Classifications

• • G—PHYSICS
  • G06—COMPUTING; CALCULATING OR COUNTING
  • G06F—ELECTRIC DIGITAL DATA PROCESSING
  • G06F1/00—Details not covered by groups G06F3/00 - G06F13/00 and G06F21/00
  • G06F1/26—Power supply means, e.g. regulation thereof
  • G06F1/32—Means for saving power
  • G06F1/3203—Power management, i.e. event-based initiation of a power-saving mode
• • G—PHYSICS
  • G06—COMPUTING; CALCULATING OR COUNTING
  • G06F—ELECTRIC DIGITAL DATA PROCESSING
  • G06F1/00—Details not covered by groups G06F3/00 - G06F13/00 and G06F21/00
  • G06F1/26—Power supply means, e.g. regulation thereof
  • G06F1/32—Means for saving power
• • G—PHYSICS
  • G06—COMPUTING; CALCULATING OR COUNTING
  • G06F—ELECTRIC DIGITAL DATA PROCESSING
  • G06F1/00—Details not covered by groups G06F3/00 - G06F13/00 and G06F21/00
  • G06F1/26—Power supply means, e.g. regulation thereof
  • G06F1/32—Means for saving power
  • G06F1/3203—Power management, i.e. event-based initiation of a power-saving mode
  • G06F1/3234—Power saving characterised by the action undertaken
  • G06F1/324—Power saving characterised by the action undertaken by lowering clock frequency
• • H—ELECTRICITY
  • H04—ELECTRIC COMMUNICATION TECHNIQUE
  • H04M—TELEPHONIC COMMUNICATION
  • H04M1/00—Substation equipment, e.g. for use by subscribers
  • H04M1/72—Mobile telephones; Cordless telephones, i.e. devices for establishing wireless links to base stations without route selection
  • H04M1/725—Cordless telephones
  • H04M1/73—Battery saving arrangements
• • H—ELECTRICITY
  • H04—ELECTRIC COMMUNICATION TECHNIQUE
  • H04W—WIRELESS COMMUNICATION NETWORKS
  • H04W52/00—Power management, e.g. TPC [Transmission Power Control], power saving or power classes
  • H04W52/02—Power saving arrangements
  • H04W52/0209—Power saving arrangements in terminal devices
  • H04W52/0251—Power saving arrangements in terminal devices using monitoring of local events, e.g. events related to user activity
  • H04W52/0258—Power saving arrangements in terminal devices using monitoring of local events, e.g. events related to user activity controlling an operation mode according to history or models of usage information, e.g. activity schedule or time of day
• • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
  • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
  • Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
  • Y02D10/00—Energy efficient computing, e.g. low power processors, power management or thermal management
• • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
  • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
  • Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
  • Y02D30/00—Reducing energy consumption in communication networks
  • Y02D30/70—Reducing energy consumption in communication networks in wireless communication networks

Definitions

• the present invention relates to an apparatus such as, for example, a computing device, and to a method of managing power consumption in such an apparatus
• an apparatus comprising: an event monitor for observing events occurring within the apparatus, and a prediction component, wherein the prediction component is configured to cause an operating parameter associated with the power consumption of the apparatus to change if a sequence of events observed by the event monitor corresponds to a pre-defined sequence associated with the change in the operating parameter.
• an apparatus comprising: at least one processor; and at least one memory including computer program code, the at least one memory and the computer program code configured to, with the at least one processor, cause the apparatus to perform at least the following: manage power consumption in the apparatus, by: observing events occurring in the apparatus and changing an operating parameter of the apparatus associated with the power consumption of the apparatus if an observed sequence of events corresponds to a pre-defined sequence of events associated with the change in the operating parameter.
• a method comprising: managing power consumption in an apparatus, including: observing events occurring in the apparatus and changing an operating parameter of the apparatus associated with the power consumption of the apparatus if an observed sequence of events corresponds to a pre-defined sequence of events associated with the change in the operating parameter.
• FIGURE 1 is a schematic illustration showing selected elements of a mobile telephone in accordance with a second example embodiment of the present invention
• FIGURE 2 is a block flow diagram illustrating the operation of a load monitor in the second example embodiment
• FIGURE 3 is a block flow diagram illustrating the operation of a learning component in the second example embodiment
• FIGURE 4 is a block flow diagram illustrating the operation of a prediction component in the second example embodiment.
• FIGURE 5 is a block diagram illustrating a computer readable medium having code modules stored thereon to implement the components of the second example embodiment.
• Such systems typically adopt one of two approaches.
• applications used by the computing device register their performance requirements, such that the device can determine the overall performance requirements and adjust the operating frequency of the processor accordingly.
