A computer system for optimizing bandwidth usage within a cloud storage system identifies distinct requests to access a particular digital file. When the number of requests exceeds a threshold, the computer system queries a remote directory server for the particular digital file. The query system then receives, from the remote directory server, addresses to data blocks stored within multiple remote storage nodes. The system requests at least a portion of the addressed data blocks. Upon receiving the blocks, the system decodes the particular digital file from the portion of the addressed data blocks. The computer system then stores the decoded digital file within local memory and communicates the local-area network address to the remote directory server.

BACKGROUND

Computing system functionality can be enhanced by a computing systems' ability to be interconnected to other computing systems via network connections. Network connections may include, but are not limited to, connections via wired or wireless Ethernet, cellular connections, or even computer-to-computer connections through serial, parallel, USB, or other connections. The connections allow a computing system to access services at other computing systems and to quickly and efficiently receive application data from other computing systems.

Interconnection of computing systems has facilitated distributed computing systems, such as so-called “cloud” computing systems. In this description, “cloud computing” may be systems or resources for enabling ubiquitous, convenient, on-demand network access to a shared pool of configurable computing resources (e.g., networks, servers, storage, applications, services, etc.) that can be provisioned and released with reduced management effort or service provider interaction. A cloud model can be composed of various characteristics (e.g., on-demand self-service, broad network access, resource pooling, rapid elasticity, measured service, etc.), service models (e.g., Software as a Service (“SaaS”), Platform as a Service (“PaaS”), Infrastructure as a Service (“IaaS”), and deployment models (e.g., private cloud, community cloud, public cloud, hybrid cloud, etc.).

Cloud and remote based service applications are prevalent. Such applications are hosted on public and private remote systems such as clouds and usually offer a set of web based services for communicating back and forth with clients.

Many computers are intended to be used by direct user interaction with the computer. As such, computers have input hardware and software user interfaces to facilitate user interaction. For example, a modern general-purpose computer may include a keyboard, mouse, touchpad, camera, etc. for allowing a user to input data into the computer. In addition, various software user interfaces may be available.

Examples of software user interfaces include graphical user interfaces, text command line based user interfaces, function key or hot key user interfaces, and the like.

In recent years, the use of cloud storage has gained significant popularity due to its ease of use, pervasive access, and security. For example, files stored within the cloud are often available to users through their computers, smart phones, or through any generic web browser. Additionally, files stored within the cloud are often stored within professional quality server farms that utilize various methods of data protection and redundancy, including, but not limited to, RAID configurations, data verification, advanced filesystems, and other similar technologies.

While cloud storage has provided significant benefits to end users, it comes at a high cost in bandwidth and hardware to the cloud providers. Cloud providers are conventionally required to purchase and continually update expensive storage arrays—that must also be redundant. Similarly, cloud providers are conventionally required to purchase and maintain large amounts of bandwidth so that users can quickly download large files that may be stored within their cloud accounts. As such, there is significant interest in addressing the technical challenges relating to efficient cloud storage.

BRIEF SUMMARY

Embodiments disclosed herein include computer systems, methods, and computer readable media for optimizing bandwidth usage within a local-network. An exemplary computer system is configured to identify, within a local-area network, one or more distinct requests to access a particular digital file. Each distinct request is associated with a different user device. When a number of the one or more distinct requests exceeds a threshold, the computer system queries a remote directory server for the particular digital file. The computer system then receives, from the remote directory server, addresses to data blocks stored within multiple remote storage nodes.

The computer system requests, from at least a portion of the remote storage nodes, at least a portion of the addressed data blocks. Upon receiving the data blocks, the computer system decodes the particular digital file from the portion of the addressed data blocks. Decoding the particular digital file comprises rebuilding at least a portion of the particular digital file using parity information associated with the portion of the addressed data blocks.

The computer system stores the decoded digital file within local memory. The local memory is located within the local-area network. Additionally, the decoded digital file is associated with a local-area network address. The computer system then communicates the local-area network address to the remote directory server.

DETAILED DESCRIPTION

Embodiments disclosed herein provide methods and systems for optimizing bandwidth usage within a cloud storage system. In particular, disclosed embodiments intelligently cache and link files locally. The intelligent caching and linking can provide significant benefits to managing bandwidth by intelligently minimizing strain on a local-area network's connection to the Internet.

