Patent Publication Number: US-2023147688-A1

Title: Caching Data Based On Greenhouse Gas Data

Description:
BACKGROUND 
     Computing devices typically include components (e.g., memory, hard disk drives, solid-state drives, etc.) that are used to store data utilized by the computing devices. Caching is a technique that can be employed to increase the speed at which data is provided to various consumers of data in a computing device. Caching may be implemented in hardware as well as in software. Examples of hardware caches include processor caches, disk caches, etc. Examples of software caches include web browser caches, database caches, etc. Many caching algorithms exist for managing data in a cache. Examples of such algorithms include first in first out (FIFO), last in first out (LIFO), first in last out (FILO), least recently used (LRU), most recently used (MRU), least frequently used (LFU), etc. 
     SUMMARY 
     In some embodiments, a non-transitory machine-readable medium stores a program executable by at least one processing unit of a device. The program receives a first set of data and a first greenhouse gas emission value associated with the first set of data. The program further stores, in a cache of the device, the first set of data and the first greenhouse gas emission value. The program also receives a second set of data and a second greenhouse gas emission value associated with the second set of data. The program further stores, in the cache of the device, the second set of data and the second greenhouse gas emission value. The program also receives a third set of data and a third greenhouse gas emission value associated with the third set of data. The program further determines one of the first and second sets of data to remove from the cache of the device based on the first greenhouse gas emission value and the second greenhouse gas emission value. The program also replaces, in the cache of the device, the one of the first and second sets of data and the corresponding first or second greenhouse gas emission value with the third set of data and the third greenhouse gas emission value. 
     In some embodiments, the program may further send a computing system a request through an application programming interface (API) provided by the computing system. The first set of data and the first greenhouse gas emission value may be received from the computing system in response to the request. The first greenhouse gas emission value may indicate an amount of greenhouse gas emitted by the computing system to process the request and determine the first set of data. 
     In some embodiments, the program may further receive, through a graphical user interface (GUI), the first greenhouse gas emission value specified for the first set of data and store a mapping between the first greenhouse gas emission value and the first set of data. The program may further send a computing system a request through an application programming interface (API) provided by the computing system, wherein the first set of data is received from the computing system in response to the request, and determine that the first greenhouse gas emission value is associated with the first set of data based on the mapping between the first greenhouse gas emission value and the first set of data. 
     In some embodiments, determining the one of the first and second sets of data to remove from the cache of the device may include determining one of the first and second gas emission values having a highest value and determining a corresponding set of data in the first and second sets of data as being the one of the first and second sets of data to remove from the cache of the device. The cache of the device may be a memory cache of the device. 
     In some embodiments, a method, executable by a device, receives a first set of data and a first greenhouse gas emission value associated with the first set of data. The method further stores, in a cache of the device, the first set of data and the first greenhouse gas emission value. The method also receives a second set of data and a second greenhouse gas emission value associated with the second set of data. The method further stores, in the cache of the device, the second set of data and the second greenhouse gas emission value. The method also receives a third set of data and a third greenhouse gas emission value associated with the third set of data. The method further determines one of the first and second sets of data to remove from the cache of the device based on the first greenhouse gas emission value and the second greenhouse gas emission value. The method also replaces, in the cache of the device, the one of the first and second sets of data and the corresponding first or second greenhouse gas emission value with the third set of data and the third greenhouse gas emission value. 
     In some embodiments, the method may further send a computing system a request through an application programming interface (API) provided by the computing system. The first set of data and the first greenhouse gas emission value may be received from the computing system in response to the request. The first greenhouse gas emission value may indicate an amount of greenhouse gas emitted by the computing system to process the request and determine the first set of data. 
     In some embodiments, the method may further receive, through a graphical user interface (GUI), the first greenhouse gas emission value specified for the first set of data and store a mapping between the first greenhouse gas emission value and the first set of data. The method may further send a computing system a request through an application programming interface (API) provided by the computing system, wherein the first set of data is received from the computing system in response to the request, and determine that the first greenhouse gas emission value is associated with the first set of data based on the mapping between the first greenhouse gas emission value and the first set of data. 
     In some embodiments, determining the one of the first and second sets of data to remove from the cache of the device may include determining one of the first and second gas emission values having a highest value and determining a corresponding set of data in the first and second sets of data as being the one of the first and second sets of data to remove from the cache of the device. The cache of the device may be a memory cache of the device. 
     In some embodiments, a system includes a set of processing units and a non-transitory machine-readable medium that stores instructions. The instructions cause at least one processing unit to receive a first set of data and a first greenhouse gas emission value associated with the first set of data. The instructions further cause the at least one processing unit to store, in a cache of the system, the first set of data and the first greenhouse gas emission value. The instructions also cause the at least one processing unit to receive a second set of data and a second greenhouse gas emission value associated with the second set of data. The instructions further cause the at least one processing unit to store, in the cache of the system, the second set of data and the second greenhouse gas emission value. The instructions also cause the at least one processing unit to receive a third set of data and a third greenhouse gas emission value associated with the third set of data. The instructions further cause the at least one processing unit to determine one of the first and second sets of data to remove from the cache of the system based on the first greenhouse gas emission value and the second greenhouse gas emission value. The instructions also cause the at least one processing unit to replace, in the cache of the system, the one of the first and second sets of data and the corresponding first or second greenhouse gas emission value with the third set of data and the third greenhouse gas emission value. 
