Digital rights management leveraging motion or environmental traits

Digital rights management techniques are used to control access to items of content based on motion or environmental traits. Data is collected that describes motion or environmental traits associated with a request to access content, the request received from a user. A determination is made from the data using a digital rights management module embedded as part of the content as to whether the motion or environmental traits meet specified traits of a motion or environmental behavior of a digital rights management policy enforced by the digital rights management module for at least one item of the content. Responsive to a determination that the specified traits are met, access to the at least one item of the content is permitted by the embedded digital rights management module.

BACKGROUND

Digital rights management is used to control use of content, e.g., to alter, consume, or distribute content. Current digital rights management techniques are based on qualities that are unique to a particular user. For example, a purchaser of an application from a conventional application store, a song from an online music store, and so on may be given access to the content via a user name and password of an account associated with the user for a corresponding service. Other conventional examples include persistent online authentication, unique content identifiers (e.g., CD keys), digital watermarks, and encryption keys associated with a particular user or user's device.

Each of these conventional techniques, however, is rigid and lacks an ability to address changes in how the content is to be consumed and thus limit usability of the content. Accordingly, this “all-or-nothing” approach to content access may be frustrating to consumers of the content and thus limit desired distribution of the content, and even force the creation of multiple versions of the content and consequently complicate distribution of this content to intended recipients.

SUMMARY

Digital rights management techniques are described that are used to control access to items of content based on motion or environmental traits. Data is collected that describes motion or environmental traits associated with a request to access content. The request is received from a user and describes motion of a user, motion of a computing device associated with the user, environmental traits describing a user's surroundings, or environmental traits describing biometrics of the user.

A determination is made from the data using a digital rights management module embedded as part of the content as to whether the motion or environmental traits meet specified traits of a motion or environmental behavior of a digital rights management policy enforced by the digital rights management module for at least one item of the content. The determination, for instance, may be used to determine how a user is likely to consume the content, where the user is likely to consume the content, emotions associated with the user, and so forth.

Responsive to a determination that the specified traits are met, access to the at least one item of the content is permitted by the embedded digital rights management module. This access, for instance, may be performed based on a determination is whether a user has completed a particular activity, is engaged in a particular activity, does or does not have a specified emotional state, whether or not the user is moving, and so forth. In this way, the digital rights management module may dynamically react to a user and the user's surroundings to control content access.

DETAILED DESCRIPTION

Overview

Conventional digital rights management techniques are rigid and inflexible and thus not able to take into account potentially changing traits of a behavior of a user that is to consume content. For example, conventional techniques typically rely on credentials that are particular to a user such that the credentials uniquely identify that user from each other user. Verification of these credentials is then used to grant access to the content in its entirety in these conventional techniques. This is because conventional credentials do not describe content consumption characteristics of the user.

A user name and password, for instance, may be used to control access to content obtained from an online music store, application store, and so on. Accordingly, the user name and password do not describe behaviors of a population, such as a way in which the population acts or conducts itself toward content. As such, although these conventional techniques may relate to the particular user, these techniques do not address traits of a population behavior that may include the user and thus are not capable of addressing changing traits of the behaviors of the users nor can these conventional techniques adapt to other users.

Digital rights management techniques are described that address traits of a behavior of a user population that is to consume the content. In one or more implementations, traits of a behavior are specified that are incorporated as part of a digital rights management policy for content. Analytics data, for instance, may be collected that describes a user population as a whole. A creator of a DRM policy may then select traits of behaviors for a target population as a subset of this user population to control content consumption by the subset of the user population. As described above, behaviors describe a way in which a user population acts or conducts itself toward content that is relevant to the population as a whole but is not particular to any specific user of that population.

In this way, access to all or portions (i.e., items) of the content may be controlled by a digital rights management module based on contemplated behaviors of consumers of the content, which is embedded as part of the content. For example, a marketer may wish to include an image as part of a marketing campaign for a population segment. The marketer may then specify traits of behaviors of the specific target population (e.g., content consumption characteristics related to age, gender, geographic location included as part of analytics data) to be implemented as part of a digital rights management policy as well as characteristics of content that is to be created.

