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MEERA: cross-layer methodology for energy efficient resource allocation in wireless networks
In many portable devices, wireless network interfaces consume upwards of 30% of scarce system energy. Reducing the transceiver's power consumption to extend the system lifetime has therefore become a design goal. Our work is targeted at this goal and is based on the following two observations....
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Published in: | IEEE transactions on wireless communications 2007-02, Vol.6 (2), p.617-628 |
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description | In many portable devices, wireless network interfaces consume upwards of 30% of scarce system energy. Reducing the transceiver's power consumption to extend the system lifetime has therefore become a design goal. Our work is targeted at this goal and is based on the following two observations. First, conventional energy management approaches have focused independently on minimizing the fixed energy cost (by shutdown) and on scalable energy costs (by leveraging, for example, the modulation, code-rate and transmission power). These two energy management approaches present a tradeoff. For example, lower modulation rates and transmission power minimize the variable energy component, but this shortens the sleep duration thereby increasing fixed energy consumption. Second, in order to meet the quality of service (QoS) timeliness requirements for multiple users, we need to determine to what extent each system in the network may sleep and scale. Therefore, we propose a two-phase methodology that resolves the sleep-scaling tradeoff across the physical, communications and link layers at design time and schedules nodes at runtime with near optimal energy-efficient configurations in the solution space. As a result, we are able to achieve very low run-time overheads. Our methodology is applied to a case study on delivering a guaranteed QoS for multiple users with MPEG-4 video over a slow-fading channel. By exploiting runtime controllable parameters of actual RF components and a modified 802.11 medium access controller, system lifetime is increased by a factor of 3-to-10 in comparison with conventional techniques |
doi_str_mv | 10.1109/TWC.2007.05356 |
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Reducing the transceiver's power consumption to extend the system lifetime has therefore become a design goal. Our work is targeted at this goal and is based on the following two observations. First, conventional energy management approaches have focused independently on minimizing the fixed energy cost (by shutdown) and on scalable energy costs (by leveraging, for example, the modulation, code-rate and transmission power). These two energy management approaches present a tradeoff. For example, lower modulation rates and transmission power minimize the variable energy component, but this shortens the sleep duration thereby increasing fixed energy consumption. Second, in order to meet the quality of service (QoS) timeliness requirements for multiple users, we need to determine to what extent each system in the network may sleep and scale. Therefore, we propose a two-phase methodology that resolves the sleep-scaling tradeoff across the physical, communications and link layers at design time and schedules nodes at runtime with near optimal energy-efficient configurations in the solution space. As a result, we are able to achieve very low run-time overheads. Our methodology is applied to a case study on delivering a guaranteed QoS for multiple users with MPEG-4 video over a slow-fading channel. 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Therefore, we propose a two-phase methodology that resolves the sleep-scaling tradeoff across the physical, communications and link layers at design time and schedules nodes at runtime with near optimal energy-efficient configurations in the solution space. As a result, we are able to achieve very low run-time overheads. Our methodology is applied to a case study on delivering a guaranteed QoS for multiple users with MPEG-4 video over a slow-fading channel. By exploiting runtime controllable parameters of actual RF components and a modified 802.11 medium access controller, system lifetime is increased by a factor of 3-to-10 in comparison with conventional techniques</description><subject>Applied sciences</subject><subject>Business and industry local networks</subject><subject>Control systems</subject><subject>Costs</subject><subject>Energy consumption</subject><subject>Energy costs</subject><subject>Energy efficiency</subject><subject>Energy management</subject><subject>Exact sciences and technology</subject><subject>Methodology</subject><subject>Modulation</subject><subject>Networks</subject><subject>Networks and services in france and abroad</subject><subject>Operation, maintenance, reliability</subject><subject>Quality of service</subject><subject>Radiocommunications</subject><subject>Resource management</subject><subject>Runtime</subject><subject>Sleep</subject><subject>Studies</subject><subject>Systems, networks and services of telecommunications</subject><subject>Telecommunications</subject><subject>Telecommunications and information theory</subject><subject>Teleprocessing networks. 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Receivers</topic><topic>Wireless communication</topic><topic>Wireless networks</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Pollin, S.</creatorcontrib><creatorcontrib>Mangharam, R.</creatorcontrib><creatorcontrib>Bougard, B.</creatorcontrib><creatorcontrib>Van der Perre, L.</creatorcontrib><creatorcontrib>Moerman, I.</creatorcontrib><creatorcontrib>Rajkumar, R.</creatorcontrib><creatorcontrib>Catthoor, F.</creatorcontrib><collection>IEEE All-Society Periodicals Package (ASPP) 2005-present</collection><collection>IEEE All-Society Periodicals Package (ASPP) 1998-Present</collection><collection>IEEE Electronic Library Online</collection><collection>Pascal-Francis</collection><collection>CrossRef</collection><collection>Computer and Information Systems Abstracts</collection><collection>Electronics & Communications Abstracts</collection><collection>Technology Research Database</collection><collection>ProQuest Computer Science Collection</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts – Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><collection>ANTE: Abstracts in New Technology & Engineering</collection><collection>Engineering Research Database</collection><jtitle>IEEE transactions on wireless communications</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Pollin, S.</au><au>Mangharam, R.</au><au>Bougard, B.</au><au>Van der Perre, L.</au><au>Moerman, I.</au><au>Rajkumar, R.</au><au>Catthoor, F.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>MEERA: cross-layer methodology for energy efficient resource allocation in wireless networks</atitle><jtitle>IEEE transactions on wireless communications</jtitle><stitle>TWC</stitle><date>2007-02-01</date><risdate>2007</risdate><volume>6</volume><issue>2</issue><spage>617</spage><epage>628</epage><pages>617-628</pages><issn>1536-1276</issn><eissn>1558-2248</eissn><coden>ITWCAX</coden><abstract>In many portable devices, wireless network interfaces consume upwards of 30% of scarce system energy. 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subjects | Applied sciences Business and industry local networks Control systems Costs Energy consumption Energy costs Energy efficiency Energy management Exact sciences and technology Methodology Modulation Networks Networks and services in france and abroad Operation, maintenance, reliability Quality of service Radiocommunications Resource management Runtime Sleep Studies Systems, networks and services of telecommunications Telecommunications Telecommunications and information theory Teleprocessing networks. Isdn Transmission and modulation (techniques and equipments) Transmitters. Receivers Wireless communication Wireless networks |
title | MEERA: cross-layer methodology for energy efficient resource allocation in wireless networks |
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