     In some embodiments, the instructions may further cause the at least one processing unit to send a computing system a request through an application programming interface (API) provided by the computing system. The first set of data and the first greenhouse gas emission value may be received from the computing system in response to the request. The first greenhouse gas emission value may indicate an amount of greenhouse gas emitted by the computing system to process the request and determine the first set of data. 
     In some embodiments, the instructions may further cause the at least one processing unit to receive, through a graphical user interface (GUI), the first greenhouse gas emission value specified for the first set of data and store a mapping between the first greenhouse gas emission value and the first set of data. The instructions may further cause the at least one processing unit to send a computing system a request through an application programming interface (API) provided by the computing system, wherein the first set of data is received from the computing system in response to the request, and determine that the first greenhouse gas emission value is associated with the first set of data based on the mapping between the first greenhouse gas emission value and the first set of data. Determining the one of the first and second sets of data to remove from the cache of the device may include determining one of the first and second gas emission values having a highest value and determining a corresponding set of data in the first and second sets of data as being the one of the first and second sets of data to remove from the cache of the device. 
     The following detailed description and accompanying drawings provide a better understanding of the nature and advantages of various embodiments of the present disclosure. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
         FIG.  1    illustrates a system for caching data based on greenhouse gas data according to some embodiments. 
         FIG.  2    illustrates an example data structure for a cache entry stored in a cache according to some embodiments. 
         FIGS.  3 A- 3 F  illustrate an example of managing data for a cache based on greenhouse data according to some embodiments. 
         FIG.  4    illustrates a process for caching data based on greenhouse gas data according to some embodiments. 
         FIG.  5    illustrates an exemplary computer system, in which various embodiments may be implemented. 
         FIG.  6    illustrates an exemplary computing device, in which various embodiments may be implemented. 
         FIG.  7    illustrates an exemplary system, in which various embodiments may be implemented. 
     
    
    
     DETAILED DESCRIPTION 
     In the following description, for purposes of explanation, numerous examples and specific details are set forth in order to provide a thorough understanding of the present disclosure. It will be evident, however, to one skilled in the art that various embodiment of the present disclosure as defined by the claims may include some or all of the features in these examples alone or in combination with other features described below, and may further include modifications and equivalents of the features and concepts described herein. 
     Described herein are techniques for caching data based on greenhouse gas data. In some embodiments, a first computing system that is configured to cache data based on greenhouse gas data. For example, the first computing system may call an application programming interface (API) provided by a second computing system. In response to the API call, the first computing system can receive a set of data from the second computing system. In some cases, the first computing system may also receive a greenhouse gas emission value from the second computing system. In other cases, a user of a client device has defined a greenhouse gas emission value associated with the set of data. Regardless of where the greenhouse gas emission value comes from, the first computing system stores the set of data and the greenhouse gas emission value in a cache. The first computing system may continue to cache data that has an associated greenhouse gas emission value in this manner. When the first computing system is caching a particular set of data and its associated greenhouse gas emission value and the cache is full, the first computing system can determine a cache entry in the cache to replace with the particular set of data and its associated greenhouse gas emission value based on the greenhouse gas emission values of the cache entries currently stored in the cache. The first computing system may replace the determined cache entry in the cache with the particular set of data and its associated greenhouse gas emission value. 
       FIG.  1    illustrates a system  100  for caching data based on greenhouse gas data according to some embodiments. As shown, system  100  includes client device  105 , computing system  110 , and computing system  135 . Client device  105  may communicate and interact with computing system  110 . For example, a user of client device  105  can access (e.g., via a graphical user interface (GUI) provided by computing system  110 ) computing system  110  to specify different greenhouse gas emission values for different sets of data. In some embodiments, a data identifier (ID) may be used to identify a particular set of data. In some such embodiments, a user of client device  105  may specify a greenhouse gas emission value for a particular set of data by specifying the greenhouse gas emission value for a data ID identifying the particular set of data. 
     As depicted in  FIG.  1   , computing system  110  includes configuration manager  115 , cache manager  120 , mappings storage  125 , and cache storage  130 . Mapping storage  125  is configured to store mappings between sets of data and greenhouse gas emission values. In some embodiments, a greenhouse gas emission value (e.g., a carbon dioxide emission value, a nitrous oxide emission value, a methane emission value, etc.) indicates an amount of greenhouse gas (e.g., in terms of tons of the greenhouse gas) emitted to produce a corresponding set of data. Cache storage  130  can stores caches for caching sets of data. In some embodiments, storages  125  and  130  are implemented in a single physical storage while, in other embodiments, storages  125  and  130  may be implemented across several physical storages. While  FIG.  1    shows storages  125  and  130  as part of computing system  110 , one of ordinary skill in the art will appreciate that mappings storage  125  and/or cache storage  130  may be external to computing system  110  in some embodiments. 
     Configuration manager  115  is responsible for managing configuration settings for computing system  110 . For instance, configuration manager  115  can provide a graphical user interface (GUI) for receiving different greenhouse gas emission values specified for different sets of data. Through such a GUI, configuration manager  115  may receive a greenhouse gas emission value specified for a particular set of data. In response to receiving the greenhouse gas emission value, configuration manager  115  stores a mapping between the greenhouse gas emission value and the particular set of data (e.g., a data ID identifying the particular set of data). 