• applications are designed or adapted to comply with the particular performance requirement reporting system used by the device, which adds to the complexity of the applications.
• different devices may have different performance requirement reporting systems, meaning that different versions of the same application must be produced for compatibility with the different devices.
• the second approach is to monitor the load on the processor of the device, and to adjust the operating frequency of the processor to its lowest possible value, without overloading it, in response to a change in the demand placed on the processor.
• the adjustment to the operating frequency of the processor lags behind the change in the load on the processor that caused the adjustment.
• the processor is overloaded until the increase in its operating frequency is effected, resulting in a temporary loss of performance. If the load on the processor decreases, the processor will run at a higher frequency than is necessary until the change in operating frequency is effected, resulting in a temporary waste of energy.
• a first example embodiment of the invention takes a different approach from the above, and in particular is directed at monitoring sequences of events in a computing device, and changing an operating parameter of the computing device if a monitored sequence of events corresponds to a pre-determined sequence of events taken from a set of such predetermined sequences, the pre-determined sequences of events having operating parameter changes respectively associated therewith.
• a particular sequence of events that may occur may have associated therewith an operating parameter change in the form of an increase in processor speed.
• the operating parameter change in the form of the increase in processor speed is implemented. In this way, in this example the required desirable operating parameters of the computing device can be predicted and the operating parameters adjusted thereto based on monitored sequences of events.
• a computing device comprising an event monitor for observing events occurring within the computing device.
• a prediction component is also provided in this example within the computing device, the prediction component being configured to cause an operating parameter associated with the power consumption of the computing device to change if a sequence of events observed by the event monitor corresponds to a pre-defined sequence.
• the pre-defined sequence is associated with the change in the operating parameter that occurs.
• the prediction component of the present invention is able to predict, based on the events observed by the event monitor, when the operating parameters of the computing device will need to change to meet changing power requirements. For example, the operating parameter associated with the power consumption of the device can then be changed in a timely fashion to ensure that any loss of performance as a result of the change is minimised, whilst also minimising unnecessary power consumption.
• the computing device may further comprise a learning component which is configured to learn the pre-defined sequence of events associated with the change in the operating parameter.
• the learning component may be associated with the event monitor and may be configured to make a prediction relating to the operating parameter if a sequence of events observed by the event monitor corresponds to a sequence previously recorded by the learning component.
• the computing device may further comprise a processor load monitor
• the learning component may for example be configured to verify its prediction by examining the processor load monitor after the sequence of events recorded by the learning component has occurred.
• the recorded sequence of events may be associated with a score, which score is changed if the prediction was correct.
• the prediction component may be configured to store the recorded sequence of events as a pre-defined sequence if the score reaches a predetermined threshold.
• the learning component is able to learn which sequences of events are likely to give rise to changes in the operating parameter associated with the power consumption of the device, and the prediction component is able to store these sequences of events, and the associated changes in the operating parameter, for future use, to reduce the power consumption by pre-emptively changing the operating parameter in response to the sequences of events.
• the learning component may be configured to record a sequence of events observed by the event monitor if the observed sequence of events does not correspond to a sequence previously recorded by the learning component. For example, new sequences of events which may give rise to a change in the operating parameter of the device can be learned.
• the operating parameter may comprise an operating frequency of a processor of the computing device. That is, for example, the operating frequency may be changed so as to be higher, for example when the processing load on the device is predicted, via the monitored sequence of events, to be larger, or may be changed so as to be lower, for example when the processing load on the device is predicted, via the monitored sequence of events, to be smaller.
• the computing device may be a symmetric multi-processor device and the operating parameter may comprise the number of processors that are enabled.
• the computing device may be a heterogeneous multi-processor device and the operating parameter may comprise the type of processors that are enabled.
• the computing device is a mobile telephone.
• the computing device may be any other computing device such as a desktop computer, laptop computer, personal digital assistant (PDA), MP3 player, portable video player, digital camera, and the like.
• PDA personal digital assistant
• MP3 player portable video player
• digital camera digital camera
• a portable computing device in this example a mobile telephone, is shown generally at 10.
• the mobile telephone 10 comprises additional elements and components.
• the mobile telephone 10 illustrated in Figure 1 is only one example of a computing device in which examples of the present invention can be implemented, and that examples of the present invention are equally applicable to other computing devices such as desktop computers, laptop computers, personal digital assistants (PDAs) and the like.
• PDAs personal digital assistants
• the mobile telephone 10 comprises one or more processors 12 for handling application software which runs on the device, such as, for example, a media player, web browser, organiser, games and the like, as well as an operating system of the mobile telephone 10.