Disclosed embodiments in computer systems are configured to intelligently select one or more data blocks from multiple remote storage nodes. In at least one embodiment, when a threshold number of requests for a digital file are generated, the computer system retrieves and locally caches one or more data blocks associated with the requested digital file. The computer system may decode the digital file from the one or more data blocks, or alternatively, the computer system may store the encoded one or more data blocks such that the data is still encrypted.

Further, in at least one embodiment, the computer system dynamically adjusts the number of threshold requests required to initiate a local caching of one or more data blocks associated with the digital file. For example, each of the data blocks may be stored at a different remote storage node. Additionally, each remote storage node may have unique bandwidth constraints. As such, some remote storage nodes may provide relatively low latency, fast downloads, while other remote storage nodes may act as bottle necks due to their slow network connections or high latency.

In at least one embodiment, the computer system dynamically adjusts the number of threshold requests required to initiate a local caching of one or more data blocks associated with the digital file on a remote storage node basis. For instance, the computer system may generate different thresholds for one or more of the remote storage nodes based upon the connection speed between the computer system and the remote storage node.

As such, the computer system may identify multiple requests over time for a particular digital file. The computer system may further identify that data blocks associated with the particular digital file are stored on a particular set of remote storage nodes. As the data blocks are downloaded, the computer system monitors the connection speed and latency of each connection to each remote storage node. The computer system sets a per-remote-storage-node threshold based upon the speed and latency of the particular connection. When the threshold is exceeded, the computer system downloads and stores locally the data block from that particular remote storage node. The computer system then updates a remote directory server such that requests from the local-area network for the data block are re-directed to the locally stored data block. Accordingly, in at least one embodiment, the computer system downloads and locally caches only a portion of the data blocks required for reconstructing a digital file.

Turning now to the figures,FIGS. 1 and 2illustrate schematics of an embodiment of a system for optimizing bandwidth usage within a cloud storage system.FIG. 1depicts a hardware-based schematic that illustrates different hardware components within the system, whileFIG. 2illustrates a module-based schematic that illustrates modules within hardware components. As depicted, a mobile computing device100communicates, through a network connection110, with a remote directory server120, an account management server140, and various remote storage nodes130(a-d).

One will understand that the depicted components ofFIGS. 1 and 2are provided for the sake of example and clarity. In various additional or alternative embodiments, different configurations and combinations of components are used. For example, the mobile computing device100can comprise a smart phone, a tablet computer, a laptop computer, a desktop computer, an embedded device, or any other device capable of processing digital information and communicating over a network. Similarly, the account management server140and the remote directory server120may be combined within a single server or distributed between multiple distinct servers.

Additionally, as used herein, a remote storage node comprises individual nodes within a distributed storage system. For example, the remote storage nodes may comprise individual computing units within different respective houses. In particular, the remote storage nodes may comprise a home server or home-based embedded device. For instance, in at least one embodiment, the remote storage nodes comprise home-based media storage devices that are configured to store the home owner's multimedia collection. As such, embodiments disclosed herein are configured to utilize excess space within home-based computing systems by forming a distributed cloud that leverages multiple remote storage nodes.

In at least one embodiment, the mobile computing device100comprises a computer system for optimizing bandwidth usage within a cloud storage system. In particular, the mobile computing device100comprises one or more processors and one or more computer-readable media having stored thereon executable instructions that when executed by the one or more processors configure the computer system to perform various acts. The acts include receiving a request, through an application program interface204, to store a digital file.

In at least one embodiment, the request is generated by a software application206that is executed on the mobile computing device100. For example, the mobile computing device100may execute a photo editing software application206that stores photos within the cloud. To initialize the storage of the photo, the photo editing software application206communicates the file to a storage API204.

Upon receiving the file, or an address to the file, the processor202accesses the file within memory208and encodes the digital file into a set of multiple distinct blocks of data. The multiple distinct blocks of data each comprise a retrievable portion of the digital file, and the set of multiple distinct blocks of data comprises parity information (e.g., error-correction coding). In at least one embodiment, the processor202encodes the data using a Reed-Solomon algorithm. Additionally, in at least one additional or alternative embodiment, before encoding the data file, the processor202encrypts the digital file and stores the associated encryption key locally. Encrypting the file can protect the user's data while the data is stored in the cloud.