     Cache manager  120  is configured to manage data for caches stored in cache storage  130 . For example, when cache manager  120  receives a set of data and a greenhouse gas emission value to be cached in a particular cache, cache manager  120  caches the set of data and the greenhouse gas emission value in the particular cache stored in cache storage  130  based on the greenhouse gas emission values associated with the sets of data stored in the particular cache. Details of a data caching example will be described below.  FIG.  2    illustrates an example data structure  200  for a cache entry stored in a cache according to some embodiments. As shown, data structure  200  includes three attributes  205 - 215 . Attribute  205  is configured to store a data ID for identify the set of data stored in attribute  210 . Attribute  210  stores a set of data. Attribute  215  is configured to store a greenhouse gas emission value. 
     Returning to  FIG.  1   , computing system  135  includes application programming interface (API) manager  140  and greenhouse gas emission data storage  145 . Greenhouse gas emission data storage  145  stores different greenhouse gas emission values for different sets of data produced from executing different API requests. API manager  140  is responsible for managing API requests for APIs provided by computing system  135 . For instance, API manager  140  can receive an API request from computing system  110 . In response to the request, API manager  140  executes the corresponding API, which causes the API to generate a set of data. Next, API manager  140  sends computing system  110   a  response to the API request that includes the set of data. 
     An example data caching operation will now be described by reference to  FIGS.  3 A- 3 F .  FIGS.  3 A- 3 F  illustrate an example of managing data for a cache  300  based on greenhouse data according to some embodiments. For this example, cache  300  is stored in cache storage  130  and cache entries stored in cache  300  are stored according to data structure  200 . The example operation begins with computing system  110  sending API manager  140  a request through an API called API_12. In response to the request, API manager  140  executes API_12, which generates a string value of “orange.” Then, API manager  140  sends computing system  110  the string “orange” and an associated greenhouse gas emission value 0.008. When computing system  110  receives the data, computing system  110  sends cache manager  120  the data as well as name of the API (API_12 in this example). Next, cache manager  120  generates a cache entry that includes a data ID of API_12, a set of data that includes the string “orange,” and a greenhouse gas emission value of 0.008. As shown in  FIG.  3 A , cache  300  includes cache entry  305 , which is the cache entry generated by cache manager  120 . Cache entry  305  includes a data ID of API_12, a set of data that includes the string “orange,” and a greenhouse gas emission value of 0.008. Here, cache manager  120  has stored cache entry  305  in cache  300 . 
     The example operation continues by computing system  110  sending API manager  140  a request via an API called API_7. Upon receiving the request, API manager  140  executes API_7, which generates a string of “green.” API manager  140  sends computing system  110  the string “green” and an associated greenhouse gas emission value 0.002 that API manager  140  retrieves from greenhouse gas emissions data storage  145 . Once computing system  110  receives the data from API manager  140 , computing system  110  sends cache manager  120  the data and the name of the API (API_7 in this example). Next, cache manager  120  generates a cache entry that includes a data ID of API_7, a set of data that includes the string “green,” and a greenhouse gas emission value of 0.002.  FIG.  3 A  also illustrates that cache entry  310  is to be cached in cache  300 . As shown, cache entry  310 , which is generated by cache manager  120 , includes a data ID of API_12, a set of data that includes the string “green,” and a greenhouse gas emission value of 0.002. 
       FIG.  3 B  illustrates cache  300  after cache manager  120  caches cache entry  310 . In this example, cache manager  120  stores cache entry  310  in cache  300  based on the greenhouse gas emission values of cache entries  305  and  310 . In particular, cache manager  120  caches cache entry  310  in cache  300  so that the cache entries in cache  300  are ordered based on the greenhouse gas emission values from smallest to largest (smallest on the left and largest on the right in this example). Here, cache entry  310  has a smaller greenhouse gas emission value than cache entry  305 . Thus, cache entry  310  is depicted as being on the left of cache entry  305  in  FIG.  3 B . 
     Continuing with the example operation, computing system  110  sends API manager  140  a request via an API called API_4. When API manager  140  receives the request, API manager  140  executes API_4, which generates a string of “red.” Then, API manager  140  sends computing system  110  the string “red” and an associated greenhouse gas emission value 0.006 that API manager  140  retrieves from greenhouse gas emissions data storage  145 . Upon receiving the data from API manager  140 , computing system  110  sends cache manager  120  the string, the associated greenhouse gas emission value, and the name of the API (API_4 in this example). Cache manager  120  then generates a cache entry that includes a data ID of API, a set of data that includes the string “red,” and a greenhouse gas emission value of 0.006.  FIG.  3 B  further shows that cache entry  315  is to be cached in cache  300 . As depicted in  FIG.  3 B , cache entry  315 , which is generated by cache manager  120 , includes a data ID of API_4, a set of data that includes the string “red,” and a greenhouse gas emission value of 0.006. 
       FIG.  3 C  illustrates cache  300  after cache manager  120  caches cache entry  315 . For this example, cache manager  120  stores cache entry  315  in cache  300  based on the greenhouse gas emission values of cache entries  305 - 315 . Specifically, cache manager  120  caches cache entry  315  in cache  300  so that the cache entries in cache  300  are ordered based on the greenhouse gas emission values from smallest to largest (smallest on the left and largest on the right in this example). In this example, cache entry  315  has a smaller greenhouse gas emission value than cache entry  305  but a larger greenhouse gas emission value than cache entry  310 . Therefore, cache entry  315  is shown as being on the left of cache entry  305  and to the right of cache entry  310 . 
