Deriving a Generic Energy Consumption Model for Network Enabled Devices

Varsha Jain, Gerard Parr, David Bustard, Philip Morrow

Research output: Chapter in Book/Report/Conference proceedingConference contribution

5 Citations (Scopus)

Abstract

Energy saving has become a global issue when people use network enabled equipment in the office or at home. However few methods exist to measure and monitor energy use per user or per application, or to control equipment power states. We propose a generic energy consumption model that is based on the power state of network attached equipment, and that supports power management capabilities. This includes measures for each power state (on/off/sleep) and for per bit energy consumption, per interface, per application and at the network QoS (Quality of Services) level. Given the power state of a network device, a network manger could remotely inspect the energy consumption and make changes to the power management setting; for this to happen we introduce a new MIB (Management Information Base) schema to capture the attributes of relevance. Using an agent based modeling framework, we introduce the overall autonomic architecture that makes it possible to minimize energy consumption of network enabled equipment.
LanguageEnglish
Title of host publicationUnknown Host Publication
Number of pages5
DOIs
Publication statusPublished - 15 Mar 2010
EventNational Conference on Communications -
Duration: 15 Mar 2010 → …

Conference

ConferenceNational Conference on Communications
Period15/03/10 → …

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Energy utilization
Control equipment
Information management
Energy conservation
Quality of service
Power management

Keywords

  • power management
  • Energy Aware MIB
  • SNMP
  • energy efficiency
  • generic energy consumption.

Cite this

Jain, Varsha ; Parr, Gerard ; Bustard, David ; Morrow, Philip. / Deriving a Generic Energy Consumption Model for Network Enabled Devices. Unknown Host Publication. 2010.
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abstract = "Energy saving has become a global issue when people use network enabled equipment in the office or at home. However few methods exist to measure and monitor energy use per user or per application, or to control equipment power states. We propose a generic energy consumption model that is based on the power state of network attached equipment, and that supports power management capabilities. This includes measures for each power state (on/off/sleep) and for per bit energy consumption, per interface, per application and at the network QoS (Quality of Services) level. Given the power state of a network device, a network manger could remotely inspect the energy consumption and make changes to the power management setting; for this to happen we introduce a new MIB (Management Information Base) schema to capture the attributes of relevance. Using an agent based modeling framework, we introduce the overall autonomic architecture that makes it possible to minimize energy consumption of network enabled equipment.",
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author = "Varsha Jain and Gerard Parr and David Bustard and Philip Morrow",
note = "Reference text: [1] SMART 2020 Report, “Enabling the low carbon economy in the information age”, Nov 2008. http://www.theclimategroup.org/assets/resources/publications/Smart2020Report.pdf [2] RISO Inc, “Hidden costs of Copiers and Printers,” Report, Jan 2009. https://us.riso.com [3] European Commission Join Research Centre, “Code of conduct on energy consumption of broadband equipment” Version 3, Nov 2009. http://re.jrc.ec.europa.eu/energyefficiency/pdf/CoC{\%}20Brodband{\%}20Equipment/Code{\%}20of{\%}20Conduct{\%}20Broadband{\%}20Equipment{\%}20V3{\%}20final.pdf [4] J. Baliga, et al., “Photonic switching and the energy bottleneck,” Proc. IEEE Photonics in Switching, pp. 125-126, Aug 2007. [5] L. Benini, A. Bogliolo, G.A. Paleologo and G. De Micheli, “Policy optimization for dynamic power management,” IEEE Trans. On Computer-Aided Design, Vol. 18, No. 6 (1999), pages 813-833. [6] Advanced Configuration and Power Interface Specification, Revision 4.0, June 16, 2009. http://www.acpi.info/DOWNLOADS/ACPIspec40.pdf [7] J. Quittek, “Requirement for Power Monitoring”, Internet-Draft, Oct 2009. http://tools.ietf.org/pdf/draft-quittek-power-monitoring-requirements-00.pdf. [8] C. Harris and V. Cahill, “Exploiting user behaviour for context-aware power management,” In International Conference on Wireless and Mobile Computing, Networking and Communications, Montreal, Canada, vol. 4, pp. 122-130, August 2005. [9] G. Theocharous, S. Mannor, N. Shah, P. Gandhi, B. Kveton,S. Siddiqi, and C-H. Yu, “Machine learning for adaptive power management,” Intel Technology Journal, Vol. 10, pp. 299-312, November 2006. [10] M. Gupta, “Using low-power modes for energy conservation in ethernet LANs”, IEEE INFOCOM, pp. 2451-2455, May 2007. [11] M. Gupta, “Dynamic ethernet link shutdown for energy conservation on ethernet links”, IEEE ICC, pp. 6156-6161, Jun 2007. [12] M. Gupta, “A feasibility study for power management in LAN switches”, IEEE ICNP, pp. 361-371, Oct. 2004. [13] Berger and D. Romascanu, “Power Ethernet MIB”, RFC 3621, December 2003. [14] F. Blanquicet and K. Christensen, {"}Managing energy use in a network with a new SNMP power state MIB,{"} Proceedings of the IEEE Conference on Local Computer Networks, pp. 509-511, October 2008. [15] P. Mahadevan, P. Sharma, S. Banerjee, and P. Ranganathan, “A power benchmarking framework for network devices,” in Proceedings of IFIP Networking ,pp. 795-808, May 2009. [16] Ying Tan, Qinru Qiu, {"}A framework of stochastic power management using hidden markov model,{"} Design, Automation and Test in Europe (DATE 08), pp. 92-97, 2008. [17] Steven Latr{\'e}, Pieter Simoens a, Bart De Vleeschauwer, “Design for a Generic Knowledge Base for Autonomic QoE Optimization in Multimedia Access Networks, “IEEE NOMOS Workshop, pp.335-342, April 2008.",
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Jain, V, Parr, G, Bustard, D & Morrow, P 2010, Deriving a Generic Energy Consumption Model for Network Enabled Devices. in Unknown Host Publication. National Conference on Communications, 15/03/10. https://doi.org/10.1109/NCC.2010.5430165

Deriving a Generic Energy Consumption Model for Network Enabled Devices. / Jain, Varsha; Parr, Gerard; Bustard, David; Morrow, Philip.