The characteristics of the content as specified by the marketer are then used by a creative professional to create the content, which is then embedded with a digital rights management module that is configured to implement the digital rights management policy. Thus, in this example a workflow may be supported in which a target population and corresponding policy is first specified through interaction with analytics data and then used as a basis to create content for deployment.

Once deployed, the digital rights management (DRM) module may implement the digital rights management policy to dynamically address traits and changes to the traits of a behavior of users that consume the content. The DRM module, for instance, is configured to control access to different portions of the content based on which traits are met by a user requesting this access. Further, the access may be conditional, such as to permit access to one portion of content if a trait is met (e.g., traveling at a speed below a threshold) but a different portion of content if the trait is not met, e.g., traveling at a speed above the threshold. In this way, the marketers may specify how content is to be consumed, address potentially changing tastes and desires of users, as well as how the content is to be consumed dynamically as the user's traits change without changing the content itself. Accordingly, a single item of content may dynamically change to address changing behaviors of users that are to consume the content which was not possible in conventional techniques, which thus required updates and changes to the content which would then be populated back to the users.

For example, motion traits associated with a user that requests access may be used to control access to portions of the content. Motion traits, for instance, may describe an amount of motion (e.g., speed) detected for a user that requests access. A user that is walking, for instance, may be given access to headlines and section headers of an article and when stopped may be given access to a body of the article. In another example, motion traits may be used to distinguish between types of movement and as such may be used as a basis to control access to particular portions of content, e.g., to distinguish between biking and running. Thus, a variety of different motion traits may be used as behaviors to control content access, further discussion of which is described in relation toFIGS. 3-5.

In another example, environmental traits are used to control access to portion of the content. Environmental traits include biometric traits associated with a user that requests access to the content, such as heart rate, galvanic skin response, skin temperature, and other traits detected by sensors from a user's body. These traits may also be used to control content access directly (e.g., based on a user's temperature) or indirectly as inferring other environmental traits of the user, e.g., emotions. For example, a combination of breathing, galvanic response, and temperature may be used to determine whether a user is agitated, e.g., as possibly lying, nervous, hurried, and so forth. From this, access to portions of content may be controlled accordingly, such as to permit access to generalized portions when agitated but restrict access to detailed portions of content once a user has “calmed down.”

Environmental traits may also be associated with an environment surrounding a user that requests access to the content. Like above, sensors are used to detect these environmental traits, such as accelerometers, gyroscopes, ambient light sensors, UV sensors, barometers, thermometers, and so forth. These environmental traits are then used to control access to content based on a likely “how” and “where” a user is likely to consume the content. For instance, it may be readily determined as to whether a user is likely indoors or outside and thus access to corresponding portions of the content may be controlled based on this determination, e.g., interior controls for an automobile in a user manual when in a car and exterior options for the automobile when outside the car.

Further, these environmental traits may be combined with the biometric traits above and even the motion traits to make a determination as to a likely activity, in which, a user is participating and/or has participated. Environmental traits, for instance, may be used to determine whether a user has completed an activity and thus may be given access to a portion of content regarding a next activity, may be used to determine a current activity and control data access related to that current activity, and so forth. In this way, dynamic content access is provided that adjusts to how a user access the content as well as what a user is doing in relation to this content access, further discussion of which may be found in relation toFIGS. 6-9.

In the description herein, content refers to a variety of different types of content, such as images, video, sound, and so on. Accordingly, characteristics of content to be created may describe a variety of visual and/or audio characteristics, such as objects to be included in an image, general look and feel of the image, types of sounds to be included in sound, locations for capture of video, and so forth. Digital rights management refers to access control techniques that are usable to control access to the content as a whole or particular portions of the content through use of a digital rights management policy, which in the following may be based on traits of a behavior. Traits of behaviors describe a way in which a user population acts or conducts itself toward content that is relevant to the population as a whole but is not particular to any specific user of that population, such as age group, gender, geographic location, profile, business status, group membership, device characteristics, motion or environmental traits, and so forth. Thus, traits met by a particular user are leveraged by the digital rights management policy to control access to content as a whole or particular portions of the content as further described below.