     The example operation continues by computing system  110  sending API manager  140  a request via an API called API_13. In response to the request, API manager  140  executes API_13, which generates a string of “purple.” Next, API manager  140  sends computing system  110  the string “purple” and an associated greenhouse gas emission value 0.005 that API manager  140  retrieves from greenhouse gas emissions data storage  145 . When computing system  110  receives the data from API manager  140 , computing system  110  sends cache manager  120  the string, the associated greenhouse gas emission value, and the name of the API (API_13 in this example). Then, cache manager  120  generates a cache entry that includes a data ID of API, a set of data that includes the string “purple,” and a greenhouse gas emission value of 0.005.  FIG.  3 C  also illustrates that cache entry  320  is to be cached in cache  300 . As shown, cache entry  320 , which is generated by cache manager  120 , includes a data ID of API_13, a set of data that includes the string “purple,” and a greenhouse gas emission value of 0.005. 
       FIG.  3 D  illustrates cache  300  after cache manager  120  caches cache entry  320 . Here, cache manager  120  stores cache entry  320  in cache  300  based on the greenhouse gas emission values of cache entries  305 - 320 . In particular, cache manager  120  caches cache entry  320  in cache  300  so that the cache entries in cache  300  are ordered based on the greenhouse gas emission values from smallest to largest (smallest on the left and largest on the right in this example). For this example, cache entry  320  has a smaller greenhouse gas emission value than cache entries  315  and  305  but a larger greenhouse gas emission value than cache entry  310 . Hence, cache entry  320  is depicted as being on the left of cache entry  315  and to the right of cache entry  310 . 
     Continuing with the example operation, computing system  110  sends API manager  140  a request via an API called API_1. Upon receiving the request, API manager  140  executes API_1, which generates a string of “blue.” API manager  140  then sends computing system  110  the string “blue” and an associated greenhouse gas emission value 0.01 that API manager  140  retrieves from greenhouse gas emissions data storage  145 . Once computing system  110  receives the data from API manager  140 , computing system  110  sends cache manager  120  the string, the associated greenhouse gas emission value, and the name of the API (API_1 in this example). Next, cache manager  120  generates a cache entry that includes a data ID of API, a set of data that includes the string “blue,” and a greenhouse gas emission value of 0.01.  FIG.  3 D  further shows that cache entry  325  is to be cached in cache  300 . As illustrated in  FIG.  3 D , cache entry  325 , which is generated by cache manager  120 , includes a data ID of API_1, a set of data that includes the string “blue,” and a greenhouse gas emission value of 0.01. 
       FIG.  3 E  illustrates cache  300  after cache manager  120  caches cache entry  325 . In this example, cache manager  120  stores cache entry  325  in cache  300  based on the greenhouse gas emission values of cache entries  305 - 325 . As shown, cache  300  is currently full of cache entries. Thus, cache manager  120  determines how to process cache entry  325 . Here, cache manager  120  determines the cache entry among cache entries  305 - 325  having the smallest greenhouse gas emission value. If the determined cache entry is cache entry  325 , then cache manager  120  drops cache entry  325 . Otherwise, cache manager  120  replaces the determined cache entry with cache entry  325  in a manner that maintains the order of the cache entries from smallest to largest. For this example, cache manager  120  determines that cache entry  310  has the smallest greenhouse gas emission value among cache entries  305 - 325 . As such, cache manager  120  replaces cache entry  310  with cache entry  325 . Since cache entry  325  has the largest greenhouse gas emission value, it is depicted in the right-most position in cache  300  in  FIG.  3 E . 
     The example operation continues by computing system  110  sending API manager  140  a request via an API called API_8. Upon receiving the request, API manager  140  executes API_8, which generates a string of “yellow.” Then, API manager  140  sends computing system  110  the string “yellow” and an associated greenhouse gas emission value 0.001 that API manager  140  retrieves from greenhouse gas emissions data storage  145 . Upon receiving the data from API manager  140 , computing system  110  sends cache manager  120  the string, the associated greenhouse gas emission value, and the name of the API (API_8 in this example). Next, cache manager  120  generates a cache entry that includes a data ID of API, a set of data that includes the string “yellow,” and a greenhouse gas emission value of 0.001.  FIG.  3 E  further depicts that cache entry  330  is to be cached in cache  300 . As illustrated in  FIG.  3 E , cache entry  330 , which is generated by cache manager  120 , includes a data ID of API_8, a set of data that includes the string “yellow,” and a greenhouse gas emission value of 0.001. 
       FIG.  3 F  illustrates cache  300  after cache manager  120  caches cache entry  330 . For this example, cache manager  120  stores cache entry  330  in cache  300  based on the greenhouse gas emission values of cache entries  305 - 330 . As illustrated, cache  300  is currently full of cache entries. Hence, cache manager  120  determines how to process cache entry  330 . In this example, cache manager  120  determines the cache entry among cache entries  305 - 330  having the smallest greenhouse gas emission value. If the determined cache entry is cache entry  330 , then cache manager  120  drops cache entry  330 . If the determined cache entry is not cache entry  330 , cache manager  120  replaces the determined cache entry with cache entry  330  in a manner that maintains the order of the cache entries from smallest to largest. Here, cache manager  120  determines that cache entry  330  has the smallest greenhouse gas emission value among cache entries  305 - 330 . Accordingly, cache manager  120  drops cache entry  330 . As shown, the same cache entries  305 - 320  are still stored in cache  300 . 
