U.S. patent application number 13/103259 was filed with the patent office on 2011-09-01 for dynamic power usage management based on historical traffic pattern data for network devices.
This patent application is currently assigned to CISCO TECHNOLOGY, INC.. Invention is credited to Kenneth Durazzo, Andrew G. Harvey.
Application Number | 20110213865 13/103259 |
Document ID | / |
Family ID | 40382050 |
Filed Date | 2011-09-01 |
United States Patent
Application |
20110213865 |
Kind Code |
A1 |
Durazzo; Kenneth ; et
al. |
September 1, 2011 |
Dynamic Power Usage Management Based on Historical Traffic Pattern
Data for Network Devices
Abstract
Particular embodiments provide power usage management for
network devices according to historical traffic pattern data.
Network traffic statistics for traffic flowing through a network
device may be determined. A traffic pattern for a time period based
on the traffic flowing through the network device is then
determined. The network device may then manage power based on the
pattern. For example, when a pattern indicates that traffic flowing
through the network device is light during a time period, then the
network device may operate in a lower power mode, such as a standby
mode and when it indicates that there is higher usage, the network
device may operate in a normal power mode. In one embodiment, a
power usage policy may be determined based on the historical
traffic patterns and is automatically enforced by the network
device. The power usage policy may also be dynamically adjusted
over time based on network traffic statistics.
Inventors: |
Durazzo; Kenneth; (San
Ramon, CA) ; Harvey; Andrew G.; (Pleasanton,
CA) |
Assignee: |
CISCO TECHNOLOGY, INC.
San Jose
CA
|
Family ID: |
40382050 |
Appl. No.: |
13/103259 |
Filed: |
May 9, 2011 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
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11844325 |
Aug 23, 2007 |
7957335 |
|
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13103259 |
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Current U.S.
Class: |
709/220 |
Current CPC
Class: |
H04W 52/225
20130101 |
Class at
Publication: |
709/220 |
International
Class: |
G06F 15/177 20060101
G06F015/177 |
Claims
1. A method comprising: creating, using a Network Management
Station (NMS), a Simple Network Management Protocol (SNMP) context,
an associated SNMP context name and an associated SNMP view, the
NMS being coupled to a plurality of network devices in the network;
specifying, using the NMS and the SNMP context name, a network
configuration and an order of the network devices, wherein the
specified order comprises an order in which SNMP SET commands are
executed on the network devices; acquiring, using the NMS, an
exclusive lock mechanism on the network configuration, wherein the
exclusive lock mechanism prevents other network configuration
changes while the exclusive lock mechanism is acquired; issuing,
using the NMS, the SNMP SET commands in the specified order such
that the network configuration is validated by all of the network
devices in the specified order and using the SNMP context name; in
response to validation of the specified network configuration by
all of the network devices, pushing, from the NMS and in the
specified order, the network configuration to each of the network
devices, wherein the pushing begins after a set time has elapsed,
wherein the set time is greater than a time taken for pushing the
network configuration across all of the network devices;
performing, using the NMS and the SNMP context name, an SNMP WALK
on all of the network devices to verify the implementation of the
network configuration, wherein the SNMP WALK is performed within
the time taken for pushing the network configuration across all of
the network devices; and based on the verification of the
implementation of the network configuration, destroying, using the
NMS, the SNMP context.
Description
CROSS REFERENCE TO RELATED APPLICATION
[0001] This application is a continuation application of and claims
priority to U.S. application Ser. No. 11/844,325, filed on Aug. 23,
2007, the contents of which are hereby incorporated by
reference.
TECHNICAL FIELD
[0002] Particular embodiments generally relate to power
management.
BACKGROUND
[0003] Network equipment platforms operate at one power consumption
level. For example, if a platform has a 300 watt power supply, it
is drawing power at that level regardless if it is using that power
to transfer packets.
[0004] There are also home appliances, such as dishwashers, washers
and dryers, etc., that may be EnergyStar.TM. compliant. These
appliances may be more energy efficient than their predecessors.
