GBV_ILN_151 GBV_ILN_2021 GBV_ILN_2190 GBV_ILN_4125 54.00 AVZ 05.00 AVZ AR 24 2016 3 1647-1660 |
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10.1109/TNET.2015.2419219 doi PQ20160719 (DE-627)OLC197836637X (DE-599)GBVOLC197836637X (PRQ)c953-99f5225ac72e83c1c32a511e7370653e4efbb9c2275e6b50978532ad9a51a6770 (KEY)0226258420160000024000301647processornetworkspeedscalingforenergydelaytradeoff DE-627 ger DE-627 rakwb eng 620 004 DNB 54.00 bkl 05.00 bkl Kwak, Jeongho verfasserin aut Processor-Network Speed Scaling for Energy-Delay Tradeoff in Smartphone Applications 2016 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier Many smartphone applications, e.g., file backup, are intrinsically delay-tolerant so that data processing and transfer can be delayed to reduce smartphone battery usage. In the literature, these energy-delay tradeoff issues have been addressed independently in the forms of Dynamic Voltage and Frequency Scaling (DVFS) problems and network selection problems when smartphones have multiple wireless interfaces. In this paper, we jointly optimize the CPU speed and network speed to determine how much more energy can be saved through the joint optimization when applications can tolerate delays. We propose a dynamic speed scaling scheme called SpeedControl that jointly adjusts the processing and networking speeds using four controls: application scheduling, CPU speed control, wireless interface selection, and transmit power control. Through invoking the "Lyapunov drift-plus-penalty" technique, the scheme is demonstrated to be near optimal because it substantially reduces energy consumption for a given delay constraint. This paper is the first to reveal the energy-delay tradeoff relationship from a holistic perspective for smartphones with multiple wireless interfaces, DVFS, and multitasking capabilities. The trace-driven simulations based on real measurements of CPU power, network power, WiFi/3G throughput, and CPU workload demonstrate that SpeedControl can reduce battery usage by more than 42% through trading a 10 minutes delay when compared with the same delay in existing schemes; moreover, this energy conservation level increases as the WiFi coverage extends. IEEE 802.11 Standards CPU speed scaling network interface selection Artificial neural networks heterogeneous wireless networks Delays energy-delay tradeoff multitasking Power demand transmit power control Wireless communication Network interfaces Power control Choi, Okyoung oth Chong, Song oth Mohapatra, Prasant oth Enthalten in IEEE ACM transactions on networking New York, NY : IEEE, 1993 24(2016), 3, Seite 1647-1660 (DE-627)165670215 (DE-600)1150634-9 (DE-576)034200843 1063-6692 nnns volume:24 year:2016 number:3 pages:1647-1660 http://dx.doi.org/10.1109/TNET.2015.2419219 Volltext http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=7091048 GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-TEC SSG-OLC-MAT GBV_ILN_70 GBV_ILN_151 GBV_ILN_2021 GBV_ILN_2190 GBV_ILN_4125 54.00 AVZ 05.00 AVZ AR 24 2016 3 1647-1660 |
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10.1109/TNET.2015.2419219 doi PQ20160719 (DE-627)OLC197836637X (DE-599)GBVOLC197836637X (PRQ)c953-99f5225ac72e83c1c32a511e7370653e4efbb9c2275e6b50978532ad9a51a6770 (KEY)0226258420160000024000301647processornetworkspeedscalingforenergydelaytradeoff DE-627 ger DE-627 rakwb eng 620 004 DNB 54.00 bkl 05.00 bkl Kwak, Jeongho verfasserin aut Processor-Network Speed Scaling for Energy-Delay Tradeoff in Smartphone Applications 2016 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier Many smartphone applications, e.g., file backup, are intrinsically delay-tolerant so that data processing and transfer can be delayed to reduce smartphone battery usage. In the literature, these energy-delay tradeoff issues have been addressed independently in the forms of Dynamic Voltage and Frequency Scaling (DVFS) problems and network selection problems when smartphones have multiple wireless interfaces. In this paper, we jointly optimize the CPU speed and network speed to determine how much more energy can be saved through the joint optimization when applications can tolerate delays. We propose a dynamic speed scaling scheme called SpeedControl that jointly adjusts the processing and networking speeds using four controls: application scheduling, CPU speed control, wireless interface selection, and transmit power control. Through invoking the "Lyapunov drift-plus-penalty" technique, the scheme is demonstrated to be near optimal because it substantially reduces energy consumption for a given delay constraint. This paper is the first to reveal the energy-delay tradeoff relationship from a holistic perspective for smartphones with multiple wireless interfaces, DVFS, and multitasking capabilities. The trace-driven simulations based on real measurements of CPU power, network power, WiFi/3G throughput, and CPU workload demonstrate that SpeedControl can reduce battery usage by more than 42% through trading a 10 minutes delay when compared with the same delay in existing schemes; moreover, this energy conservation level increases as the WiFi coverage extends. IEEE 802.11 Standards CPU speed scaling network interface selection Artificial neural networks heterogeneous wireless networks Delays energy-delay tradeoff multitasking Power demand transmit power control Wireless communication Network interfaces Power control Choi, Okyoung oth Chong, Song oth Mohapatra, Prasant oth Enthalten in IEEE ACM transactions on networking New York, NY : IEEE, 1993 24(2016), 3, Seite 1647-1660 (DE-627)165670215 (DE-600)1150634-9 (DE-576)034200843 1063-6692 nnns volume:24 year:2016 number:3 pages:1647-1660 http://dx.doi.org/10.1109/TNET.2015.2419219 Volltext http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=7091048 GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-TEC SSG-OLC-MAT GBV_ILN_70 GBV_ILN_151 GBV_ILN_2021 GBV_ILN_2190 GBV_ILN_4125 54.00 AVZ 05.00 AVZ AR 24 2016 3 1647-1660 |
