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001 978-3-031-02475-7
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007 cr nn 008mamaa
008 220601s2007 sz | s |||| 0|eng d
020 _a9783031024757
_9978-3-031-02475-7
024 7 _a10.1007/978-3-031-02475-7
_2doi
050 4 _aQA1-939
072 7 _aPB
_2bicssc
072 7 _aMAT000000
_2bisacsh
072 7 _aPB
_2thema
082 0 4 _a510
_223
100 1 _aEllis, Carla Schlatter.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_978795
245 1 0 _aControlling Energy Demand in Mobile Computing Systems
_h[electronic resource] /
_cby Carla Schlatter Ellis.
250 _a1st ed. 2007.
264 1 _aCham :
_bSpringer International Publishing :
_bImprint: Springer,
_c2007.
300 _aVIII, 89 p.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aSynthesis Lectures on Mobile & Pervasive Computing,
_x1933-902X
505 0 _aIntroduction -- System Energy Models and Metrics -- Management of Device Power States -- Dynamic Voltage Scheduling (DVS) -- Multiple Devices-Interactions and Tradeoffs -- Energy-Aware Application Code -- Challenges and Opportunities.
520 _aThis lecture provides an introduction to the problem of managing the energy demand of mobile devices. Reducing energy consumption, primarily with the goal of extending the lifetime of battery-powered devices, has emerged as a fundamental challenge in mobile computing and wireless communication. The focus of this lecture is on a systems approach where software techniques exploit state-of-the-art architectural features rather than relying only upon advances in lower-power circuitry or the slow improvements in battery technology to solve the problem. Fortunately, there are many opportunities to innovate on managing energy demand at the higher levels of a mobile system. Increasingly, device components offer low power modes that enable software to directly affect the energy consumption of the system. The challenge is to design resource management policies to effectively use these capabilities. The lecture begins by providing the necessary foundations, including basic energy terminology andwidely accepted metrics, system models of how power is consumed by a device, and measurement methods and tools available for experimental evaluation. For components that offer low power modes, management policies are considered that address the questions of when to power down to a lower power state and when to power back up to a higher power state. These policies rely on detecting periods when the device is idle as well as techniques for modifying the access patterns of a workload to increase opportunities for power state transitions. For processors with frequency and voltage scaling capabilities, dynamic scheduling policies are developed that determine points during execution when those settings can be changed without harming quality of service constraints. The interactions and tradeoffs among the power management policies of multiple devices are discussed. We explore how the effective power management on one component of a system may have either a positive or negative impact on overall energy consumption or on the design of policies for another component. The important role that application-level involvement may play in energy management is described, with several examples of cross-layer cooperation. Application program interfaces (APIs) that provide information flow across the application-OS boundary are valuable tools in encouraging development of energy-aware applications. Finally, we summarize the key lessons of this lecture and discuss future directions in managing energy demand.
650 0 _aMathematics.
_911584
650 0 _aEngineering.
_99405
650 0 _aMobile computing.
_93438
650 0 _aCooperating objects (Computer systems).
_96195
650 0 _aUser interfaces (Computer systems).
_911681
650 0 _aHuman-computer interaction.
_96196
650 1 4 _aMathematics.
_911584
650 2 4 _aTechnology and Engineering.
_978796
650 2 4 _aMobile Computing.
_93438
650 2 4 _aCyber-Physical Systems.
_932475
650 2 4 _aUser Interfaces and Human Computer Interaction.
_931632
710 2 _aSpringerLink (Online service)
_978797
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9783031013478
776 0 8 _iPrinted edition:
_z9783031036033
830 0 _aSynthesis Lectures on Mobile & Pervasive Computing,
_x1933-902X
_978798
856 4 0 _uhttps://doi.org/10.1007/978-3-031-02475-7
912 _aZDB-2-SXSC
942 _cEBK
999 _c84659
_d84659