       FIG.  4    illustrates a process  400  for caching data based on greenhouse gas data according to some embodiments. In some embodiments, computing system  110  performs process  400 . Process  400  begins by receiving, at  410  a first set of data and a first greenhouse gas emission value associated with the first set of data. Referring to  FIGS.  1  and  3 B , computing system  110  can receive from API manager  140  the string “red” and an associated greenhouse gas emission value 0.006. 
     Next, process  400  stores, at  420 , in a cache of the device, the first set of data and the first greenhouse gas emission value. Referring to  FIGS.  1  and  3 C  as an example, cache manager  120  stores cache entry  315 , which includes the string “red” and an associated greenhouse gas emission value 0.006, in cache  300 . Process  400  then receives, at  430 , a second set of data and a second greenhouse gas emission value associated with the second set of data. Referring to  FIGS.  1  and  3 C , computing system  110  may receive from API manager  140  the string “purple” and an associated greenhouse gas emission value 0.005. 
     At  440 , process  400  stores, in the cache of the device, the second set of data and the second greenhouse gas emission value. Referring to  FIGS.  1  and  3 D  as an example, cache manager  120  stores cache entry  320 , which includes the string “purple” and an associated greenhouse gas emission value 0.005, in cache  300 . Then, process  400  receives, at  450 , a third set of data and a third greenhouse gas emission value associated with the third set of data. Referring to  FIGS.  1  and  3 D , computing system  110  may receive from API manager  140  the string “blue” and an associated greenhouse gas emission value 0.01. 
     Next, process  400  determines, at  460 , one of the first and second sets of data to remove from the cache of the device based on the first greenhouse gas emission value and the second greenhouse gas emission value. Referring to  FIGS.  1  and  3 E  as an example, cache manager  120  determines how to process cache entry  325  by determining the cache entry among cache entries  305 - 325  having the smallest greenhouse gas emission value. 
     Finally, process  400  replaces, at  470 , in the cache of the device, the one of the first and second sets of data and the corresponding first or second greenhouse gas emission value with the third set of data and the third greenhouse gas emission value. Referring to  FIGS.  1  and  3 E  as an example, if the determined cache entry is cache entry  325 , cache manager  120  drops cache entry  325 . Otherwise, cache manager  120  replaces the determined cache entry with cache entry  325  in a manner that maintains the order of the cache entries from smallest to largest. Here, cache manager  120  determines that cache entry  310  has the smallest greenhouse gas emission value among cache entries  305 - 325  cache manager  120  replaces cache entry  310  with cache entry  325 , which includes the string “blue” and an associated greenhouse gas emission value 0.01, in cache  300 . 
     The examples described above by reference to  FIGS.  1 - 4    show a technique for caching data based on greenhouse gas emission values. One of ordinary skill in the art will appreciate that such a technique can be applied to any type of caching mechanism. For example, the data caching technique may be applied to any types of software caches (e.g., database/database management system (DBMS) caching, web caching, etc.) as well as any types of hardware caches (e.g., processor memory caching (e.g., L2 memory caching, L3 memory caching, L4 memory caching, etc.), page/disk caching, etc.). 
       FIG.  5    illustrates an exemplary computer system  500  for implementing various embodiments described above. For example, computer system  500  may be used to implement client device  105 , computing system  110 , and computing system  135 . Computer system  500  may be a desktop computer, a laptop, a server computer, or any other type of computer system or combination thereof. Some or all elements of configuration manager  115 , cache manager  120 , API manager  140 , or combinations thereof can be included or implemented in computer system  500 . In addition, computer system  500  can implement many of the operations, methods, and/or processes described above (e.g., process  400 ). As shown in  FIG.  5   , computer system  500  includes processing subsystem  502 , which communicates, via bus subsystem  526 , with input/output (I/O) subsystem  508 , storage subsystem  510  and communication subsystem  524 . 
     Bus subsystem  526  is configured to facilitate communication among the various components and subsystems of computer system  500 . While bus subsystem  526  is illustrated in  FIG.  5    as a single bus, one of ordinary skill in the art will understand that bus subsystem  526  may be implemented as multiple buses. Bus subsystem  526  may be any of several types of bus structures (e.g., a memory bus or memory controller, a peripheral bus, a local bus, etc.) using any of a variety of bus architectures. Examples of bus architectures may include an Industry Standard Architecture (ISA) bus, a Micro Channel Architecture (MCA) bus, an Enhanced ISA (EISA) bus, a Video Electronics Standards Association (VESA) local bus, a Peripheral Component Interconnect (PCI) bus, a Universal Serial Bus (USB), etc. 
     Processing subsystem  502 , which can be implemented as one or more integrated circuits (e.g., a conventional microprocessor or microcontroller), controls the operation of computer system  500 . Processing subsystem  502  may include one or more processors  504 . Each processor  504  may include one processing unit  506  (e.g., a single core processor such as processor  504 - 1 ) or several processing units  506  (e.g., a multicore processor such as processor  504 - 2 ). In some embodiments, processors  504  of processing subsystem  502  may be implemented as independent processors while, in other embodiments, processors  504  of processing subsystem  502  may be implemented as multiple processors integrate into a single chip or multiple chips. Still, in some embodiments, processors  504  of processing subsystem  502  may be implemented as a combination of independent processors and multiple processors integrated into a single chip or multiple chips. 
