Patent Publication Number: US-11023671-B2

Title: Data classification using spatial data

Description:
FIELD 
     The present disclosure relates generally to computer architecture software for data classification and information security and, in some more particular aspects, to verifying information or events in a file system using spatial data. 
     BACKGROUND 
     The sheer volume and complexity of data that is collected, analyzed and stored is increasing rapidly over time. The computer infrastructure used to handle this data is also becoming more complex, with more processing power and more portability. As a result, data management and storage is becoming increasingly important. Significant aspects of these processes include access to reliable data backup and storage, and fast data recovery in cases of failure. Other aspects include data portability across locations and platforms. 
     At the same time, unauthorized access to systems and ransomware have become major cyber-security threats in recent times. In this regard, data security regulations such as those mandated in the General Data Protection Regulation 2016/679 (GDPR) place strict notification obligations on data holders. The GDPR is a regulation in EU law relating to data protection and privacy for all individuals within the European Union and the European Economic Area. The regulation also addresses the export of personal data outside the EU and EEA areas, such as into the United States. Under the GDPR regulation, if there is a data breach the data holder is required to notify all affected users very quickly. Thus, the rapid detection of ransomware or unauthorized access to data is critical. 
     SUMMARY 
     In an example embodiment, a data management system is provided. The system may comprise a first storage device configured to store a base file associated with a first version of a virtual machine; a second storage device configured to store one or more forward incremental files associated with one or more versions of the virtual machine; a text content verifier; and one or more processors in communication with the first storage device and the second storage device, the one or more processors configured to perform operations including: identifying a spreadsheet among the base file and one or more forward incremental files, the spreadsheet including formatted text and row and column dimensions; generating spreadsheet spatial metadata by parsing the formatted text and row and column dimensions; and supply the spreadsheet spatial metadata to the text content verifier. 
     In another example, a data management system comprises a first storage device configured to store a base file associated with a first version of a virtual machine; a second storage device configured to store one or more forward incremental files associated with one or more versions of the virtual machine; a text content verifier; and one or more processors in communication with the first storage device and the second storage device, the one or more processors configured to perform operations including: identifying a spreadsheet stored in a file in a monitored computer system, the spreadsheet including formatted text and row and column dimensions; generating spreadsheet spatial metadata by parsing the formatted text and row and column dimensions; and supply the spreadsheet spatial metadata to the text content verifier. 
     In another example, a data management system comprises a storage device; a text content verifier; and one or more processors in communication with the storage device, the one or more processors configured to perform operations including: identifying a spreadsheet stored in a file in the storage device, the spreadsheet including formatted text and row and column dimensions; generating spreadsheet spatial metadata by parsing the formatted text and row and column dimensions; and supply the spreadsheet spatial metadata to the text content verifier. 
     In some embodiments of the above examples, the one or more processors are further configured to identify a data construct in the spreadsheet, the data construct including a table or a header; and incorporate the identified data structure in the spreadsheet spatial metadata. 
     In some embodiments, the text content verifier is included in a tiered array of text content verifiers and wherein the spreadsheet special metadata is supplied to the tiered array of text content verifiers. 
     In some embodiments, a first text content verifier in the array of tiered text content verifiers is supplied spreadsheet spatial metadata comprising keyword data sourced from a first ranked region of the spreadsheet, and a second text content verifier in the tiered array of text content verifiers is supplied spreadsheet spatial comprising aspects of the data construct sourced from a second ranked region of the spreadsheet. 
     In some embodiments, the keyword data is sourced from a proximity-based keyword search based on a selection of a row or column dimension of the spreadsheet. 
     In some embodiments, the one or more processors is further configured to incorporate at least some of the spreadsheet spatial metadata in a key to verify an audit event in a series of audit events including at least a create event, a write event, a read event, or a cleanup event. 
    
    
     
       DESCRIPTION OF THE DRAWINGS 
       Some embodiments are illustrated by way of example and not limitation in the figures of the accompanying drawings: 
         FIG. 1  depicts one embodiment of a networked computing environment in which the disclosed technology may be practiced, according to an example embodiment. 
         FIG. 2  depicts one embodiment of server in  FIG. 1 , according to an example embodiment. 