For example, they may include circuitry that operates in a more
efficient manner than the circuitry of predecessor appliances.
However, a certain level of power is still continuously used no
matter how the appliance is operating. The appliances just use less
energy when operating than previous appliances.
BRIEF DESCRIPTION OF THE DRAWINGS
[0005] FIG. 1 depicts an example of a system for providing power
usage management.
[0006] FIG. 2 depicts an example of a method for determining a
power usage policy.
[0007] FIG. 3 depicts an example of enforcing a power usage policy
at a network device.
[0008] FIG. 4 depicts a more detailed example of the network device
and traffic pattern analyzer 104.
DESCRIPTION OF EXAMPLE EMBODIMENTS
Overview
[0009] Particular embodiments provide power usage management for
network devices according to historical traffic pattern data.
Network traffic statistics for traffic flowing through a network
device may be determined. A traffic pattern for a time period based
on the traffic flowing through the network device is then
determined. For example, it may be determined that from 9 a.m.-5
p.m. on Monday, there is high traffic use but from 5 p.m.-12:00
p.m., there is low traffic use. Also, on Tuesday, there may be low
traffic use from 12:01 a.m. to 10:00 a.m. followed by a period of
high traffic use from 10:00 a.m. to 8:00 p.m. These patterns may be
determined based on the network traffic statistics. The network
device may then manage power based on the pattern. For example,
when a pattern indicates that traffic flowing through the network
device is light during a time period, then the network device may
operate in a lower power mode, such as a standby mode. When the
traffic pattern indicates that there is higher usage, then the
network device may operate in a normal power mode. In one
embodiment, a power usage policy may be determined based on the
historical traffic patterns and is automatically enforced by the
network device. The power usage policy may indicate when the
network device should operate in a lower power mode or a higher
power mode. The power usage policy may be dynamically adjusted over
time based on network traffic statistics. For example, every day,
week, month, etc., the network traffic statistics may be evaluated
and a new power usage policy may be determined and enforced on the
network device.
[0010] In one embodiment, a method is provided that comprises:
determining network traffic statistics for traffic flowing through
a network device; providing the network device with traffic pattern
information based on the network traffic statistics for traffic
flowing through the network device, the traffic pattern information
allowing for power usage management to be performed where the
network device operates in a lower power mode when the traffic
pattern information indicates a traffic pattern associated with
lower usage; and dynamically providing the network device with
updated traffic pattern information based on new network traffic
statistics to allow the network device to adjust its power usage
management.
[0011] In another embodiment, a method is provided that comprises:
determining network traffic statistics for traffic flowing through
a network device; determining traffic pattern information, the
traffic pattern information determined based on the traffic flowing
through the network device; performing power usage management by
operating in a lower power mode during one or more first time
periods when the traffic pattern information indicates a traffic
pattern associated with lower usage and operating in a higher power
mode during one or more second time periods when the traffic
pattern information indicates a traffic pattern associated with
higher usage; and dynamically changing the power usage management
by changing at least one of the one or more first time periods
and/or the one or more second time periods of operating in the
lower power mode and higher power mode based on new traffic pattern
information determined from new network traffic statistics.
[0012] In yet another embodiment, an apparatus is provided
comprises: one or more processors; and logic encoded in one or more
tangible media for execution by the one or more processors and when
executed operable to: determine network traffic statistics for
traffic flowing through a network device; provide the network
device with traffic pattern information based on the network
traffic statistics for traffic flowing through the network device,
the traffic pattern information allowing for power usage management
to be performed where the network device operates in a lower power
mode when the traffic pattern information indicates a traffic
pattern associated with lower usage; and dynamically provide the
network device with updated traffic pattern information based on
new network traffic statistics to allow the network device to
adjust its power usage management.
