Abstract:
Techniques introduced here enable cloud-based file prefetching on electronic devices. The electronic devices store certain files on a remote storage server and preload some of the files locally to include file access efficiency. File access patterns on the electronic devices are analyzed collectively and efficiently using a cloud service to detect global access patterns and help determine which files to preload on each of the electronic devices.

Description:
PRIORITY CLAIM 
       [0001]    This application claims to the benefit of U.S. Provisional Patent Application No. 61/708,794, entitled “CLOUD COMPUTING INTEGRATED OPERATING SYSTEM”, which was filed on Oct. 2, 2012 and is incorporated by reference herein in its entirety. 
     
    
     FIELD OF THE INVENTION 
       [0002]    At least one embodiment of the present invention pertains to cloud computing and file prefetching, and more particularly, to cloud-based file prefetching on electronic devices. 
       BACKGROUND 
       [0003]    Today, people perform a large number of activities using a variety of electronic devices. For example, people watch videos on their desktops or play games on their cell phones. It would be helpful to ensure that when one is ready to perform an activity using an electronic device, the digital content necessary for performing the activity is available on the electronic device. 
       SUMMARY 
       [0004]    Techniques introduced here enable cloud-based file prefetching on electronic devices. The electronic devices store certain files on a remote storage server and preload some of the files locally to include file access efficiency. File access patterns on the electronic devices are analyzed collectively and efficiently using a cloud service to detect global access patterns and help determine which files to preload on each of the electronic devices. 
         [0005]    Using the access patterns, the cloud service can instruct the electronic devices to preload the files that have high probability to be used by the devices in future. Such increased hit rates for the cache of the preloaded files improve the file access efficiency and reduce data access lag for the electronic devices. 
         [0006]    In accordance with the techniques introduced here, therefore, a method performed by a processor on a server that is connected to a plurality of client devices over networks is provided. The method receives a usage profile from one of the client devices. The usage profile contains access statistics of files that have been accessed by the client device. The method further analyzes usage profiles received from more than one of the client devices collectively to generate a prefetching profile for the client device. The prefetching profile specifies files that are likely to be accessed in the future by the client device. Then the method sends the prefetching profile to the client device. 
         [0007]    In accordance with the techniques introduced here, therefore, another method for cloud-based file prefetching is also provided. The method sends a usage profile to the server. The usage profile contains access statistics of files that have been accessed by the client device. The method then receives a prefetching profile from the server. The prefetching profile specifies files that are likely to be accessed by the client device in the future based on a collective analysis of usage profiles sent by more than one of the client devices. 
         [0008]    In accordance with the techniques introduced here, therefore, a method performed by a processor on a server that is connected to at least one client device over a network is also provided. The method receives usage profiles from a client device. Each of the usage profiles contains access statistics of files that have been accessed by one of multiple computer applications executed at the client device. The method then analyzes the usage profiles collectively to generate a prefetching profile for the client device. The prefetching profile specifies files that are likely to be accessed in the future by the client device. The method sends the prefetching profile to the client device so that the client device can prefetching files from a storage server based on the prefetching profile. 
         [0009]    Alternatively, the server monitors the client device for specifics. e.g. storage size, storage usage, file access patterns, etc. Based on the monitored specifics, the server can a strong indication to the client device instructing the client device to cache a particular set of files. The server can also send to the client device a caching priority set (e.g. as a file or a message). The caching priority set includes cache scores assigned by the server for each file of the client device. The client device can choose to prioritize prefetching the files based on the cache scores. The caching priority set can be unique per client device, per device class (e.g., a class of mobile phones, a class tablet computers, etc), or per user account. 
         [0010]    In accordance with the techniques introduced here, therefore, a client device connected to a server is also provided. The client includes a sending unit and a receiving unit. The sending unit sends a usage profile to the server. The usage profile contains access statistics of files that have been accessed by the client device. The receiving unit receives a prefetching profile from the server, wherein the prefetching profile specifies files that are likely to be accessed by the client device in the future based on a collective analysis of usage profiles sent by more than one of client devices connected to the server. 
         [0011]    Other aspects of the technology introduced here will be apparent from the accompanying figures and from the detailed description which follows. 