• a processor load monitor 14 is provided to monitor the load on the processor(s) 12 (B.2.2).
• the processor load monitor 14 in this example reports the load on the processor(s) 12 to a controller 16 (B.2.4) which in this example is configured to control an operating parameter of the mobile telephone 10 (B.2.6) which affects the power consumption of the mobile telephone 10.
• the controller 16 may control the operating frequency of the processor 12 in a single-processor device, or may in another example control the number of processors 12 that are enabled in a symmetric multi-processor device, or may in a further example control the type of processors 12 that are enabled in a heterogeneous multi-processor device.
• the controller 16 also reports the operating parameters of the mobile telephone 10, such as the operating frequency of the processor(s) 12 or the number or type of processor(s) which have been enabled, to a learning component 18, as shown at B.3.2 of Figure 3.
• the learning component 18 is connected to an event monitor 20 which monitors events occurring in the mobile telephone 10.
• an operation or activity which will cause a change in the demand on the processor(s) 12 of the mobile telephone 10 is typically preceded by one or more events, and the event monitor 20 is configured to keep a record of such events in a suitable buffer (B.3.4), which must be large enough to accommodate records of a large number of such events.
• a media file such as an MP3 file
• the media player application is run and a handle to the media file is opened.
• These events can for example be detected by monitoring a program loader (i.e. a software component responsible for loading applications or drivers into memory of the mobile telephone 10 and preparing them to run), a file server (i.e. a software component which is responsible for accessing files stored in a file system) and a scheduler of the mobile telephone 10.
• a program loader i.e. a software component responsible for loading applications or drivers into memory of the mobile telephone 10 and preparing them to run
• a file server i.e. a software component which is responsible for accessing files stored in a file system
• a scheduler of the mobile telephone 10.
• the file type is recognised by a multimedia sub-system of the mobile telephone 10;
• the media player application is loaded by the program loader or a file server
• a media player thread is scheduled by a scheduler of the mobile telephone 10;
• a sound driver is loaded by the program loader or file server;
• a suitable codec e.g. an MP3 codec is loaded by the program loader or file server;
• the multimedia sub-system sends audio data to the sound driver.
• a camera of the mobile telephone 10 is launched and a telephony stack of the mobile telephone 10 is started, by loading appropriate drivers and scheduling appropriate threads. These events can be detected for example by monitoring the program loader, scheduler and telephony stack.
• a Java® game is launched on the mobile telephone 10 this will typically be preceded by a large increase in the amount of memory allocated to a Java Virtual Machine (JVM) of the mobile telephone 10, for example, which can be detected by monitoring a kernel or user allocator of the mobile telephone 10.
• JVM Java Virtual Machine
• the event monitor 20 is configured to monitor the file server, the program loader, the scheduler, the kernel or user allocator, the telephony stack and other subsystems and software components of the mobile telephone 10, as well as user events occurring in the mobile telephone 10, and to record events which occur in these subsystems and software components in the buffer (B.3.4).
• the learning component 18 is configured to determine whether a particular sequence of events recorded by the event monitor 20 is likely to lead to a change in the load on the processor(s) 12. In this example every time the controller 16 changes the operating frequency of the processor(s) 12 or another operating parameter of the mobile telephone 10 such as, for example, the number or type of processors 12 that are enabled in response to a change in the demand on the processor(s) 12, the learning component 18 examines the contents of the buffer of the event monitor 20 (B.3.6) and creates a record of the change in the operating parameters and the events that preceded the change (B.3.8).
• the learning component 18 builds up a list (or "learning pool") of event sequences which may cause a change in one or more operating parameters of the mobile telephone 10.
• the newly-created record is also allocated a score of zero, which for example changes depending upon the accuracy of predictions made by the learning component 18 of whether an operating parameter of the mobile telephone 10 will change as a result of the recorded sequence of events, as will be described below.
• the learning component 18 continually monitors the event monitor 20 such that any time a sequence of events occurs which corresponds to a sequence which is already stored in a record in the learning component 18, the learning component 18 is able to predict whether that sequence will cause a change in one or more operating parameters of the mobile telephone 10. In this example the learning component 18 then checks whether its prediction was correct by examining the processor load monitor 14 after the sequence of events. In this example if the prediction of the learning component 18 was correct, the score associated with that particular sequence of events and the associated change in operating parameters is incremented, whereas if the prediction of the learning component 18 was incorrect, the score associated with the sequence of events and the associated change in operating parameters is decremented (B.3.10).