[0013] In another embodiment, an apparatus is provided that
comprises: one or more processors; and logic encoded in one or more
tangible media for execution by the one or more processors and when
executed operable to: determine network traffic statistics for
traffic flowing through a network device; determine traffic pattern
information determined based on the traffic flowing through the
network device; perform power usage management by operating in a
lower power mode during one or more first time periods when the
traffic pattern information indicates a traffic pattern associated
with lower usage and operating in a higher power mode during one or
more second time periods when the traffic pattern information
indicates a traffic pattern associated with higher usage; and
dynamically change the power usage management by changing at least
one of the one or more first time periods and/or the one or more
second time periods of operating in the lower power mode and higher
power mode based on new traffic pattern information determined from
new network traffic statistics.
Example Embodiments
[0014] FIG. 1 depicts an example of a system for providing power
usage management. The system includes a network device 102, a
traffic pattern analyzer 104, a plurality of data senders 106, and
a plurality of data receivers 108. Although one network device 102
is shown, it will be understood that many network devices may use
the power usage management techniques as described in particular
embodiments. Also, although traffic pattern analyzer 104 is shown
as being separate from network device 102, it will be understood
that it may be integrated with network device 102 or functions
described with respect to traffic pattern analyzer 104 may be
distributed to network device 102.
[0015] Network device 102 may be any device that is configured to
process data. For example, network device 102 may process network
traffic. The network traffic may be processed in terms of received
data/sent data. In one embodiment, the input/output of data may be
measured in packets received/packets sent and/or bytes
received/bytes sent, etc. Network device 102 may be a network
equipment platform or be part of one. A network equipment platform
may be one or more network devices that are configured to process
data. Examples of network device 102 include a router, switch,
server, or any other computing device.
[0016] Data senders 106 and data receivers 108 send and receive
data. For example, data senders 106 and data receivers 108 may be
end devices in a network, such as voice over Internet protocol
(VoIP) telephones, personal computers, set top boxes, etc. Also,
they may be other routers, switches, servers, etc. Data senders 106
send data to network device 102. Network device 102 may then send
at least a portion of the data to data receivers 108. For example,
network device 102 may be routing packets as is known in the
art.
[0017] Traffic pattern analyzer 104 is configured to receive
network traffic statistics for the traffic flowing through network
device 102. For example, a history of how many packets were
received and sent by network device 102 may be determined. Traffic
pattern analyzer 104 then can determine a traffic pattern based on
the traffic flowing through the network device. For example, the
traffic pattern may be different levels of usage during different
time periods. In one example, the patterns may be categorized in
hourly, daily, monthly, yearly, daily, etc. windows. Network device
102 then manages power usage based on the patterns. For example, a
power usage policy is determined. The power usage policy may manage
power depending on when various traffic patterns are observed. For
example, the policy may power down network device 102 to a lower
power level during periods of low activity and power up network
device 102 during periods of higher activity.
[0018] The power usage management may be dynamically adjusted over
time. For example, network traffic statistics may be continuously
monitored. As patterns change, the power usage policy may be
dynamically updated. For example, network device 102 may power down
to a lower power level at different times based on the new traffic
patterns observed.
[0019] Traffic pattern analyzer 104 may be separate from network
device 102. A sync of network traffic statistics may occur at
determined times, such as network device 102 may send the
statistics daily to traffic pattern analyzer 104. Also, traffic
pattern analyzer 104 does not have to be separate from network
device, such as traffic pattern analyzer 104 may be software module
in network device 102 that receives (or monitors) the network
traffic statistics. Network device 102 also does not have to
monitor the network traffic statistics itself. For example, another
network device may determine the statistics for network device 102,
such as another network device at an end of a link with network
device 102 may monitor the number of packets received from network
device 102. For example, network device 102 may have to send
packets through a gateway and the gateway can determine the number
of packets sent by network device 102. The other network device
reports the network traffic statistics to traffic pattern analyzer
104, which can then determine the pattern based on the statistics.
By offloading traffic pattern analyzer 104, computing resources may
be saved at network device 102 because it does not need to analyze
the network traffic statistics.