     In some embodiments, processing subsystem  502  can execute a variety of programs or processes in response to program code and can maintain multiple concurrently executing programs or processes. At any given time, some or all of the program code to be executed can reside in processing subsystem  502  and/or in storage subsystem  510 . Through suitable programming, processing subsystem  502  can provide various functionalities, such as the functionalities described above by reference to process  400 . 
     I/O subsystem  508  may include any number of user interface input devices and/or user interface output devices. User interface input devices may include a keyboard, pointing devices (e.g., a mouse, a trackball, etc.), a touchpad, a touch screen incorporated into a display, a scroll wheel, a click wheel, a dial, a button, a switch, a keypad, audio input devices with voice recognition systems, microphones, image/video capture devices (e.g., webcams, image scanners, barcode readers, etc.), motion sensing devices, gesture recognition devices, eye gesture (e.g., blinking) recognition devices, biometric input devices, and/or any other types of input devices. 
     User interface output devices may include visual output devices (e.g., a display subsystem, indicator lights, etc.), audio output devices (e.g., speakers, headphones, etc.), etc. Examples of a display subsystem may include a cathode ray tube (CRT), a flat-panel device (e.g., a liquid crystal display (LCD), a plasma display, etc.), a projection device, a touch screen, and/or any other types of devices and mechanisms for outputting information from computer system  500  to a user or another device (e.g., a printer). 
     As illustrated in  FIG.  5   , storage subsystem  510  includes system memory  512 , computer-readable storage medium  520 , and computer-readable storage medium reader  522 . System memory  512  may be configured to store software in the form of program instructions that are loadable and executable by processing subsystem  502  as well as data generated during the execution of program instructions. In some embodiments, system memory  512  may include volatile memory (e.g., random access memory (RAM)) and/or non-volatile memory (e.g., read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), flash memory, etc.). System memory  512  may include different types of memory, such as static random access memory (SRAM) and/or dynamic random access memory (DRAM). System memory  512  may include a basic input/output system (BIOS), in some embodiments, that is configured to store basic routines to facilitate transferring information between elements within computer system  500  (e.g., during start-up). Such a BIOS may be stored in ROM (e.g., a ROM chip), flash memory, or any other type of memory that may be configured to store the BIOS. 
     As shown in  FIG.  5   , system memory  512  includes application programs  514 , program data  516 , and operating system (OS)  518 . OS  518  may be one of various versions of Microsoft Windows, Apple Mac OS, Apple OS X, Apple macOS, and/or Linux operating systems, a variety of commercially-available UNIX or UNIX-like operating systems (including without limitation the variety of GNU/Linux operating systems, the Google Chrome® OS, and the like) and/or mobile operating systems such as Apple iOS, Windows Phone, Windows Mobile, Android, BlackBerry OS, Blackberry  10 , and Palm OS, WebOS operating systems. 
     Computer-readable storage medium  520  may be a non-transitory computer-readable medium configured to store software (e.g., programs, code modules, data constructs, instructions, etc.). Many of the components (e.g., configuration manager  115 , cache manager  120 , and API manager  140 ) and/or processes (e.g., process  400 ) described above may be implemented as software that when executed by a processor or processing unit (e.g., a processor or processing unit of processing subsystem  502 ) performs the operations of such components and/or processes. Storage subsystem  510  may also store data used for, or generated during, the execution of the software. 
     Storage subsystem  510  may also include computer-readable storage medium reader  522  that is configured to communicate with computer-readable storage medium  520 . Together and, optionally, in combination with system memory  512 , computer-readable storage medium  520  may comprehensively represent remote, local, fixed, and/or removable storage devices plus storage media for temporarily and/or more permanently containing, storing, transmitting, and retrieving computer-readable information. 
     Computer-readable storage medium  520  may be any appropriate media known or used in the art, including storage media such as volatile, non-volatile, removable, non-removable media implemented in any method or technology for storage and/or transmission of information. Examples of such storage media includes RAM, ROM, EEPROM, flash memory or other memory technology, compact disc read-only memory (CD-ROM), digital versatile disk (DVD), Blu-ray Disc (BD), magnetic cassettes, magnetic tape, magnetic disk storage (e.g., hard disk drives), Zip drives, solid-state drives (SSD), flash memory card (e.g., secure digital (SD) cards, CompactFlash cards, etc.), USB flash drives, or any other type of computer-readable storage media or device. 
     Communication subsystem  524  serves as an interface for receiving data from, and transmitting data to, other devices, computer systems, and networks. For example, communication subsystem  524  may allow computer system  500  to connect to one or more devices via a network (e.g., a personal area network (PAN), a local area network (LAN), a storage area network (SAN), a campus area network (CAN), a metropolitan area network (MAN), a wide area network (WAN), a global area network (GAN), an intranet, the Internet, a network of any number of different types of networks, etc.). Communication subsystem  524  can include any number of different communication components. Examples of such components may include radio frequency (RF) transceiver components for accessing wireless voice and/or data networks (e.g., using cellular technologies such as 2G, 3G, 4G, 5G, etc., wireless data technologies such as Wi-Fi, Bluetooth, ZigBee, etc., or any combination thereof), global positioning system (GPS) receiver components, and/or other components. In some embodiments, communication subsystem  524  may provide components configured for wired communication (e.g., Ethernet) in addition to or instead of components configured for wireless communication. 
     One of ordinary skill in the art will realize that the architecture shown in  FIG.  5    is only an example architecture of computer system  500 , and that computer system  500  may have additional or fewer components than shown, or a different configuration of components. The various components shown in  FIG.  5    may be implemented in hardware, software, firmware or any combination thereof, including one or more signal processing and/or application specific integrated circuits. 