• the event sequence ⁇ A, B, C ⁇ may be recorded in the learning component 18 and associated with the action "Reduce Operating Frequency of Processor". If the learning component 18 recognises this event sequence in the buffer of the event monitor 20, and the operating frequency of the processor 12 is subsequently reduced, the score associated with the sequence and the change in the operating parameter (i.e. the reduction in the operating frequency of the processor 12) is incremented. However, if following the event sequence ⁇ A, B, C ⁇ the operating frequency of the processor does not change, the score is decremented.
• the learning component 18 uses a pattern matching algorithm to recognise event sequences stored in the buffer of the event monitor 20.
• the sequence ⁇ A, B, X, Y, C, D, Z, E ⁇ appearing in the buffer would be recognised as both sequences ⁇ A, B, C ⁇ and ⁇ X, Y, Z ⁇ by the learning component 18.
• the positive and negative thresholds in the example given above could be reversed such that the score associated with a particular event sequence is decremented if the prediction made by the learning component 18 is correct, with the event sequence and associated change in the operating parameter(s) of the mobile telephone 10 being added to the predicting pool if the score reaches a predetermined negative threshold.
• the prediction component 22 continually monitors the event monitor 20 (B.4.2), such that if a sequence of events recorded by the event monitor 20 matches a sequence in the prediction pool (B.4.4) the prediction component 22 is able to make the associated change to the operating parameters of the mobile telephone 10 without the intervention of the controller 16. In this way, in this example the prediction component 22 is able to recognise sequences of events that will necessitate a change to one or more operating parameters of the mobile telephone 10 and make the necessary change preemptively (B.4.6), thus reducing the power consumption of the mobile telephone 10.
• the controller 16 will become redundant, as it will not be required to implement changes to the operating parameters of the mobile telephone 10.
• the controller 16 will need to be used to change the operating parameters until such time as the learning component 18 has successfully learned all of the new event sequences and their associated changes to the operating parameters and stored them in the prediction pool.
• the contents of the prediction pool may for example be extracted and saved as a file which can be used to pre-load the prediction pool of newly- manufactured mobile telephones 10.
• the new mobile telephones 10 will be able to benefit immediately from the pre-loaded prediction pool to reduce power consumption.
• the processor load monitor 14, the controller 16, the learning component 18, the event monitor 20 and the prediction component 22 may for example be implemented as individual hardware elements, such as individual integrated circuits, or may be implemented for example as component parts of a device such as an FPGA, or may be implemented for example as software components running on a suitably-configured processor, or as a combination of these different implementations.
• the second example embodiments is implemented as software modules stored on a computer readable medium, as shown in Figure 5.
• the computing device 10 has a processor 12 and a computer readable medium 30, which stores software modules relating to the various components of the second example embodiment already described.
• an event monitor module 32 is provided, as well as a load monitor module 37, and a controller module 38.
• a learning component module 34 and a prediction component module 36 is also provided.
• the various software modules when run as processes on the processor 12 operate to provide the functionality described above so as to implement the present example.
• a "computer-readable medium” may be any media or means that can contain, store, communicate, propagate or transport the instructions for use by or in connection with an instruction execution system, apparatus, or device, such as a computer, with one example of a computer described and depicted in FIGURE 5.
• a computer-readable medium may comprise a computer-readable storage medium that may be any media or means that can contain or store the instructions for use by or in connection with an instruction execution system, apparatus, or device, such as a computer.
• the different functions discussed herein may be performed in a different order and/or concurrently with each other. Furthermore, if desired, one or more of the above- described functions may be optional or may be combined.

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• Engineering & Computer Science (AREA)
• Theoretical Computer Science (AREA)
• Physics & Mathematics (AREA)
• General Engineering & Computer Science (AREA)
• General Physics & Mathematics (AREA)
• Computer Networks & Wireless Communication (AREA)
• Signal Processing (AREA)
• Power Sources (AREA)
• Mobile Radio Communication Systems (AREA)
• Telephone Function (AREA)
• Debugging And Monitoring (AREA)

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• 2008
  • 2008-11-21 GB GB0821362A patent/GB2465594A/en not_active Withdrawn
• 2009
  • 2009-11-18 EP EP09827251A patent/EP2359217A1/en not_active Withdrawn
  • 2009-11-18 CN CN2009801465412A patent/CN102224475A/zh active Pending
  • 2009-11-18 WO PCT/IB2009/055144 patent/WO2010058352A1/en active Application Filing
  • 2009-11-18 US US13/130,355 patent/US20110320836A1/en not_active Abandoned
  • 2009-11-18 KR KR1020117014131A patent/KR20110097859A/ko not_active Application Discontinuation

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