[0020] In one example, network device 102 may be found in a
platform. Network traffic analyzer 104 may include software that is
configured to adjust the power consumption of network device 102 in
the platform. A historical sample of data, such as a month's worth
of data, may be determined. A history of data traffic patterns for
time periods may then be determined. For example, hourly, daily,
weekly, monthly traffic patterns may be determined. Traffic
patterns may then be sent to network device 102. For example, a
daily sync to network device 102 may be provided with the observed
traffic patterns. Network device 102 would then determine when to
manage power consumption based on the traffic patterns. For
example, if the traffic patterns indicate high usage, then network
device 102 would be operating in a normal power mode. Also, when
traffic patterns indicate low use, then network device 102 may
power down to a lower power mode of operation.
[0021] FIG. 2 depicts an example of a method for determining a
power usage policy. In one embodiment, traffic pattern analyzer 104
performs the method.
[0022] In step 202, traffic pattern analyzer 104 determines network
traffic statistics. In one embodiment, the network traffic
statistics may be received in the form of a daily sync from network
device 102 to traffic pattern analyzer 104. The sync may also be
performed at other intervals.
[0023] In step 204, traffic pattern analyzer 104 determines a
traffic pattern for one or more time periods. For example, the
patterns determined may be within certain windows of time, such as
hourly, daily, weekly, etc. It may not be efficient to frequently
switch a network device between power modes. Thus, traffic pattern
analyzer 104 may determine patterns that occur over a longer time
period, such as in terms of hours. Spikes or aberrations in usage
may be ignored over a sample period (e.g., a month's worth of data)
such that efficient power usage is provided where a pattern of
defined usage (e.g., low usage) can be determined over a time
interval. For example, if N packets are transferred over eight
hours, this may be considered a pattern of low usage. However, if
over N packets are transferred in the eight hours, then this may be
a pattern of higher usage.
[0024] In step 206, a power usage policy is determined. The power
usage policy may be used by network device 102 to determine when to
vary power. For example, if the traffic pattern indicates a low
transfer rate of packets received/sent during a time period, then
the policy may indicate that network device 102 should operate in a
lower power mode, such as a standby mode or powered off. The usage
over time may be compared to a threshold to determine if it is
considered low or high. For example, if the usage is below a
threshold, then it is considered low. The lower power mode of
operation may be any level of operation that is less than the
normal or full level of operation. If the power supply for network
device 102 is 300 V, the lower power mode may draw power at a lower
level than 300 V. Also, in traffic patterns that show higher usage,
then the policy indicates that network device 102 should operate in
a normal power mode. The normal power mode may be a power mode that
draws maximum power from a power supply. Also, the normal power
level may just be higher than the lower power level. It should be
noted that the policy may indicate many different levels of power
usage. For example, depending on the traffic pattern, different
levels of power may be provided. In one example, at some points,
network device 102 may be off, then may be powered to a 1st power
level, then to a 2nd power level, and so on.
[0025] In step 208, traffic pattern analyzer 104 facilitates
enforcement of the power usage policy. For example, the policy is
sent to network device 102, which can then determine when to manage
its power based on the policy. The policy may indicate windows of
time where network device 102 should operate in the lower power
mode of operation. Although a power usage policy is described, it
will be understood that any method of determining when to manage
power for network device 102 is covered by the power usage policy.
For example, once the traffic pattern is determined, network device
102 may be configured to determine when to operate in a lower power
mode based on the traffic pattern. The traffic pattern may be sent
to network device 102 indicating which time periods constitute high
and low use. Then, network device 102 is configured to manage power
based on the patterns. Also, many network devices 102 may interpret
the data and adjust their power accordingly. For example, some
network devices 102 may be considered critical and are only powered
to a half power level when the pattern indicates very low usage,
while some network devices move a standby mode.
[0026] Step 210 determines if dynamic readjustment of the power
usage policy is needed. For example, particular embodiments may be
continuously monitoring network traffic that flows through network
device 102. When traffic patterns change, then the power usage
policy may be dynamically altered. For example, after a certain
time period, such as a week or month, the policy may be readjusted
based on additional network traffic data that is received. In this
case, the method reiterates to step 202 and a new power usage
policy is determined.