         FIG. 3  depicts one embodiment of storage appliance in  FIG. 1 , according to an example embodiment. 
         FIGS. 4-6  each depict a block flow chart indicating example operations in a method of the present disclosure, according to an example embodiment. 
         FIG. 7  depicts a block diagram illustrating an example of a software architecture that may be installed on a machine, according to some example embodiments. 
         FIG. 8  depicts a block diagram illustrating an architecture of software, according to an example embodiment. 
         FIG. 9  illustrates a diagrammatic representation of a machine in the form of a computer system within which a set of instructions may be executed for causing a machine to perform any one or more of the methodologies discussed herein, according to an example embodiment. 
     
    
    
     DESCRIPTION 
     The description that follows includes systems, methods, techniques, instruction sequences, and computing machine program products that embody illustrative embodiments of the present disclosure. In the following description, for purposes of explanation, numerous specific details are set forth in order to provide a thorough understanding of example embodiments. It will be evident, however, to one skilled in the art that the present invention may be practiced without these specific details. 
     A portion of the disclosure of this patent document contains material that is subject to copyright protection. The copyright owner has no objection to the facsimile reproduction by anyone of the patent document or the patent disclosure, as it appears in the Patent and Trademark Office patent files or records, but otherwise reserves all copyright rights whatsoever. The following notice applies to the software and data as described below and in the drawings that form a part of this document: Copyright Rubrik, Inc., 2018-2019, All Rights Reserved. 
       FIG. 1  depicts one embodiment of a networked computing environment  100  in which the disclosed technology may be practiced. As depicted, the networked computing environment  100  includes a data center  150 , a storage appliance  140 , and a computing device  154  in communication with each other via one or more networks  180 . The networked computing environment  100  may also include a plurality of computing devices interconnected through one or more networks  180 . The one or more networks  180  may allow computing devices and/or storage devices to connect to and communicate with other computing devices and/or other storage devices. In some cases, the networked computing environment may include other computing devices and/or other storage devices not shown. The other computing devices may include, for example, a mobile computing device, a non-mobile computing device, a server, a work-station, a laptop computer, a tablet computer, a desktop computer, or an information processing system. The other storage devices may include, for example, a storage area network storage device, a networked-attached storage device, a hard disk drive, a solid-state drive, or a data storage system. 
     The data center  150  may include one or more servers, such as server  160 , in communication with one or more storage devices, such as storage device  156 . The one or more servers may also be in communication with one or more storage appliances, such as storage appliance  170 . The server  160 , storage device  156 , and storage appliance  170  may be in communication with each other via a networking fabric connecting servers and data storage units within the data center to each other. The storage appliance  170  may include a data management system for backing up virtual machines and/or files within a virtualized infrastructure. The server  160  may be used to create and manage one or more virtual machines associated with a virtualized infrastructure. 
     The one or more virtual machines may run various applications, such as a database application or a web server. The storage device  156  may include one or more hardware storage devices for storing data, such as a hard disk drive (HDD), a magnetic tape drive, a solid-state drive (SSD), a storage area network (SAN) storage device, or a Networked-Attached Storage (NAS) device. In some cases, a data center, such as data center  150 , may include thousands of servers and/or data storage devices in communication with each other. The one or more data storage devices  156  may comprise a tiered data storage infrastructure (or a portion of a tiered data storage infrastructure). The tiered data storage infrastructure may allow for the movement of data across different tiers of a data storage infrastructure between higher-cost, higher-performance storage devices (e.g., solid-state drives and hard disk drives) and relatively lower-cost, lower-performance storage devices (e.g., magnetic tape drives). 
     The one or more networks  180  may include a secure network such as an enterprise private network, an unsecure network such as a wireless open network, a local area network (LAN), a wide area network (WAN), and the Internet. The one or more networks  180  may include a cellular network, a mobile network, a wireless network, or a wired network. Each network of the one or more networks  180  may include hubs, bridges, routers, switches, and wired transmission media such as a direct-wired connection. The one or more networks  180  may include an extranet or other private network for securely sharing information or providing controlled access to applications or files. 
     A server, such as server  160 , may allow a client to download information or files (e.g., executable, text, application, audio, image, or video files) from the server or to perform a search query related to particular information stored on the server. In some cases, a server may act as an application server or a file server. In general, a server  160  may refer to a hardware device that acts as the host in a client-server relationship or a software process that shares a resource with or performs work for one or more clients. 