Example Environment

FIG. 1is an illustration of an environment100in an example implementation that is operable to employ digital rights management and behavioral trait techniques described herein. The illustrated environment100includes a client device102, a content creation service104, a marketing service106, and an analytics service108that are communicatively coupled, one to another, via a network110. Each of these entities may be configured in a variety of ways using one or more computing devices.

A computing device, for instance, may be configured as a desktop computer, a laptop computer, a mobile device (e.g., assuming a handheld configuration such as a tablet or mobile phone as illustrated), and so forth to implement the client device102. Thus, the computing device may range from full resource devices with substantial memory and processor resources (e.g., personal computers, game consoles) to a low-resource device with limited memory and/or processing resources (e.g., mobile devices). Additionally, a computing device may be representative of a plurality of different devices, such as multiple servers utilized by a business to perform operations “over the cloud” to implement the content creation service104, the marketing service106, and the analytics service108as further described in relation toFIG. 11.

The marketing service106is illustrated as including a marketing manager module112. The marketing manager module112is representative of functionality to support user interaction to create a marketing campaign, track deployment of the marketing campaign, and so forth. A user, for instance, may interact with the marketing manager module112to specify a marketing campaign, items of content to be included in the campaign, and one or more behaviors of the campaign. The user may also interact with a DRM creation module114that is representative of functionality to specify traits of behaviors to form a DRM policy116to be utilized to manage access to content118. The campaign, for instance, may be configured to control output of different images as a background based on age of users that access the content.

The marketing manager module112may employ analytics to generate analytics data (i.e., “big data”) that describes a user population, such as traits of behaviors as described above. Through interaction with the marketing manager module112, a user may then select traits of behaviors of a target population from this data that are to be met by users to consume corresponding portions of content118. For example, the marketing manager module112may output a user interface via which a user may select traits of behaviors for a desired target population (e.g., age, gender, job title), such as by selecting a check box, keyword input, and so forth. In this way, the user is provided with detailed knowledge of traits of behaviors of a target population and from this knowledge select traits of behaviors to be met to consume particular portions of the content118, rather than guessing which traits could be met by a target population as performed in conventional techniques which may be prone to error and inefficient.

Data describing the content118to be created and the traits specified above as part of creation of the DRM policy116through interaction with the DRM creation module114is then provided to a content creation service104in this example. The content creation service104includes a content creation module120that is representative of functionality to create content118, which is illustrated as stored in storage122. A variety of content118may be created, such as webpages, advertisements, media including video and/or audio content, and so forth.

Continuing with the previous example, a user interacts with the content creation module120to create content118having characteristics as specified by the marketing service106. As part of this creation, a DRM manager module124is used to embed a DRM module126as part of the content118. The DRM manager module124is representative of functionality to control implementation of the DRM policy116as part of the content118during consumption of the content118, e.g., by a communication module128(e.g., browser, web-enabled application) of the client device102.

The DRM module126may be configured to determine traits of a user that requests access to the content118and provide access to portions of the content118, if any, that correspond to those traits. For example, the DRM policy116may specify different backgrounds of an advertisement for different behaviors. Accordingly, the DRM module126determines traits of a user requesting access and provides access to corresponding portions of the content118, e.g., the backgrounds. In this way, the DRM policy116as specified by the marketing service106in this example serves as a basis for creation of the content118and management of access to portions of the content118. Examples that support additional complications and dynamic responses of DRM control are described in the following.