     
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
         [0012]    These and other objects, features and characteristics of the present invention will become more apparent to those skilled in the art from a study of the following detailed description in conjunction with the appended claims and drawings, all of which form a part of this specification. In the drawings: 
           [0013]      FIG. 1  contains a diagram illustrating an example environment in which cloud-based file prefetching on electronic devices can be carried out. 
           [0014]      FIG. 2  contains a diagram illustrating an example operating system of an electronic device. 
           [0015]      FIG. 3  contains a block diagram illustrating example components of a local prefetching module. 
           [0016]      FIG. 4  contains a diagram illustrating an example usage profile maintained by a local profile manager. 
           [0017]      FIG. 5  contains a diagram illustrating an example prefetching profile received by a local profile manager. 
           [0018]      FIG. 6  contains a block diagram illustrating example components of a global prefetching module hosted by a prefetching server. 
           [0019]      FIG. 7  contains a flowchart illustrating an example operation of a global profile manager of the global prefetching module. 
           [0020]      FIG. 8  contains a flowchart illustrating an example operation of the local prefetching module. 
           [0021]      FIG. 9  contains a high-level block diagram showing an example architecture of a computer server, which may represent any computer described herein. 
       
    
    
     DETAILED DESCRIPTION 
       [0022]    References in this specification to “an embodiment,” “one embodiment,” or the like, mean that the particular feature, structure, or characteristic being described is included in at least one embodiment of the present invention. Occurrences of such phrases in this specification do not all necessarily refer to the same embodiment, however. 
         [0023]      FIG. 1  contains a diagram illustrating an example environment in which cloud-based file prefetching on electronic devices can be carried out. In one embodiment, a cloud service  110  comprises a cluster having nodes  112  interconnected with each other by a network. Each of the nodes  112  contains one or more processors  114  and storage devices  116 . The storage devices  116  can include optical disk storage, RAM, ROM, EEPROM, flash memory, phase change memory, magnetic cassettes, magnetic tapes, magnetic disk storage or any other computer storage medium which can be used to store the desired information. 
         [0024]    In one embodiment, the cloud service  110  can store computer applications and application data used by electronic devices  130 . The computer applications can include applications for general productivity and information retrieval, such as email, calendar, and applications in other categories, such as mobile games, GPS services, banking, and any other categories as contemplated by a person having ordinary skill in the art. The cloud service  110  can also store usage profiles and store prefetching profiles. Each usage profile characterizes activities performed by a user using one of the electronic devices  130  in terms of required files. Each prefetching profile specifies files to be prefetched on the electronic device in anticipation of the user performing activities which require the files. The cloud service  110  can be responsible for making sure that the metadata and the actual content data of the files are persistent in the client-server distributed storage system. 
         [0025]    An electronic device  130  can be a desktop computer, a laptop computer, a tablet computer, an automobile computer, a game console, a smart phone, a personal digital assistant, or any other device capable of running computer applications. In one embodiment, the electronic device  130  includes one primary store  136  to store computer applications, the installation of which is typical or requested by the user, application data created or requested by the user, user data, usage profiles, prefetching profiles, meta-data, and so on. The electronic device  130  also includes a secondary store  138  to store additional computer applications and application data that are not yet available in the primary store  136  but are expected to be requested by the user in the near future. The primary and secondary stores can similarly be any computer storage medium which can be used to store desired information. 
         [0026]    A prefetching server  120  can be any standalone apparatus or system which has sufficient network bandwidth, data capacity, computational resources, and so on. In one embodiment, a prefetching server  120  can include a local storage device  122  to store analytical algorithms to be applied to usage profiles. The local storage device  112  can similarly be any computer storage medium which can be used to store desired information. In an alternative embodiment, the prefetching server  120  does not include a local storage device. The metadata of the files can be stored in memory components of the prefetching server  120  or electronic devices  130 . Each of the networks  140  may be a cellular network, a telephonic network, an open network, such as the Internet, a private network, such as an intranet and/or the extranet, or any other network known to a person having ordinary skill in the art. 
         [0027]    Each of the electronic devices hosts an operating system which includes a local prefetching module.  FIG. 2  contains a diagram illustrating an example operating system  200 . In one embodiment, the operating system  200  includes a kernel  204 . The kernel  204  controls the computer applications running on top of the kernel  204 . It provides interfaces to the hardware of the electronic device, thereby isolating the computer applications from the hardware. It may also include one or more intervening sources that can affect the execution of a computer application. For example, the kernel  204  may include a network I/O module  206 , a file I/O module  208 , a multi-threading module  210 , a user input module  214 , a system interrupts module  216 , and a shared memory access module  218 . 