       FIG.  6    illustrates an exemplary computing device  600  for implementing various embodiments described above. For example, computing device  600  may be used to implement client device  105 . Computing device  600  may be a cellphone, a smartphone, a wearable device, an activity tracker or manager, a tablet, a personal digital assistant (PDA), a media player, or any other type of mobile computing device or combination thereof. As shown in  FIG.  6   , computing device  600  includes processing system  602 , input/output (I/O) system  608 , communication system  618 , and storage system  620 . These components may be coupled by one or more communication buses or signal lines. 
     Processing system  602 , which can be implemented as one or more integrated circuits (e.g., a conventional microprocessor or microcontroller), controls the operation of computing device  600 . As shown, processing system  602  includes one or more processors  604  and memory  606 . Processors  604  are configured to run or execute various software and/or sets of instructions stored in memory  606  to perform various functions for computing device  600  and to process data. 
     Each processor of processors  604  may include one processing unit (e.g., a single core processor) or several processing units (e.g., a multicore processor). In some embodiments, processors  604  of processing system  602  may be implemented as independent processors while, in other embodiments, processors  604  of processing system  602  may be implemented as multiple processors integrate into a single chip. Still, in some embodiments, processors  604  of processing system  602  may be implemented as a combination of independent processors and multiple processors integrated into a single chip. 
     Memory  606  may be configured to receive and store software (e.g., operating system  622 , applications  624 , I/O module  626 , communication module  628 , etc. from storage system  620 ) in the form of program instructions that are loadable and executable by processors  604  as well as data generated during the execution of program instructions. In some embodiments, memory  606  may include volatile memory (e.g., random access memory (RAM)), non-volatile memory (e.g., read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), flash memory, etc.), or a combination thereof. 
     I/O system  608  is responsible for receiving input through various components and providing output through various components. As shown for this example, I/O system  608  includes display  610 , one or more sensors  612 , speaker  614 , and microphone  616 . Display  610  is configured to output visual information (e.g., a graphical user interface (GUI) generated and/or rendered by processors  604 ). In some embodiments, display  610  is a touch screen that is configured to also receive touch-based input. Display  610  may be implemented using liquid crystal display (LCD) technology, light-emitting diode (LED) technology, organic LED (OLED) technology, organic electro luminescence (OEL) technology, or any other type of display technologies. Sensors  612  may include any number of different types of sensors for measuring a physical quantity (e.g., temperature, force, pressure, acceleration, orientation, light, radiation, etc.). Speaker  614  is configured to output audio information and microphone  616  is configured to receive audio input. One of ordinary skill in the art will appreciate that I/O system  608  may include any number of additional, fewer, and/or different components. For instance, I/O system  608  may include a keypad or keyboard for receiving input, a port for transmitting data, receiving data and/or power, and/or communicating with another device or component, an image capture component for capturing photos and/or videos, etc. 
     Communication system  618  serves as an interface for receiving data from, and transmitting data to, other devices, computer systems, and networks. For example, communication system  618  may allow computing device  600  to connect to one or more devices via a network (e.g., a personal area network (PAN), a local area network (LAN), a storage area network (SAN), a campus area network (CAN), a metropolitan area network (MAN), a wide area network (WAN), a global area network (GAN), an intranet, the Internet, a network of any number of different types of networks, etc.). Communication system  618  can include any number of different communication components. Examples of such components may include radio frequency (RF) transceiver components for accessing wireless voice and/or data networks (e.g., using cellular technologies such as 2G, 3G, 4G, 5G, etc., wireless data technologies such as Wi-Fi, Bluetooth, ZigBee, etc., or any combination thereof), global positioning system (GPS) receiver components, and/or other components. In some embodiments, communication system  618  may provide components configured for wired communication (e.g., Ethernet) in addition to or instead of components configured for wireless communication. 
     Storage system  620  handles the storage and management of data for computing device  600 . Storage system  620  may be implemented by one or more non-transitory machine-readable mediums that are configured to store software (e.g., programs, code modules, data constructs, instructions, etc.) and store data used for, or generated during, the execution of the software. 
     In this example, storage system  620  includes operating system  622 , one or more applications  624 , I/O module  626 , and communication module  628 . Operating system  622  includes various procedures, sets of instructions, software components and/or drivers for controlling and managing general system tasks (e.g., memory management, storage device control, power management, etc.) and facilitates communication between various hardware and software components. Operating system  622  may be one of various versions of Microsoft Windows, Apple Mac OS, Apple OS X, Apple macOS, and/or Linux operating systems, a variety of commercially-available UNIX or UNIX-like operating systems (including without limitation the variety of GNU/Linux operating systems, the Google Chrome® OS, and the like) and/or mobile operating systems such as Apple iOS, Windows Phone, Windows Mobile, Android, BlackBerry OS, Blackberry  10 , and Palm OS, WebOS operating systems. 
     Applications  624  can include any number of different applications installed on computing device  600 . Examples of such applications may include a browser application, an address book application, a contact list application, an email application, an instant messaging application, a word processing application, JAVA-enabled applications, an encryption application, a digital rights management application, a voice recognition application, location determination application, a mapping application, a music player application, etc. 
     I/O module  626  manages information received via input components (e.g., display  610 , sensors  612 , and microphone  616 ) and information to be outputted via output components (e.g., display  610  and speaker  614 ). Communication module  628  facilitates communication with other devices via communication system  618  and includes various software components for handling data received from communication system  618 . 