The DRM module126is configured to leverage data obtained from a variety of sources to determine traits associated with a user in order to control access. An example of one such source is illustrated as an analytics service108having an analytics manager module130that is representative of functionality to collect analytics data. This may include analytics data such as social network posts, webpages visited, items bought and so forth that is exposed via application programming interfaces by websites. This may also include tracking code that is embedded as part of content that exposes data describing usage of the content. Thus, the “big data” collected by the analytics service108from third-party sources may describe the user and content usage of the user which may then be used by the DRM module126to control interaction with the content118as further described below.

FIG. 2depicts a system200in an example implementation of creation of a DRM policy and subsequent content to be consumed by users included in a target segment. The system200is illustrated using first, second, and third stages202,204,206. At the first stage202, user interaction with a marketing manager module110is used to specify content characteristics208, e.g., for part of a marketing campaign. A variety of different content characteristics208may be specified, including type of content such as webpage, printed add, audio such as a jingle or song, video such as an instructional product video or dedicated product advertisement, legal contract. The content is also deliverable in a variety of ways, e.g., streaming or downloaded for local storage and subsequent playback.

The marketing manager module112as previously described also includes a DRM creation module114. The DRM creation module114in this instance is representative of functionality to specify digital rights management (DRM) traits210of behaviors that are used to create a DRM policy116of the content creation service104. The DRM policy116as previously described is configured to control content access by determining which traits of users are satisfied in order to gain access to portions of content. As described above, the DRM traits may be specified in a variety of ways, such as through selection of particular traits collected through analytics by the marketing service106.

A variety of different DRM traits210may be specified, such as traits particular to a behavior but are not unique to individual members having the behavior, e.g., may be satisfied by a plurality of users. Examples of such behavioral traits that are usable to determine potential interaction of a user with content include age group212(e.g., particular age or age range), gender214, geographic location216(e.g., based on IP address, city, state, region, country, continent), organizational associations such as profile218(e.g., traits included in a social network profile, business title in a business website, educational degrees achieved, particular skills), business status220(e.g., whether an associated business is in good standing, business certifications), group membership222(e.g., membership to a particular organization), and other traits such as device characteristics224of a device being used by the user to gain access (e.g., brand, hardware resources, software resources, display resources), and temporal traits (e.g., business hours, time of day, day of week, week of month, year). Additional examples of traits include motion226(e.g., motion exhibited by a user or a device making a request), environmental228(e.g., a user's surrounding or biometric to describe the user), and so forth as further described in the following.

At the second stage204, a content creation module120of the content creation service104is used to create content118and a DRM module126to control access to the content118as specified by a DRM policy116created based on the specified DRM traits210. A creative professional, for instance, may interact with the content creation module120of the content creation service104to create content118as specified by the content characteristics208received from the marketing service106. The marketing service106, for instance, may specify different images and the content characteristics208thereof to be used as alternatives as part of a marketing campaign based on the DRM traits210. The creative professional may then create content118as specified.

The content creation module120also includes a DRM manger module124that is representative of functionality that is configured to implement the DRM policy116through embedding the DRM module126as part of the content118. The DRM module126, for instance, may be executable to determine DRM traits associated with consumption of the content118. As described above, these may include DRM traits210of a behavior that are not specific to a particular user, including traits of a device used, age group, geographic location, and so forth.

Accordingly, the content118having the DRM module126may be provided to a client device102for consumption as shown at the third stage206. The DRM module126may then be utilized to address differences in traits between users, such as gender212. The DRM module126is also usable to address changes in the user, itself, such as change in age group212, geographic location216, business status220(e.g., job title), membership222, motion226, an environment228in which the user is location, and so on. Further, as the DRM module126is embedded as part of the content118this dynamic consumption may be performed offline without accessing a network, and thus may address limitations of conventional techniques that required access in order to serve different content, such as targeted advertisements as part of webpages that are obtained and not available locally until relevant characteristics of a user are determined.