[0027] If it is not time to dynamically readjust the power usage
policy, the process reiterates to step 210 where it waits until
dynamic readjustment should be performed. In some cases, the new
data may indicate that a change in the policy is necessary because
traffic patterns change. For example, at some point, usage may
increase during a period defined as a low usage period in the
policy. In one example, the usage may go above a certain threshold
for a certain amount of time. Traffic pattern analyzer 104 may note
the new pattern, determine a new policy and have network device 102
enforce it. Thus, when changes occur, network device 102 can adjust
its power management accordingly. This may be important because it
is undesirable to have network device 102 in a lower power mode
during high usage. Also, to save power, network device 102 should
be in a lower power mode when periods previously defined as high
usage become periods of low usage. Thus, particular embodiments
react to changes in the traffic patterns automatically.
[0028] FIG. 3 depicts an example of enforcing a power usage policy
at network device 102. Step 302 installs a power usage policy. For
example, a power usage policy may be received from traffic pattern
analyzer 104 and be installed. By installing the policy, network
device 102 uses data in the policy to alter its power management.
For example, network device 102 may dynamically determine when it
needs to move to a lower power mode and when it needs to be in a
regular power mode based on traffic patterns.
[0029] In step 304, network device 102 determines a time for
entering a lower power mode. For example, the policy may specify
that at 9:00 a.m. network device 102 should enter into a lower
power mode of operation. Also, the pattern may indicate lower
usage, and network device 102 determines it should go into a lower
power mode.
[0030] In step 306, network device 102 enters the lower power mode.
In one embodiment, if a spike of network traffic is received during
a lower power mode of operation, network device 102 may power up as
much as necessary to the maximum power level to service the
request. This may be a power override condition. If a power
override condition occurs, dynamic re-determination of the traffic
pattern may occur to account for the spike in usage, especially if
the spike happens multiple times around the same time period.
However, a single occurrence of a spike may not cause
re-determination of the power usage policy.
[0031] In step 308, network device 102 determines a time to enter a
normal power mode of operation. For example, at 8:00 a.m. it may be
determined that network traffic may start to increase. Thus, in
step 310, network device 102 enters a normal mode of operation. In
one example, network device 102 may power up to the normal mode
before 8:00 a.m. because it may take some time to move from the
lower power mode to the normal mode. Thus, at 8:00 a.m., network
device 102 is able to handle a normal load rather than starting the
powering up process at 8:00 a.m.
[0032] Steps 302-310 may be performed continuously as network
device 102 determines when to enter into a lower power mode of
operation and when to be in a regular power mode of operation.
[0033] Step 312 determines if a new traffic pattern is observed. In
this case, the traffic patterns of new network traffic through
network device 102 may have been further analyzed using additional
data. Accordingly, a new power usage policy may have been
determined and it is installed and enforced.
[0034] FIG. 4 depicts a more detailed example of network device 102
and traffic pattern analyzer 104. A network traffic statistic
determiner 402 is configured to determine network traffic that is
flowing through network device 102. For example, network traffic
statistic determiner 402 may be part of a device that measures
packets received and sent by network device 102. This information
is sent to a traffic pattern determiner 404 of traffic pattern
analyzer 104. Traffic pattern determiner 404 determines traffic
patterns that may exist in data. For example, periods of time when
traffic flowing through network device 102 is low may be
determined.
[0035] A power usage policy determiner 406 then determines a power
usage policy according to the traffic patterns. For example, when
network traffic falls below a certain threshold for a certain
amount of time, this may be considered a pattern of low usage. The
policy may then indicate that network device 102 should move to a
lower power mode of operation. Certain thresholds may be used to
determine when to change power modes. For example, if the traffic
patterns keep varying significantly in that they indicate network
device 102 should operate in a lower power mode of operation for 10
minutes, then a higher power mode of operation for the next 10
minutes, then a lower power mode of operation, and so on, it may
not be desirable to continually power down and power up network
device 102. This may also use more power than just keeping network
device 102 constantly at one power level. Accordingly, power usage
policy determiner 406 intelligently determines when an optimal time
to power down network device 102 to a lower power mode of operation
is desired.
[0036] The policy may be sent and stored in a policy database 408.