Unknown Host Publication. 2010.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

TY - GEN

T1 - Deriving a Generic Energy Consumption Model for Network Enabled Devices

AU - Jain, Varsha

AU - Parr, Gerard

AU - Bustard, David

AU - Morrow, Philip

N1 - Reference text: [1] SMART 2020 Report, “Enabling the low carbon economy in the information age”, Nov 2008. http://www.theclimategroup.org/assets/resources/publications/Smart2020Report.pdf [2] RISO Inc, “Hidden costs of Copiers and Printers,” Report, Jan 2009. https://us.riso.com [3] European Commission Join Research Centre, “Code of conduct on energy consumption of broadband equipment” Version 3, Nov 2009. http://re.jrc.ec.europa.eu/energyefficiency/pdf/CoC%20Brodband%20Equipment/Code%20of%20Conduct%20Broadband%20Equipment%20V3%20final.pdf [4] J. Baliga, et al., “Photonic switching and the energy bottleneck,” Proc. IEEE Photonics in Switching, pp. 125-126, Aug 2007. [5] L. Benini, A. Bogliolo, G.A. Paleologo and G. De Micheli, “Policy optimization for dynamic power management,” IEEE Trans. On Computer-Aided Design, Vol. 18, No. 6 (1999), pages 813-833. [6] Advanced Configuration and Power Interface Specification, Revision 4.0, June 16, 2009. http://www.acpi.info/DOWNLOADS/ACPIspec40.pdf [7] J. Quittek, “Requirement for Power Monitoring”, Internet-Draft, Oct 2009. http://tools.ietf.org/pdf/draft-quittek-power-monitoring-requirements-00.pdf. [8] C. Harris and V. Cahill, “Exploiting user behaviour for context-aware power management,” In International Conference on Wireless and Mobile Computing, Networking and Communications, Montreal, Canada, vol. 4, pp. 122-130, August 2005. [9] G. Theocharous, S. Mannor, N. Shah, P. Gandhi, B. Kveton,S. Siddiqi, and C-H. Yu, “Machine learning for adaptive power management,” Intel Technology Journal, Vol. 10, pp. 299-312, November 2006. [10] M. Gupta, “Using low-power modes for energy conservation in ethernet LANs”, IEEE INFOCOM, pp. 2451-2455, May 2007. [11] M. Gupta, “Dynamic ethernet link shutdown for energy conservation on ethernet links”, IEEE ICC, pp. 6156-6161, Jun 2007. [12] M. Gupta, “A feasibility study for power management in LAN switches”, IEEE ICNP, pp. 361-371, Oct. 2004. [13] Berger and D. Romascanu, “Power Ethernet MIB”, RFC 3621, December 2003. [14] F. Blanquicet and K. Christensen, "Managing energy use in a network with a new SNMP power state MIB," Proceedings of the IEEE Conference on Local Computer Networks, pp. 509-511, October 2008. [15] P. Mahadevan, P. Sharma, S. Banerjee, and P. Ranganathan, “A power benchmarking framework for network devices,” in Proceedings of IFIP Networking ,pp. 795-808, May 2009. [16] Ying Tan, Qinru Qiu, "A framework of stochastic power management using hidden markov model," Design, Automation and Test in Europe (DATE 08), pp. 92-97, 2008. [17] Steven Latré, Pieter Simoens a, Bart De Vleeschauwer, “Design for a Generic Knowledge Base for Autonomic QoE Optimization in Multimedia Access Networks, “IEEE NOMOS Workshop, pp.335-342, April 2008.

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N2 - Energy saving has become a global issue when people use network enabled equipment in the office or at home. However few methods exist to measure and monitor energy use per user or per application, or to control equipment power states. We propose a generic energy consumption model that is based on the power state of network attached equipment, and that supports power management capabilities. This includes measures for each power state (on/off/sleep) and for per bit energy consumption, per interface, per application and at the network QoS (Quality of Services) level. Given the power state of a network device, a network manger could remotely inspect the energy consumption and make changes to the power management setting; for this to happen we introduce a new MIB (Management Information Base) schema to capture the attributes of relevance. Using an agent based modeling framework, we introduce the overall autonomic architecture that makes it possible to minimize energy consumption of network enabled equipment.

AB - Energy saving has become a global issue when people use network enabled equipment in the office or at home. However few methods exist to measure and monitor energy use per user or per application, or to control equipment power states. We propose a generic energy consumption model that is based on the power state of network attached equipment, and that supports power management capabilities. This includes measures for each power state (on/off/sleep) and for per bit energy consumption, per interface, per application and at the network QoS (Quality of Services) level. Given the power state of a network device, a network manger could remotely inspect the energy consumption and make changes to the power management setting; for this to happen we introduce a new MIB (Management Information Base) schema to capture the attributes of relevance. Using an agent based modeling framework, we introduce the overall autonomic architecture that makes it possible to minimize energy consumption of network enabled equipment.

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KW - Energy Aware MIB

KW - SNMP

KW - energy efficiency

KW - generic energy consumption.

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DO - 10.1109/NCC.2010.5430165

M3 - Conference contribution

SN - 978-1-4244-6383-1 (print)

BT - Unknown Host Publication

ER -