FIG. 3depicts a system300in an example implementation in which digital rights management is utilized to control access to items of content based on motion. This example is illustrated using first and second stages302,304. The client device102includes a sensor306that is configured to detect motion308. This motion308may include motion of the client device102itself (e.g., is included as part of the client device102) or motion of a user310of the client device102, e.g., detected using a wearable computing device. A variety of different types of sensors may be used, such as an accelerometer, positioning system, inertia detection device, or magnetometer.

The motion308detected by the sensor306is leveraged by the DRM module126to control access to first and second items of content312,314. In the illustrated example at the first stage302, the DRM module126determines from data received from the sensor306that the user310is not moving above a threshold amount, e.g., is standing relatively still. In response, the DRM module126permits access to the first and second items of content312,314.

At the second stage304, however, the DRM module126determines from data received from the sensor306that the user310is moving above the threshold amount, e.g., is walking as illustrated. In response, the DRM module126restricts access to the second item of content314yet permits access to the first item of content312. In this way, the DRM module126may dynamically provide access to individual items of the content118in a manner that addresses motion of a user. An example of this access is described in the following and shown in a corresponding figure.

FIG. 4depicts an implementation400showing an example of control of access to items of content based on detected motion. This implementation is also shown using first and second stages302,304that correspond to the first and second stages302,304ofFIG. 3, respectively.

At the first stage302, the user310is not moving above a threshold amount and therefore access to first and second items of content312,314is permitted. The first item of content312in this example includes a section header “Sports News Today” and article titles “Playoff Football is Here” and “Ice Time.” The second item of content314includes a body of the articles. Thus, at the first stage302the user310may view the section header, article titles, and body of the articles when not moving above a threshold amount. This threshold may be set such that the threshold distinguishes between motion that could find the second item of content314distracting (e.g., and therefore potentially harmful to the user310) and motion at which the second item of content314is not a distraction as further described below.

At the second stage304, for instance, the DRM module126determines that the user310is moving above the threshold amount, e.g., is walking and not just “fidgeting.” In response, the DRM module126restricts access to the second item of content314(e.g., the body of the articles) but permits access to the first item of content312, e.g., the section header and article titles. In this way, distraction caused by the second item of content314is prevented while moving. This process may continue for a series of successively greater amounts of motion and corresponding greater restrictions on access to respective items of the content, e.g., in a hierarchical relationship based on amounts of motion.

In the illustrated example of the second stage304, indications are output to inform the user310as to why the second item of content314is not viewable. Other examples are also contemplated, such as to reformat the content such that these removed sections and the space previously consumed by these sections is not viewable by a user. Additionally, although an ability to view the items of content is described as an example of access, other examples are also contemplated, such as to permit viewing but restrict the user's ability to edit the items of content when moving. In this example, an amount of motion is used to dynamically control access to items of content by the DRM module126. Other examples are also contemplated in which different types of motion are distinguished, one from another, and used to dynamically control content access, an example of which is described in the following and shown in a corresponding figure.

FIG. 5depicts an implementation500showing an example of control of access to items of content based on types of detected motion. This example is illustrated using first and second stages502,504. As previously described, the sensor306may be configured in a variety of different ways to detect motion308, such as through use of accelerometers (e.g., three-axis accelerometers), positioning system (e.g., global positioning system receiver), inertia detection device, magnetometers (e.g., detection motion in relation to true north or local objects), and so forth. Through use of one or more of these sensors, motion can be detected as well as a type of motion, which may be used to control access.

As shown at the first stage502, a user506is running. This type of motion is identified by the DRM module126by detecting motion of the user's506legs (e.g., steps) as well as the swinging of the user's506arms. In response, the DRM module126restricts access to the first item of content312but permits access to a second item of content314, e.g., that pertains to running.

At the second stage504, the user506is cycling. This type of motion is identified by the DRM module126by detecting motion of the user's506legs (e.g., steps) and noting that the user's506arms are not swinging. In response, the DRM module126restricts access to the second item of content314but permits access to the first item of content312, e.g., that pertains to cycling. Thus, the DRM module126may differentiate between a variety of different types of motion and dynamically control access to individual items of content. Other traits may also be detected using the sensors306, additional examples of which are described in the following.