     One embodiment of server  160  includes a network interface  165 , processor  166 , memory  167 , disk  168 , and virtualization manager  169  all in communication with each other. Network interface  165  allows server  160  to connect to one or more networks  180 . Network interface  165  may include a wireless network interface and/or a wired network interface. Processor  166  allows server  160  to execute computer readable instructions stored in memory  167  in order to perform processes described herein. Processor  166  may include one or more processing units, such as one or more CPUs and/or one or more GPUs. Memory  167  may comprise one or more types of memory (e.g., RAM, SRAM, DRAM, ROM, EEPROM, Flash, etc.). Disk  168  may include a hard disk drive and/or a solid-state drive. Memory  167  and disk  168  may comprise hardware storage devices. 
     The virtualization manager  169  may manage a virtualized infrastructure and perform management operations associated with the virtualized infrastructure. The virtualization manager  169  may manage the provisioning of virtual machines running within the virtualized infrastructure and provide an interface to computing devices interacting with the virtualized infrastructure. In one example, the virtualization manager  169  may set a virtual machine having a virtual disk into a frozen state in response to a snapshot request made via an application programming interface (API) by a storage appliance, such as storage appliance  170 . Setting the virtual machine into a frozen state may allow a point in time snapshot of the virtual machine to be stored or transferred. In one example, updates made to a virtual machine that has been set into a frozen state may be written to a separate file (e.g., an update file) while the virtual disk may be set into a read-only state to prevent modifications to the virtual disk file while the virtual machine is in the frozen state. 
     The virtualization manager  169  may then transfer data associated with the virtual machine (e.g., an image of the virtual machine or a portion of the image of the virtual disk file associated with the state of the virtual disk at the point in time is frozen) to a storage appliance (for example, a storage appliance  140  or  170  of  FIG. 1 , described further below) in response to a request made by the storage appliance. After the data associated with the point in time snapshot of the virtual machine has been transferred to the storage appliance  170  (for example), the virtual machine may be released from the frozen state (i.e., unfrozen) and the updates made to the virtual machine and stored in the separate file may be merged into the virtual disk file. The virtualization manager  169  may perform various virtual machine related tasks, such as cloning virtual machines, creating new virtual machines, monitoring the state of virtual machines, moving virtual machines between physical hosts for load balancing purposes, and facilitating backups of virtual machines. 
     One embodiment of a storage appliance  170  (or  140 ) includes a network interface  175 , processor  176 , memory  177 , and disk  178  all in communication with each other. Network interface  175  allows storage appliance  170  to connect to one or more networks  180 . Network interface  175  may include a wireless network interface and/or a wired network interface. Processor  176  allows storage appliance  170  to execute computer readable instructions stored in memory  177  in order to perform processes described herein. Processor  176  may include one or more processing units, such as one or more CPUs and/or one or more GPUs. Memory  177  may comprise one or more types of memory (e.g., RAM, SRAM, DRAM, ROM, EEPROM, NOR Flash, NAND Flash, etc.). Disk  178  may include a hard disk drive and/or a solid-state drive. Memory  177  and disk  178  may comprise hardware storage devices. 
     In one embodiment, the storage appliance  170  may include four machines. Each of the four machines may include a multi-core CPU, 64 GB of RAM, a 400 GB SSD, three 4 TB HDDs, and a network interface controller. In this case, the four machines may be in communication with the one or more networks  180  via the four network interface controllers. The four machines may comprise four nodes of a server cluster. The server cluster may comprise a set of physical machines that are connected together via a network. The server cluster may be used for storing data associated with a plurality of virtual machines, such as backup data associated with different points in time versions of the virtual machines. 
     The networked computing environment  100  may provide a cloud computing environment for one or more computing devices. Cloud computing may refer to Internet-based computing, wherein shared resources, software, and/or information may be provided to one or more computing devices on-demand via the Internet. The networked computing environment  100  may comprise a cloud computing environment providing Software-as-a-Service (SaaS) or Infrastructure-as-a-Service (IaaS) services. SaaS may refer to a software distribution model in which applications are hosted by a service provider and made available to end users over the Internet. In one embodiment, the networked computing environment  100  may include a virtualized infrastructure that provides software, data processing, and/or data storage services to end users accessing the services via the networked computing environment  100 . In one example, networked computing environment  100  may provide cloud-based work productivity or business-related applications to a computing device, such as computing device  154 . The storage appliance  140  may comprise a cloud-based data management system for backing up virtual machines and/or files within a virtualized infrastructure, such as virtual machines running on server  160  or files stored on server  160 . 