         [0028]    In one embodiment, the local prefetching module  230  also runs on top of the kernel  204 . As one example, the local prefetching module  230  can run in a user space file system (e.g. FUSE) on top of a Linux kernel. As another example, the local prefetching module  230  runs in a kernel file system. Alternatively, the local prefetching module  230  can be implemented as part of a customized kernel  204 . 
         [0029]      FIG. 3  contains a block diagram illustrating example components of a local prefetching module  300  for an electronic device. In one embodiment, the local prefetching module  300  includes a local data manager  302 , a local profile manager  304  and a request handler  306 . 
         [0030]    In one embodiment, the local profile manager  304  maintains one or more usage profiles in the primary store and sends them to the prefetching server. It can send the usage profiles periodically, as soon as there is an update, in response to a request from the prefetching server, and so on.  FIG. 4  contains a diagram illustrating an example usage profile. A usage profile can contain any information about the activities performed on the electronic device in terms of required files. In one embodiment, the usage profile contains any information on access to the files stored in the primary store. Such information can include the name of a file, the type of the file (partial computer application, full computer application, application data, etc.), the size of the file, the time of access to the file, the type of access (read, write, etc.), the location of the electronic device at the time of access, the identification of an application or process that accessed the file, and so on. 
         [0031]    In one embodiment, the local profile manager  304  also receives prefetching profiles from the prefetching server and stores them in the primary store. It can also send requests to the prefetching server for the prefetching profiles periodically, when it has extra bandwidth available, and so on.  FIG. 5  contains a diagram illustrating an example prefetching profile. A prefetching profile specifies files to be preloaded on an electronic device in anticipation of the user performing activities which require the files. For each of the specified files, information regarding the name, the type, the size, the access type, the likelihood that it is to be accessed within a predetermined timeframe, etc. can be included. 
         [0032]    In one embodiment, the local prefetching module  300  can take the file access rights into account when the module  300  determines the files to be prefetched. For instance, a subset of files in one device can be only accessible by one application running on the device. The local prefetching module  300  can determine whether to prefetching any file from that subset based on the status of the application (e.g., stopped, running, sleeping, idling, etc.). There also can be file access rights depending on access statuses of other files. For instance, a file B is only accessible after file A is accessed; another file C is only accessible after file B is accessed. The local prefetching module  300  can determine that there is no need to prefetch file C if the file B has not been accessed, and that there is no need to prefetch files B and C if the file A has not been accessed. 
         [0033]    In one embodiment, the local data manager  302  sends requests to the cloud service to retrieve specific computer applications or application data. It can also send requests to whichever separate servers are hosting the computer applications or application data. In addition, the local data manager  302  receives the requested computer applications or application data and stores them in the primary store or the secondary store on the electronic device. The pace of sending the requests and storing the requested computer applications or application data can depend on where the requested computer applications or application data are to be stored, When they are to be stored in the primary store on the electronic device, it generally means that they are to be accessed immediately and the sending and storing could be performed without much delay, while when they are to be stored in the secondary store, it generally means that they are likely to be accessed in the near future and the sending and storing can be performed with some flexibility in timing. 
         [0034]    In one embodiment, given a prefetching profile, the local data manager  302  determines which requests for file retrieval to send and in what order. It may first filter the prefetching profile to remove any file that is already present in the primary store. Next, in one example, it may decide that requests are to be sent for all the files specified in the prefetching profile as the number of such files is small. In another example, it may decide that requests would first be sent for a predetermined number of files with the highest likelihoods or with the shortest time frames. On the other hand, when the size of the secondary store is limited, the local data manager  302  can enforce overwrite policies, such as cache algorithms known to someone of ordinary skill in the art. 
         [0035]    In one embodiment, the request handler  306  accepts user requests for certain files and ultimately serves those files from the primary store. In general, it may first look in the primary store, which has pre installed or previously installed files. If the requested file is not there, it looks in the secondary store, which has prefetched files. It saves the requested file in the primary store before serving it in response to user requests. 