     One of ordinary skill in the art will realize that the architecture shown in  FIG.  6    is only an example architecture of computing device  600 , and that computing device  600  may have additional or fewer components than shown, or a different configuration of components. The various components shown in  FIG.  6    may be implemented in hardware, software, firmware or any combination thereof, including one or more signal processing and/or application specific integrated circuits. 
       FIG.  7    illustrates an exemplary system  700  for implementing various embodiments described above. For example, one of the client devices  702 - 708  may be used to implement client device  105  and cloud computing system may be used to implement computing system  110  and computing system  135 . As shown, system  700  includes client devices  702 - 708 , one or more networks  710 , and cloud computing system  712 . Cloud computing system  712  is configured to provide resources and data to client devices  702 - 708  via networks  710 . In some embodiments, cloud computing system  700  provides resources to any number of different users (e.g., customers, tenants, organizations, etc.). Cloud computing system  712  may be implemented by one or more computer systems (e.g., servers), virtual machines operating on a computer system, or a combination thereof. 
     As shown, cloud computing system  712  includes one or more applications  714 , one or more services  716 , and one or more databases  718 . Cloud computing system  700  may provide applications  714 , services  716 , and databases  718  to any number of different customers in a self-service, subscription-based, elastically scalable, reliable, highly available, and secure manner. 
     In some embodiments, cloud computing system  700  may be adapted to automatically provision, manage, and track a customer&#39;s subscriptions to services offered by cloud computing system  700 . Cloud computing system  700  may provide cloud services via different deployment models. For example, cloud services may be provided under a public cloud model in which cloud computing system  700  is owned by an organization selling cloud services and the cloud services are made available to the general public or different industry enterprises. As another example, cloud services may be provided under a private cloud model in which cloud computing system  700  is operated solely for a single organization and may provide cloud services for one or more entities within the organization. The cloud services may also be provided under a community cloud model in which cloud computing system  700  and the cloud services provided by cloud computing system  700  are shared by several organizations in a related community. The cloud services may also be provided under a hybrid cloud model, which is a combination of two or more of the aforementioned different models. 
     In some instances, any one of applications  714 , services  716 , and databases  718  made available to client devices  702 - 708  via networks  710  from cloud computing system  712  is referred to as a “cloud service.” Typically, servers and systems that make up cloud computing system  712  are different from the on-premises servers and systems of a customer. For example, cloud computing system  712  may host an application and a user of one of client devices  702 - 708  may order and use the application via networks  710 . 
     Applications  714  may include software applications that are configured to execute on cloud computing system  712  (e.g., a computer system or a virtual machine operating on a computer system) and be accessed, controlled, managed, etc. via client devices  702 - 708 . In some embodiments, applications  714  may include server applications and/or mid-tier applications (e.g., HTTP (hypertext transport protocol) server applications, FTP (file transfer protocol) server applications, CGI (common gateway interface) server applications, JAVA server applications, etc.). Services  716  are software components, modules, application, etc. that are configured to execute on cloud computing system  712  and provide functionalities to client devices  702 - 708  via networks  710 . Services  716  may be web-based services or on-demand cloud services. 
     Databases  718  are configured to store and/or manage data that is accessed by applications  714 , services  716 , and/or client devices  702 - 708 . For instance, storages  125 ,  130 , and  145  may be stored in databases  718 . Databases  718  may reside on a non-transitory storage medium local to (and/or resident in) cloud computing system  712 , in a storage-area network (SAN), on a non-transitory storage medium local located remotely from cloud computing system  712 . In some embodiments, databases  718  may include relational databases that are managed by a relational database management system (RDBMS). Databases  718  may be a column-oriented databases, row-oriented databases, or a combination thereof. In some embodiments, some or all of databases  718  are in-memory databases. That is, in some such embodiments, data for databases  718  are stored and managed in memory (e.g., random access memory (RAM)). 
     Client devices  702 - 708  are configured to execute and operate a client application (e.g., a web browser, a proprietary client application, etc.) that communicates with applications  714 , services  716 , and/or databases  718  via networks  710 . This way, client devices  702 - 708  may access the various functionalities provided by applications  714 , services  716 , and databases  718  while applications  714 , services  716 , and databases  718  are operating (e.g., hosted) on cloud computing system  700 . Client devices  702 - 708  may be computer system  500  or computing device  600 , as described above by reference to  FIGS.  5  and  6   , respectively. Although system  700  is shown with four client devices, any number of client devices may be supported. 
     Networks  710  may be any type of network configured to facilitate data communications among client devices  702 - 708  and cloud computing system  712  using any of a variety of network protocols. Networks  710  may be a personal area network (PAN), a local area network (LAN), a storage area network (SAN), a campus area network (CAN), a metropolitan area network (MAN), a wide area network (WAN), a global area network (GAN), an intranet, the Internet, a network of any number of different types of networks, etc. 
     The above description illustrates various embodiments of the present disclosure along with examples of how aspects of the present disclosure may be implemented. The above examples and embodiments should not be deemed to be the only embodiments, and are presented to illustrate the flexibility and advantages of various embodiments of the present disclosure as defined by the following claims. Based on the above disclosure and the following claims, other arrangements, embodiments, implementations and equivalents will be evident to those skilled in the art and may be employed without departing from the spirit and scope of the present disclosure as defined by the claims.