In at least one additional or alternative embodiment, the processor202communicates an authentication credential to an account management server140. Upon receiving the authentication credential, a processor244within the account management server140accesses a user database242and validates the user's authentication credential. If the user's authentication credential is valid, the processor244transmits to the mobile computing device100a credential necessary for storing data within the cloud. In particular, in at least one embodiment, after being authenticated at the account management server140, the processor202at the mobile computing device100receives a credential necessary for accessing the remote directory server120. In an additional or alternative embodiment, the processor202receives a credential necessary for accessing one or more of the remote storage nodes130(a-d). Accordingly, in at least one embodiment, the ability to store data within the cloud is controlled by an account management server140.

The processor202then transmits the set of multiple distinct blocks132(a-d) of data to multiple remote storage nodes130(a-d). Specifically, the multiple distinct blocks132(a-d) of data are divided among at least a portion of the remote storage nodes130(a-d). In at least one embodiment, the mobile computing device100stores, within memory208, a list of available remote storage nodes130(a-d). In an additional or alternative embodiment, before transmitting the set of multiple distinct blocks of data132(a-d) to multiple remote storage nodes130(a-d), the processor202requests from the remote directory server120a set of remote storage nodes130(a-d) available for storage and internet protocol addresses122associated with each available remote storage node. Accordingly, there are various different means through which the processor202can identify available remote storage nodes130(a-d).

The remote directory server120utilizes a node tracker component226to identify nodes that are currently available. As used herein, a remote storage node (e.g.,130a) is available when it is connected to the network110and comprises sufficient available storage space to store the file. Additionally, in at least one embodiment, a remote storage node130ais available when the remote directory server determines that the user who is requesting to store the file has permissions to access the particular remote storage node130a. For example, as will be explained more fully herein, in at least one embodiment, multiple different users can utilize the same cloud storage service. In such a case, it may be desirable to physically isolate users' data.

In at least one embodiment, the processor202also generates a log that comprises identification information associated with the digital file and an address for each respective block of data within each respective remote storage node. For example, the log may comprise a file name associated with the digital file and an IP address for each remote storage node130(a-d) that was used to store blocks of data associated with the digital file. Additionally, the log may comprise an address for the location of the respective data blocks within each of the remote storage nodes130(a-d).

The processor202transmits the log to the remote directory server120. In at least one embodiment, the remote directory server120comprises multiple different logs222that map multiple different digital files to the remote storage nodes. Using the logs222, one or more users can identify a desired file and request the file from the associated remote storage nodes130(a-d).

For example, in at least one embodiment, a computer system, such as the mobile computing device100receives a request, through an application program interface (API), to access a digital file. The request may be generated by a software application206, such as a photo editing software application206, to access a photo stored within the cloud. In particular, the photo editing software application206may generate a request for the digital file through the storage API204.

In response to receiving the query through the storage API204, the processor202queries a remote directory server120for the digital file. The remote directory server120identifies within its logs222addresses to data blocks associated with the requested file that are stored within multiple remote storage nodes. In at least one embodiment, the remote directory server120then utilizes a node tracker component226to identify which of the respective remote storage nodes are currently available.

In at least one embodiment, an available remote storage node130(a) comprises a storage node with up-to-date content. For example, the node tracker226within the remote directory server120can track the current version of data across the remote storage nodes130(a-d). For instance, a digital file within the cloud may be updated during a time when one or more remote storage nodes130(a-d) are not available. As such, the unavailable remote storage nodes130(a-d) may not comprise the most recently updated version of the file. In such a case, the remote directory server120excludes data blocks associated with outdated versions and only returns addresses to remote storage nodes130(a-d) that have the most up-to-date versions of the file.

Further, in at least one embodiment, when a processor202is not able to update all of the remote storage nodes130(a-d) with the most recent changes to a file, the processor202saves the updated data blocks associated with the unavailable remote storage nodes within memory208. The processor202then periodically polls the previously unavailable remote storage nodes to determine if they are now available. As each remote storage node becomes available, the processor202retrieves the respective data blocks from memory208and transmits them to the appropriate remote storage node (e.g.,130a).