A policy enforcer 410 then reads the policy and enforces it. For
example, policy enforcer 410 may cause network device 102 to
operate in a lower power mode of operation 412 or a normal power
mode of operation 414 depending on the traffic pattern observed.
Thus, according to the policy, at certain times, network device 102
is moved from the lower power mode of operation 412 to the normal
power mode of operation 414.
[0037] Some examples will now be described. In one example, a
traffic pattern may be observed for a lack of any meaningful data
traffic from Friday evening at 6:00 p.m. to Monday morning at 6:00
a.m. Traffic pattern analyzer 104 may determine this traffic
pattern and send it to network device 102 in the form of a message.
Network device 102 would then use this information to move to a
lower power mode of operation on Friday evening at 6:00 p.m. It
would remain in this mode until Monday morning at 6:00 a.m.
[0038] In one embodiment, network device 102 may move to the lower
power mode by adjusting power options downward to preserve the
total amount of power to be used during this time period. Also,
network device 102 would power up before 6:00 a.m. so that it would
be at a normal power mode of operation once 6:00 a.m. occurs.
Accordingly, the traffic pattern is used to determine when to power
up before a time when a large amount of data may be received and
have to be processed and transferred. Accordingly, network device
102 can anticipate from the traffic patterns when high amounts of
traffic may be received and thus be at a full power mode of
operation when that time occurs.
[0039] In another example, traffic pattern analyzer 104 sends a
message to network device 102 indicating that there is a traffic
pattern of little or no traffic from 7:00 p.m. to 6:00 a.m. on week
nights and from Friday at 6:00 p.m. to Monday at 6:00 a.m. Network
device 102 would then implement a policy in which it is in a lower
power mode of operation during those times. This saves an
administrator from statically configuring network device 102 to be
in a lower power mode of operation. Further, network device 102 may
be dynamically reconfigured as historical patterns change. For
example, at some point, a company may decide that a back-up should
be run at 2:00 a.m. Also, certain projects may be started in which
computing resources may be used at different times, such as during
the night. Traffic pattern analyzer 104 may automatically detect
this and determine different traffic patterns for different time
periods. For example, network device 102 may then be configured to
operate in the normal power mode at 2 a.m. when the backup starts.
Thus, network device 102 may be automatically reconfigured to
operate in the lower power mode of operation at different
times.
[0040] In another embodiment, network device 102 may include
different blades within a chassis. In this case, any blade in the
chassis may have its own compute infrastructure, such as a personal
computer on a blade. Each blade may be sent a message to go into a
lower power mode of operation based on traffic patterns observed in
the chassis. Accordingly, each blade may be configured with
different policies. This saves power for the chassis as a whole,
but also for individual blades, which may be servicing different
traffic.
[0041] In another example, based upon the correlated information
(from one or more devices) about power usage, a company may
sell/share/exchange the historical information with a utility
provider. The information might allow the utility to better manage
their power infrastructure, especially during rolling-blackouts or
brownouts, etc. For example, the utility may reduce power being
provided to companies during times that show historical patterns of
low usage.
[0042] Particular embodiments provide many advantages. For example,
by analyzing historical traffic patterns, network devices 102 may
be powered down to a lower power mode of operation at optimal times
when performance may not be affected. This may save an entity money
in power usage. Also, network device 102 may be powered up to be at
a full power mode of operation at a time when network traffic may
be considered high. Thus, particular embodiments anticipate when
data traffic may be heavy and accordingly have network device 102
in a maximum power mode of operation.
[0043] Also, particular embodiments continually analyze network
traffic to dynamically adjust a power usage policy. Thus, this may
be more efficient than static policies which may be configured by a
user and not changed. Also, the policies may be more exact and are
based on actual data. This may be important as network traffic
changes. It is not expected that network traffic will remain the
same because network devices 102 may experience different data
traffic according to different conditions. Thus, the dynamic
reconfiguration of the power usage policy is necessary to
efficiently save power at network device 102.