     In some cases, networked computing environment  100  may provide remote access to secure applications and files stored within data center  150  from a remote computing device, such as computing device  154 . The data center  150  may use an access control application to manage remote access to protected resources, such as protected applications, databases, or files located within the data center. To facilitate remote access to secure applications and files, a secure network connection may be established using a virtual private network (VPN). A VPN connection may allow a remote computing device, such as computing device  154 , to securely access data from a private network (e.g., from a company file server or mail server) using an unsecure public network or the Internet. The VPN connection may require client-side software (e.g., running on the remote computing device) to establish and maintain the VPN connection. The VPN client software may provide data encryption and encapsulation prior to the transmission of secure private network traffic through the Internet. 
     In some embodiments, the storage appliance  170  may manage the extraction and storage of virtual machine snapshots associated with different point in time versions of one or more virtual machines running within the data center  150 . A snapshot of a virtual machine may correspond with a state of the virtual machine at a particular point in time. In response to a restore command from the server  160 , the storage appliance  170  may restore a point in time version of a virtual machine or restore point in time versions of one or more files located on the virtual machine and transmit the restored data to the server  160 . In response to a mount command from the server  160 , the storage appliance  170  may allow a point in time version of a virtual machine to be mounted and allow the server  160  to read and/or modify data associated with the point in time version of the virtual machine. To improve storage density, the storage appliance  170  may deduplicate and compress data associated with different versions of a virtual machine and/or deduplicate and compress data associated with different virtual machines. To improve system performance, the storage appliance  170  may first store virtual machine snapshots received from a virtualized environment in a cache, such as a flash-based cache. The cache may also store popular data or frequently accessed data (e.g., based on a history of virtual machine restorations, incremental files associated with commonly restored virtual machine versions) and current day incremental files or incremental files corresponding with snapshots captured within the past 24 hours. 
     An incremental file may comprise a forward incremental file or a reverse incremental file. A forward incremental file may include a set of data representing changes that have occurred since an earlier point in time snapshot of a virtual machine. To generate a snapshot of the virtual machine corresponding with a forward incremental file, the forward incremental file may be combined with an earlier point in time snapshot of the virtual machine (e.g., the forward incremental file may be combined with the last full image of the virtual machine that was captured before the forward incremental file was captured and any other forward incremental files that were captured subsequent to the last full image and prior to the forward incremental file). A reverse incremental file may include a set of data representing changes from a later point in time snapshot of a virtual machine. To generate a snapshot of the virtual machine corresponding with a reverse incremental file, the reverse incremental file may be combined with a later point in time snapshot of the virtual machine (e.g., the reverse incremental file may be combined with the most recent snapshot of the virtual machine and any other reverse incremental files that were captured prior to the most recent snapshot and subsequent to the reverse incremental file). 
     The storage appliance  170  may provide a user interface (e.g., a web-based interface or a graphical user interface) that displays virtual machine backup information such as identifications of the virtual machines protected and the historical versions or time machine views for each of the virtual machines protected. A time machine view of a virtual machine may include snapshots of the virtual machine over a plurality of points in time. Each snapshot may comprise the state of the virtual machine at a particular point in time. Each snapshot may correspond with a different version of the virtual machine (e.g., Version 1 of a virtual machine may correspond with the state of the virtual machine at a first point in time and Version 2 of the virtual machine may correspond with the state of the virtual machine at a second point in time subsequent to the first point in time). 