         [0036]    The prefetching server hosts a global prefetching module.  FIG. 6  contains a block diagram illustrating example components of the global prefetching module  600 . In one embodiment, the global prefetching module  600  includes a global data manager  602 , a global profile manager  604  and an analysis engine  606 . 
         [0037]    In one embodiment, the global data manager  602  receives requests for computer applications or application data from the electronic devices and forwards them to the cloud service or other sources. The global data manager  602  also receives the requested computer applications or application data from the cloud service or other sources and forwards them to the electronic devices. The pace of forwarding the requests and the requested computer applications or application data can similarly depend on where the requested computer applications or application data are to be stored, as discussed above. 
         [0038]    In one embodiment, the global profile manager  604  receives usage profiles from the electronic devices and forwards them to the cloud service for storage. It can forward a usage profile to the cloud service immediately upon receiving it from an electronic device. It can also forward the usage profiles received from an electronic device according to a preset schedule. In addition, it can forward the usage profiles received from multiple electronic devices in batches of a predetermined size or periodically. The global profile manager also maintains a global index of usage profiles in the local storage device indicating how to access the usage profiles stored with the cloud service. 
         [0039]    In one embodiment, the global profile manager  604  also receives prefetching profiles from the cloud service and forwards them to the electronic devices. Similarly, it can forward a prefetching profile to the appropriate electronic device immediately or in response to a request from the electronic device for a prefetching profile. It can also wait to forward the prefetching profile together with a response to the next request from the electronic device, such as a request to retrieve certain computer application or application data. In addition, it can forward the prefetching profiles to one or more electronic devices according to a predetermined schedule. 
         [0040]    In one embodiment, the analysis engine  606  manages analytical algorithms, the input to which are usage profiles and the output from which are prefetching profiles. Many types of analysis can be performed on the usage profiles, individually and collectively, to detect usage patterns. According to various embodiments, the usage profiles may indicate that on an electronic device, a computer application or a part thereof is often executed or a piece of application data is often used on a certain day or at a certain time, when the computer application or the piece of application data has a certain size, immediately before or after another computer application or piece of application data, when the electronic device is at a certain location, when another electronic device is connected to the prefetching server, etc. The lack of execution or use can also be incorporated into the usage patterns. 
         [0041]    Some example usage patterns are described as follows. Different levels of a game may often be accessed in an increasing order. The last few very difficult levels may never be accessed, and the levels before the currently accessed levels may also never be accessed again. The photos or soundtracks in an album may often be accessed in the listed order. More recent albums may be accessed more frequently. Larger files may often be accessed on devices with better resources. Business-related files may often be accessed during the day or on an electronic device in the office, while files pertaining to entertainment may often be accessed at night or on an electronic device at home. Best-selling books in a city may be frequently accessed in that city and surrounding cities. Therefore, different files can be associated with different access patterns (as referred to as access statistics), which can be learned from the usage profiles without knowing the nature of the files. 
         [0042]    In one embodiment, each analytical algorithm takes into consideration one or more of the usage patterns and selects a set of files for an electronic device that are likely to be accessed in the near future on the electronic device. It can assign different weights to different usage patterns. For example, it can prefer usage patterns reflecting more recent activities across electronic devices. It can also give more weight to usage patterns specific to the electronic device and/or those electronic devices owned by users similar to the owner of the electronic device. Furthermore, it can apply any classification, pattern-recognition and other techniques known to someone of ordinary skill in the art. 
         [0043]    In one embodiment, the analysis engine  606  chooses one of the analytic algorithms, based on predetermined rules, user input, etc., and submits a request to the cloud service for executing the chosen analytic algorithm. In response, the cloud service executes the chosen analytic algorithm on the stored usage profiles in a distributed manner and generates resulting prefetching profiles for the electronic devices. The analysis engine  606  can submit a request as soon as a predetermined number of updated usage profiles are stored with the cloud service, according to a preset schedule, when the rate of file retrieval is high indicating a low degree of prefetching success, and so on. 
         [0044]      FIG. 7  contains a flowchart illustrating an example operation of a global profile manager. In one embodiment, the global profile manager receives usage profiles from the electronic devices at step  702 . It forwards the usage profiles to the cloud service for storage at step  704 . Subsequently, the global profile manager submits a request to execute an analytical algorithm maintained by the analysis engine to the cloud service at step  706 . When the execution is complete, the global profile manager receives prefetching profiles for the electronic devices at step  708 . Finally, it forwards each of the prefetching profiles to the appropriate electronic device at step  710 . 