FIG. 6depicts an example implementation600in which sensors306are configured to detect environmental traits associated with a request to access content118and used as a basis to control content118access. The sensors306in this example are configured to detect characteristics of an environment in which the content118is to be consumed.

In the illustrated instance, the client device102is configured as a wearable computer (e.g., a smart watch) that is worn by the user and thus is configured to detect an environment of the user602that is to consume the content118. This includes user surroundings604such as temperature, ambient light, and so forth. From this, the DRM module126may make a determination as to “where” the content118is to be consumed as respond accordingly, further discussion of which is described in relation toFIG. 7.

The sensors306may also be configured to detect an environment of the user602, itself, such as biometrics606of the user602including heart rate, perspiration, skin temperature, and so forth. Thus, the environment of the user602itself may also be leveraged by the DRM module126to control consumption of the content118, further discussion of which is described in relation toFIG. 8.

FIG. 7depicts an example implementation700in which an output from sensors306that are configured to detect a user's surroundings604is employed by a DRM module126to manage content118access. A variety of configurations of the sensors306may be employed to detect the user surroundings604, examples of which include an accelerometer702(e.g., three-axis accelerometer), gyroscope704, ambient light706sensor, ultraviolet sensor708, thermometer710to detect air temperature, microphone712, optical sensor714(e.g., a camera, infrared sensor), barometer716, and so forth.

The DRM module126in this example implementation700includes an environmental characteristic module718that processes inputs received from the sensors306to infer characteristics about an environment in which the client device102and/or a user making a request to access the content118is disposed. A simplified example of this is illustrated as a determination as to whether the client device102is located indoors720or outdoors722, e.g., from temperature, UV sensor708, ambient light706sensor, and so forth. Other examples are also contemplated, such as to determine a likelihood that a user will be overheard (e.g., via a microphone to detect noises consistent with a coffee shop) or access the items of the content118will be otherwise compromised. In this way, the DRM module126may dynamically react to traits of a surrounding environment, in which, the content118is to be consumed.

FIG. 8depicts an example implementation800in which an output, from sensors306that are configured to detect biometrics606of a user, is employed by the DRM module126to manage content118access. A variety of configurations of the sensors306may be employed to detect biometric606information of a user that requests access to the content118. Illustrated examples of which include a heart rate sensor802(e.g., an optical heart rate sensor), a skin temperature sensor804, a capacitive sensor806, a galvanic response sensor808, and so forth.

The DRM module126includes a user emotion module810that is representative of functionality to infer a likely emotion of a user based on the biometrics606. Data received form the sensors306such as heart rate, skin temperature, and so forth may be used to infer whether the user is happy812or agitated814in this example. The DRM module126may then control access to the first and second items of content312,314based on this inference, such as to prevent access to the second item of content314when the user is agitated814and permit access when the user has calmed down, e.g., is happy812. Other inferred emotions are also contemplated such as acceptance, anger, anticipation, disgust, joy, fear, sadness, surprise, courage, hope, and so forth.

FIG. 9depicts an example implementation900in which detection of a combination of environment traits including user surroundings604and biometrics606is used to improve accuracy in a determination in how content118is likely to be consumed by a user. This implementation900is depicted using first and second stages902,904. In this example, data from multiple sensors is used to further improve accuracy as to a likely emotion exhibited by a user906.

At the first stage902, for instance, data received from the sensors306involving biometrics may indicate that the user is likely agitated or worried based on skin temperature and sweating. Accordingly, in such an instance the DRM module126may restrict access to the second item of content314due to this inference.