In contrast, to the above, in at least one embodiment, when a processor202is not able to update all of the remote storage nodes130(a-d) with the most recent changes to a file, the processor202transmits the updated data blacks associated with the unavailable remote storage nodes130(a-d) to the remote directory server120, or some other associated server. The node tracker226then polls the previously unavailable remote storage nodes and updates them as they become available.

Upon identifying available remote storage nodes, the remote directory server120sends to the processor202addresses to data blocks stored within multiple available remote storage nodes. The addresses comprise at least IP addresses for accessing the remote storage nodes.

The processor202then requests, from at least a portion of the remote storage nodes130(a-d), at least a portion of the addressed data blocks. In at least one embodiment, the processor202receives addresses to only available remote storage nodes130(a-d).

Upon receiving the data blocks from the remote storage nodes130(a-d), the processor decodes the digital file from the portion of the addressed data blocks. In at least one embodiment, decoding the digital file comprises rebuilding at least a portion of the digital file using parity information associated with the portion of the addressed data blocks. For example, one or more remote storage nodes that contain data blocks associated with the digital file may be unavailable. In such a circumstance, the processor202utilizes error-correction coding algorithms along with parity information in the received data blocks to rebuild the missing data. In at least one embodiment, the processor202utilizes a Reed-Solomon algorithm to rebuild the missing data. After rebuilding the file, the processor202communicates the decoded digital file to a requester—in this case the photo editing software application206.

Additionally, in at least one embodiment, the processor202also decrypts the data within the data blocks. In particular, the processor202accesses a decryption key that is provided by a user or stored within memory208and decrypts the received data. As stated above, encrypting and decrypting the data using a key stored or received locally at the mobile computing device100adds additional security to the cloud storage by preventing other users from accessing the data stored in the cloud.

In various additional or alternative embodiments, further methods and systems are implemented to optimize network bandwidth usage. For example,FIG. 3illustrates a schematic of yet another embodiment of another system for optimizing bandwidth usage within a cloud storage system. In particular,FIG. 3depicts multiple different user devices300(a-d) making requests through a network110. The network110connects the multiple different user devices300(a-d) to various remote storage nodes330.

In at least one embodiment, files stored within the remote storage nodes300(a-d) are shared assets, such that multiple different users may access the same stored file. For example, a user may store a family photo album within the remote storage nodes300(a-d). The user may further desire to share the family photo album with family members and friends. In such a circumstance, it may optimize bandwidth to place the entire file, or certain data blocks that are associated with the file in specific storage nodes.

For instance, in at least one embodiment, at least a portion of the multiple different user devices300(a-d) are located within the same local-area network and are all requesting access to the family photo album. Additionally, in at least one embodiment, one of the remote storage nodes (e.g., remote storage node330a) is also located within the same local-area network as the multiple different user devices300(a-d). As such, the remote storage node330ais not remote from the multiple different user devices300(a-d), but is instead remote from the other remote storage nodes330.

In at least one embodiment, upon identifying that the multiple different user devices300(a-d) are requesting the same file, the remote storage node330arequests from at least a portion of the other remote storage nodes330(b-g) at least a portion of the data blocks associated with the family photo album file. The remote storage node330athen stores the entire family album or multiple data blocks associated with the family photo album locally. The remote storage node330aalso communicates the updated locations to the remote directory server320. Future requests for the family photo album that are generated within the local-area network are directed by the remote directory server320towards remote storage node330a. In contrast, at least some requests for the family photo album generated outside the local-area network are directed to one or more of the remote storage nodes330. Accordingly, the multiple different user devices300(a-d) are then able to download the photo album or data blocks from the remote storage node300athat is within the same local-area network, as opposed to the typically slower process of downloading across networks.

In at least one embodiment, the remote storage node330aidentifies, within the local-area network, one or more distinct requests to access a particular digital file (e.g. the family photo album). Further, each distinct request is associated with a different user device. The remote storage node330may handle all requests between the local-area network and the remote directory server320.