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Processor-Network Speed Scaling for Energy-Delay Tradeoff in Smartphone Applications |
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Many smartphone applications, e.g., file backup, are intrinsically delay-tolerant so that data processing and transfer can be delayed to reduce smartphone battery usage. In the literature, these energy-delay tradeoff issues have been addressed independently in the forms of Dynamic Voltage and Frequency Scaling (DVFS) problems and network selection problems when smartphones have multiple wireless interfaces. In this paper, we jointly optimize the CPU speed and network speed to determine how much more energy can be saved through the joint optimization when applications can tolerate delays. We propose a dynamic speed scaling scheme called SpeedControl that jointly adjusts the processing and networking speeds using four controls: application scheduling, CPU speed control, wireless interface selection, and transmit power control. Through invoking the "Lyapunov drift-plus-penalty" technique, the scheme is demonstrated to be near optimal because it substantially reduces energy consumption for a given delay constraint. This paper is the first to reveal the energy-delay tradeoff relationship from a holistic perspective for smartphones with multiple wireless interfaces, DVFS, and multitasking capabilities. The trace-driven simulations based on real measurements of CPU power, network power, WiFi/3G throughput, and CPU workload demonstrate that SpeedControl can reduce battery usage by more than 42% through trading a 10 minutes delay when compared with the same delay in existing schemes; moreover, this energy conservation level increases as the WiFi coverage extends. |
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Many smartphone applications, e.g., file backup, are intrinsically delay-tolerant so that data processing and transfer can be delayed to reduce smartphone battery usage. In the literature, these energy-delay tradeoff issues have been addressed independently in the forms of Dynamic Voltage and Frequency Scaling (DVFS) problems and network selection problems when smartphones have multiple wireless interfaces. In this paper, we jointly optimize the CPU speed and network speed to determine how much more energy can be saved through the joint optimization when applications can tolerate delays. We propose a dynamic speed scaling scheme called SpeedControl that jointly adjusts the processing and networking speeds using four controls: application scheduling, CPU speed control, wireless interface selection, and transmit power control. Through invoking the "Lyapunov drift-plus-penalty" technique, the scheme is demonstrated to be near optimal because it substantially reduces energy consumption for a given delay constraint. This paper is the first to reveal the energy-delay tradeoff relationship from a holistic perspective for smartphones with multiple wireless interfaces, DVFS, and multitasking capabilities. The trace-driven simulations based on real measurements of CPU power, network power, WiFi/3G throughput, and CPU workload demonstrate that SpeedControl can reduce battery usage by more than 42% through trading a 10 minutes delay when compared with the same delay in existing schemes; moreover, this energy conservation level increases as the WiFi coverage extends. |
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Many smartphone applications, e.g., file backup, are intrinsically delay-tolerant so that data processing and transfer can be delayed to reduce smartphone battery usage. In the literature, these energy-delay tradeoff issues have been addressed independently in the forms of Dynamic Voltage and Frequency Scaling (DVFS) problems and network selection problems when smartphones have multiple wireless interfaces. In this paper, we jointly optimize the CPU speed and network speed to determine how much more energy can be saved through the joint optimization when applications can tolerate delays. We propose a dynamic speed scaling scheme called SpeedControl that jointly adjusts the processing and networking speeds using four controls: application scheduling, CPU speed control, wireless interface selection, and transmit power control. Through invoking the "Lyapunov drift-plus-penalty" technique, the scheme is demonstrated to be near optimal because it substantially reduces energy consumption for a given delay constraint. This paper is the first to reveal the energy-delay tradeoff relationship from a holistic perspective for smartphones with multiple wireless interfaces, DVFS, and multitasking capabilities. The trace-driven simulations based on real measurements of CPU power, network power, WiFi/3G throughput, and CPU workload demonstrate that SpeedControl can reduce battery usage by more than 42% through trading a 10 minutes delay when compared with the same delay in existing schemes; moreover, this energy conservation level increases as the WiFi coverage extends. |
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Processor-Network Speed Scaling for Energy-Delay Tradeoff in Smartphone Applications |
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