[0044] Although the description has been described with respect to
particular embodiments thereof, these particular embodiments are
merely illustrative, and not restrictive. Although a network device
is described, network devices may also include any device that
processes data.
[0045] Any suitable programming language can be used to implement
the routines of particular embodiments including C, C++, Java,
assembly language, etc. Different programming techniques can be
employed such as procedural or object oriented. The routines can
execute on a single processing device or multiple processors.
Although the steps, operations, or computations may be presented in
a specific order, this order may be changed in different particular
embodiments. In some particular embodiments, multiple steps shown
as sequential in this specification can be performed at the same
time. The sequence of operations described herein can be
interrupted, suspended, or otherwise controlled by another process,
such as an operating system, kernel, etc. The routines can operate
in an operating system environment or as stand-alone routines
occupying all, or a substantial part, of the system processing.
Functions can be performed in hardware, software, or a combination
of both. Unless otherwise stated, functions may also be performed
manually, in whole or in part.
[0046] A "computer-readable medium" for purposes of particular
embodiments may be any medium that can contain, store, communicate,
propagate, or transport the program for use by or in connection
with the instruction execution system, apparatus, system, or
device. The computer readable medium can be, by way of example only
but not by limitation, an electronic, magnetic, optical,
electromagnetic, infrared, or semiconductor system, apparatus,
system, device, propagation medium, or computer memory.
[0047] Particular embodiments can be implemented in the form of
control logic in software or hardware or a combination of both. The
control logic, when executed by one or more processors, may be
operable to perform that which is described in particular
embodiments.
[0048] A "processor" or "process" includes any human, hardware
and/or software system, mechanism or component that processes data,
signals, or other information. A processor can include a system
with a general-purpose central processing unit, multiple processing
units, dedicated circuitry for achieving functionality, or other
systems. Processing need not be limited to a geographic location,
or have temporal limitations. For example, a processor can perform
its functions in "real time," "offline," in a "batch mode," etc.
Portions of processing can be performed at different times and at
different locations, by different (or the same) processing
systems.
[0049] Particular embodiments may be implemented by using a
programmed general purpose digital computer, by using application
specific integrated circuits, programmable logic devices, field
programmable gate arrays, optical, chemical, biological, quantum or
nanoengineered systems, components and mechanisms may be used. In
general, the functions of particular embodiments can be achieved by
any means as is known in the art. Distributed, networked systems,
components, and/or circuits can be used. Communication, or
transfer, of data may be wired, wireless, or by any other
means.
[0050] It will also be appreciated that one or more of the elements
depicted in the drawings/figures can also be implemented in a more
separated or integrated manner, or even removed or rendered as
inoperable in certain cases, as is useful in accordance with a
particular application. It is also within the spirit and scope to
implement a program or code that can be stored in a
machine-readable medium to permit a computer to perform any of the
methods described above.
[0051] Additionally, any signal arrows in the drawings/Figures
should be considered only as exemplary, and not limiting, unless
otherwise specifically noted. Furthermore, the term "or" as used
herein is generally intended to mean "and/or" unless otherwise
indicated. Combinations of components or steps will also be
considered as being noted, where terminology is foreseen as
rendering the ability to separate or combine is unclear.
[0052] As used in the description herein and throughout the claims
that follow, "a", "an", and "the" includes plural references unless
the context clearly dictates otherwise. Also, as used in the
description herein and throughout the claims that follow, the
meaning of "in" includes "in" and "on" unless the context clearly
dictates otherwise.
[0053] Thus, while the present invention has been described herein
with reference to particular embodiments thereof, a latitude of
modification, various changes and substitutions are intended in the
foregoing disclosures, and it will be appreciated that in some
instances some features of particular embodiments will be employed
without a corresponding use of other features without departing
from the scope and spirit as set forth. Therefore, many
modifications may be made to adapt a particular situation or
material to the essential scope and spirit. It is intended that the
invention not be limited to the particular terms used in following
claims and/or to the particular embodiment disclosed as the best
mode contemplated for carrying out this invention, but that the
invention will include any and all particular embodiments and
equivalents falling within the scope of the appended claims.
* * * * *