In at least one embodiment, during the communications between the local-area network and the remote directory server320, the remote storage node330atracks the particular file being requested and the particular users who are making the requests. In contrast, in an alternative or additional embodiment, the remote directory server320tracks the particular file being requested, the particular users who are making the requests, and the location of the particular users. As needed, the remote directory server320then passes this information onto the remote storage node330a.

When a number of the one or more distinct requests exceeds a threshold, the remote storage node330aqueries the remote directory server320for addresses to the data blocks associated with the particular digital file. The threshold may be set by a user, set by an administrator of the remote directory server320, or adaptively set by a remote storage node330abased upon current network conditions. For example, in at least one embodiment, the threshold is exceeded as soon as a second device requests the same digital file within a particular time period, such as an hour. In contrast, in at least one embodiment, a user specifies the threshold such that the user controls the optimization of the network bandwidth. In at least one embodiment, the remote storage node330asets the threshold based upon the amount of time it took to originally access all of the data blocks associated with the particular file. Specifically, the longer it took to access all of the data blocks the lower the threshold is set for that particular file. As such, different files may have different thresholds that are dependent upon where the respective data blocks for the different files are stored.

The remote storage node330athen receives, from the remote directory server,320, addresses to data blocks stored within multiple remote storage nodes330. Using the received addresses, the remote storage node330arequests, from at least a portion of the remote storage nodes330, at least a portion of the addressed data blocks. For example, in at least one embodiment, the remote storage node330amay not request all of the data blocks associated with the digital file. Instead, the remote storage node330amay only request the data blocks from remote storage nodes330(b-g) with relatively slow connection speeds. Alternatively or additionally, the remote storage node330aonly requests the minimum number of data blocks needed to rebuild the digital file using the parity information. As such, the remote storage node330amay only store a portion of the total data blocks. A user device300athat requests the digital file may then be provided with links to a portion of the data blocks that are stored locally within remote storage node330aand links to other remote storage nodes330(b-g). Additionally, the user device300amay be required to use parity information to reconstruct the entire digital file from only a portion of the data blocks.

In at least one embodiment, the remote storage node330astores only a portion of the addressed data blocks within local memory. For example, the remote storage node330amay only store data blocks that are associated with remote storage nodes330with slow connections. When a particular remote storage node (e.g., remote storage node330b) drops below a specific connection speed and the number of distinct users requesting the digital file exceeds the threshold, the remote storage node330adownloads the data blocks from remote storage node330b, while leaving the data blocks remaining at the other remote storage nodes330(c-g). As such, the remote storage node330ahas only downloaded a portion of the data blocks, and the downloaded portion may be insufficient to completely reconstruct the digital file without additional data blocks from other remote storage nodes330(c-g). The user device300ais then able to download the other data blocks from the other remote storage nodes330(c-g) while accessing the locally stored portion of data blocks much more quickly than would have been possible from the slower remote storage node330b.

Accordingly, in at least one embodiment, a user device300arequests the digital file associated with the stored data blocks. The remote storage node330areceives a request from the user device300ato download a first subset of the addressed data blocks, which may only be a portion, or subset, of the data blocks associated with the digital file. The remote storage node330aidentifies the first subset within the locally stored portion of the addressed data blocks and transmits the first subset of the addressed data blocks to the first user device.

In at least one embodiment, the user device300ainitially or later downloads a second subset of the one or more addressed data blocks from the multiple remote storage nodes330(b-g). The one or more addressed data blocks of the second subset are exclusive from the one or more addressed data blocks of the first subset. For example, the first subset of data blocks comprises data blocks from slower remote storage nodes330that were downloaded locally, while the second subset of data blocks comprises data blocks that are directly downloaded from the other remote storage nodes330.

Once the data blocks are downloaded, either the user device300aor the remote storage node330adecodes the particular digital file from the portion of the addressed data blocks. In at least one embodiment, decoding the particular digital file comprises rebuilding at least a portion of the particular digital file using parity information associated with the portion of the addressed data blocks. The remote storage node330athen stores the decoded digital file within local memory (e.g., local memory232ashown inFIG. 2). The local memory is located within the local-area network, and the decoded digital file is associated with a local-area network address. The remote storage node330athen communicates the local-area network address to the remote directory server. As such, other user devices300(b-d) that are within the same local-area network and that query the remote directory server320for the digital file are directed to the local-area network address.