At the second stage904, however, data regarding a user's surroundings604is detected by the sensors306in addition to the biometrics606. From this, the DRM module126may determine that the user906is outside, e.g., due to outside temperature, ambient light, a UV sensor, and so forth. Consequently, the data from the biometrics606, rather than just indicate an agitated state of emotions of the user906may consider a source of the agitation and react accordingly, e.g., to permit access to the second item of content314in this example. A variety of other examples are also contemplated, such as to verify user surroundings604based on biometrics606, incorporate motion308(e.g., to determine whether the user is likely running inside or outside), and so forth.

Example Procedures

FIG. 10depicts a procedure1000in an example implementation in which digital rights management techniques are used to control access to items of content based on motion or environmental traits. Data is collected that describes motion or environmental traits associated with a request to access content, the request received from a user (block1002). A variety of motion sensors are contemplated, such as an accelerometer, positioning system, inertia detection device, or magnetometer. Environmental sensors are also contemplated, such as an accelerometer, a gyroscope, an ambient light sensor, an ultraviolet light sensor, a thermometer, a microphone, an optical sensor, or a barometer. Biometric sensors may also be used, such as a heart rate sensor, a skin temperature sensor, a capacitive sensor, or a galvanic skin response sensor.

A determination is made from the data using a digital rights management module embedded as part of the content as to whether the motion or environmental traits meet specified traits of a motion or environmental behavior of a digital rights management policy enforced by the digital rights management module for at least one item of the content (block1004). The determination, for instance, may be used to determine how a user is likely to consume the content, where the user is likely to consume the content, emotions associated with the user, and so forth.

Responsive to a determination that the specified traits are met, access to the least one item of the content is permitted by the embedded digital rights management module (block1006). This access, for instance, may be controlled based on a determination of whether a user has completed a particular activity, is engaged in a particular activity, has or does not have a specified emotional state, whether or not the user is moving, and so forth. In this way, the digital rights management module may dynamically react to a user and the user's surroundings to control content access.

Example System and Device

FIG. 11illustrates an example system generally at1100that includes an example computing device1102that is representative of one or more computing systems and/or devices that may implement the various techniques described herein. This is illustrated through inclusion of the content118and DRM module126. The computing device1102may be, for example, a server of a service provider, a device associated with a client (e.g., a client device), an on-chip system, and/or any other suitable computing device or computing system.

Combinations of the foregoing may also be employed to implement various techniques described herein. Accordingly, software, hardware, or executable modules may be implemented as one or more instructions and/or logic embodied on some form of computer-readable storage media and/or by one or more hardware elements1110. The computing device1102may be configured to implement particular instructions and/or functions corresponding to the software and/or hardware modules. Accordingly, implementation of a module that is executable by the computing device1102as software may be achieved at least partially in hardware, e.g., through use of computer-readable storage media and/or hardware elements1110of the processing system1104. The instructions and/or functions may be executable/operable by one or more articles of manufacture (for example, one or more computing devices1102and/or processing systems1104) to implement techniques, modules, and examples described herein.

The techniques described herein may be supported by various configurations of the computing device1102and are not limited to the specific examples of the techniques described herein. This functionality may also be implemented all or in part through use of a distributed system, such as over a “cloud”1114via a platform1116as described below.

The cloud1114includes and/or is representative of a platform1116for resources1118. The platform1116abstracts underlying functionality of hardware (e.g., servers) and software resources of the cloud1114. The resources1118may include applications and/or data that can be utilized while computer processing is executed on servers that are remote from the computing device1102. Resources1118can also include services provided over the Internet and/or through a subscriber network, such as a cellular or Wi-Fi network.

The platform1116may abstract resources and functions to connect the computing device1102with other computing devices. The platform1116may also serve to abstract scaling of resources to provide a corresponding level of scale to encountered demand for the resources1118that are implemented via the platform1116. Accordingly, in an interconnected device embodiment, implementation of functionality described herein may be distributed throughout the system1100. For example, the functionality may be implemented in part on the computing device1102as well as via the platform1116that abstracts the functionality of the cloud1114.

CONCLUSION