         [0045]      FIG. 8  contains a flowchart illustrating an example operation of a local prefetching module. In one embodiment, the request handler accepts a user request and determines whether a requested file is present in the primary store at step  802 . If the file is present, it serves the file at step  804 . If the file is not present, it determines whether the file is present in the secondary store at step  806 . If the file is present, it moves the file to the primary store at step  808  and serves the file at step  810 . If the file is not present, the local data manager retrieves the file from a source at step  712  and stores the retrieved file in the primary store at step  714 . 
         [0046]      FIG. 9  contains a high-level block diagram showing an example architecture of a computer, which may represent any electronic device, any server, or any node within a cloud service as described herein. The computer  900  includes one or more processors  910  and memory  920  coupled to an interconnect  930 . The interconnect  930  shown in  FIG. 9  is an abstraction that represents any one or more separate physical buses, point to point connections, or both connected by appropriate bridges, adapters, or controllers. The interconnect  930 , therefore, may include, for example, a system bus, a Peripheral Component Interconnect (PCI) bus or PCI-Express bus, a HyperTransport or industry standard architecture (ISA) bus, a small computer system interface (SCSI) bus, a universal serial bus (USB), IIC (I2C) bus, or an Institute of Electrical and Electronics Engineers (IEEE) standard 1394 bus, also called “Firewire”. 
         [0047]    The processor(s)  910  is/are the central processing unit (CPU) of the computer  900  and, thus, control the overall operation of the computer  900 . In certain embodiments, the processor(s)  910  accomplish this by executing software or firmware stored in memory  920 . The processor(s)  910  may be, or may include, one or more programmable general-purpose or special-purpose microprocessors, digital signal processors (DSPs), programmable controllers, application specific integrated circuits (ASICs), programmable logic devices (PLDs), field-programmable gate arrays (FPGAs), trusted platform modules (TPMs), or the like, or a combination of such devices. 
         [0048]    The memory  920  is or includes the main memory of the computer  900 . The memory  920  represents any form of random access memory (RAM), read-only memory (ROM), flash memory, or the like, or a combination of such devices. In use, the memory  920  may contain code  970  containing instructions according to the techniques disclosed herein. 
         [0049]    Also connected to the processor(s)  910  through the interconnect  930  are a network adapter  940  and a storage adapter  950 . The network adapter  940  provides the computer  900  with the ability to communicate with remote devices, over a network and may be, for example, an Ethernet adapter or Fibre Channel adapter. The network adapter  940  may also provide the computer  900  with the ability to communicate with other computers. The storage adapter  950  allows the computer  900  to access a persistent storage, and may be, for example, a Fibre Channel adapter or SCSI adapter. 
         [0050]    The code  970  stored in memory  920  may be implemented as software and/or firmware to program the processor(s)  910  to carry out actions described above. In certain embodiments, such software or firmware may be initially provided to the computer  900  by downloading it from a remote system through the computer  900  (e.g., via network adapter  940 ). 
         [0051]    The techniques introduced herein can be implemented by, for example, programmable circuitry (e.g., one or more microprocessors) programmed with software and/or firmware, or entirely in special-purpose hardwired circuitry, or in a combination of such forms. Software or firmware for use in implementing the techniques introduced here may be stored on a machine-readable storage medium and may be executed by one or more general-purpose or special-purpose programmable microprocessors. 
         [0052]    A “machine-readable storage medium”, as the term is used herein, includes any mechanism that can store information in a form accessible by a machine (a machine may be, for example, a computer, network device, cellular phone, personal digital assistant (PDA), manufacturing tool, any device with one or more processors, etc.). For example, a machine-accessible storage medium includes recordable/non-recordable media (e.g., read-only memory (ROM); random access memory (RAM); magnetic disk storage media; optical storage media; flash memory devices; etc.), etc. 
         [0053]    In addition to the above mentioned examples, various other modifications and alterations of the invention may be made without departing from the invention. Accordingly, the above disclosure is not to be considered as limiting and the appended claims are to be interpreted as encompassing the true spirit and the entire scope of the invention.