Accordingly, disclosed embodiments include methods and systems for optimizing bandwidth within a distributed cloud network. In particular, disclosed embodiments increase bandwidth efficiency by intelligently moving at least portions of a target digital file to storage within the local-area network. As such, the use of external bandwidth which is typically far costlier and much slower than local bandwidth is minimized.

Additionally, in at least one embodiment, disclosed embodiments increase bandwidth efficiency by dynamically selecting remote storage nodes to retrieve data from. For example, user device300amay request a digital file that is stored at remote storage nodes330a,330b,330c, and330d. Upon connecting to each remote storage node330a,330b,330c, and330d, the user device300amay determine that the connection to storage node330dis substantially slower than the connection to the other remote storage nodes330a,330b,330c. In such a case, instead of waiting for the data blocks to download from remote storage node330d, the user device300amay simply drop the connection to remote storage node330dand recover the digital file using error-correction coding and the data stored in remote storage nodes330a,330b, and330c. Accordingly, in at least one embodiment, a user device300adynamically determines whether it is faster to download data blocks from a collection of remote storage nodes330or to download only a portion of the data blocks from a subset of the remote storage nodes330and recover the entire digital file using error-correction coding.

One will appreciate that embodiments disclosed herein can also be described in terms of flowcharts comprising one or more acts for accomplishing a particular result. For example,FIG. 4and the corresponding text describe acts in various methods and systems for optimizing bandwidth usage within a cloud storage system. The acts ofFIG. 4are described below.

For example,FIG. 4illustrates that a flow chart of an embodiment of a method400for optimizing bandwidth usage within a cloud storage system can comprise act410of identifying requests for a digital file. Act410includes identifying, within a local-area network, one or more distinct requests to access a particular digital file, wherein each distinct request is associated with a different user device. For example, as depicted and described with respect toFIG. 3, a remote storage node330athat is within the local-area network is capable of identifying requests that are generated by user devices300(a-d) within the local-area network.

Additionally,FIG. 4illustrates that the method400comprises an act420of querying a server for the digital file. Act420includes when a number of the one or more distinct requests exceeds a threshold, querying a remote directory server for the particular digital file. For example, as depicted and described with respect toFIG. 3, when the remote storage node (e.g., remote storage node330a) identifies that more than a threshold number of user devices300(a-d) are requesting a particular digital file, the remote storage node queries the remote directory server320for the particular digital file.

FIG. 4also illustrates that the method400comprises an act430of receiving addresses to data blocks. Act430includes receiving, from the remote directory server, addresses to data blocks stored within multiple remote storage nodes. For example, as depicted and described with respect toFIG. 3, remote storage node330areceives from the remote directory server320addresses to data blocks that are stored within the other remote storage nodes (e.g., remote storage nodes300(b-g)).

Further,FIG. 4illustrates that the method400comprises an act440of requesting data blocks. Act440includes requesting, from at least a portion of the remote storage nodes, at least a portion of the addressed data blocks. For example, as depicted and described with respect toFIG. 3, remote storage node330arequests at least a portion of the data blocks that are stored within the other remote storage nodes (e.g., remote storage nodes300(b-g)).

Further still,FIG. 4illustrates that the method400comprises an act450of decoding the digital file. Act450includes decoding the particular digital file from the portion of the addressed data blocks. Decoding the particular digital file comprises rebuilding at least a portion of the particular digital file using parity information associated with the portion of the addressed data blocks and storing the decoded digital file within local memory. The local memory is located within the local-area network, and the decoded digital file is associated with a local-area network address. For example, as depicted and described with respect toFIGS. 2 and 3, the remote storage node330adecodes the digital file and stores the digital file within local memory (e.g., storage232ainFIG. 2). The remote storage node330aalso identifies a local-area network address associated with the particular digital file.

Physical computer-readable storage media includes RAM, ROM, EEPROM, CD-ROM or other optical disk storage (such as CDs, DVDs, etc.), magnetic disk storage or other magnetic storage devices, or any other medium which can be used to store desired program code means in the form of computer-executable instructions or data structures and which can be accessed by a general-purpose or special purpose computer.