     The user interface may enable an end user of the storage appliance  170  (e.g., a system administrator or a virtualization administrator) to select a particular version of a virtual machine to be restored or mounted. When a particular version of a virtual machine has been mounted, the particular version may be accessed by a client (e.g., a virtual machine, a physical machine, or a computing device) as if the particular version was local to the client. A mounted version of a virtual machine may correspond with a mount point directory (e.g., /snapshots/VM5Nersion23). In one example, the storage appliance  170  may run an NFS server and make the particular version (or a copy of the particular version) of the virtual machine accessible for reading and/or writing. The end user of the storage appliance  170  may then select the particular version to be mounted and run an application (e.g., a data analytics application) using the mounted version of the virtual machine. In another example, the particular version may be mounted as an iSCSI target. 
       FIG. 2  depicts one embodiment of server  160  in  FIG. 1 . The server  160  may comprise one server out of a plurality of servers that are networked together within a data center. In one example, the plurality of servers may be positioned within one or more server racks within the data center. As depicted, the server  160  includes hardware-level components and software-level components. The hardware-level components include one or more processors  182 , one or more memory  184 , and one or more disks  185 . The software-level components include a hypervisor  186 , a virtualized infrastructure manager  199 , and one or more virtual machines, such as virtual machine  198 . The hypervisor  186  may comprise a native hypervisor or a hosted hypervisor. The hypervisor  186  may provide a virtual operating platform for running one or more virtual machines, such as virtual machine  198 . Virtual machine  198  includes a plurality of virtual hardware devices including a virtual processor  192 , a virtual memory  194 , and a virtual disk  195 . The virtual disk  195  may comprise a file stored within the one or more disks  185 . In one example, a virtual machine  198  may include a plurality of virtual disks  195 , with each virtual disk of the plurality of virtual disks associated with a different file stored on the one or more disks  185 . Virtual machine  198  may include a guest operating system  196  that runs one or more applications, such as application  197 . 
     The virtualized infrastructure manager  199 , which may correspond with the virtualization manager  169  in  FIG. 1 , may run on a virtual machine or natively on the server  160 . The virtual machine may, for example, be or include the virtual machine  198  or a virtual machine separate from the server  160 . Other arrangements are possible. The virtualized infrastructure manager  199  may provide a centralized platform for managing a virtualized infrastructure that includes a plurality of virtual machines. The virtualized infrastructure manager  199  may manage the provisioning of virtual machines running within the virtualized infrastructure and provide an interface to computing devices interacting with the virtualized infrastructure. The virtualized infrastructure manager  199  may perform various virtualized infrastructure related tasks, such as cloning virtual machines, creating new virtual machines, monitoring the state of virtual machines, and facilitating backups of virtual machines. 
     In one embodiment, the server  160  may use the virtualized infrastructure manager  199  to facilitate backups for a plurality of virtual machines (e.g., eight different virtual machines) running on the server  160 . Each virtual machine running on the server  160  may run its own guest operating system and its own set of applications. Each virtual machine running on the server  160  may store its own set of files using one or more virtual disks associated with the virtual machine (e.g., each virtual machine may include two virtual disks that are used for storing data associated with the virtual machine). 
     In one embodiment, a data management application running on a storage appliance, such as storage appliance  140  in  FIG. 1  or storage appliance  170  in  FIG. 1 , may request a snapshot of a virtual machine running on server  160 . The snapshot of the virtual machine may be stored as one or more files, with each file associated with a virtual disk of the virtual machine. A snapshot of a virtual machine may correspond with a state of the virtual machine at a particular point in time. The particular point in time may be associated with a time stamp. In one example, a first snapshot of a virtual machine may correspond with a first state of the virtual machine (including the state of applications and files stored on the virtual machine) at a first point in time and a second snapshot of the virtual machine may correspond with a second state of the virtual machine at a second point in time subsequent to the first point in time. 
     In response to a request for a snapshot of a virtual machine at a particular point in time, the virtualized infrastructure manager  199  may set the virtual machine into a frozen state or store a copy of the virtual machine at the particular point in time. The virtualized infrastructure manager  199  may then transfer data associated with the virtual machine (e.g., an image of the virtual machine or a portion of the image of the virtual machine) to the storage appliance. The data associated with the virtual machine may include a set of files including a virtual disk file storing contents of a virtual disk of the virtual machine at the particular point in time and a virtual machine configuration file storing configuration settings for the virtual machine at the particular point in time. The contents of the virtual disk file may include the operating system used by the virtual machine, local applications stored on the virtual disk, and user files (e.g., images and word processing documents). In some cases, the virtualized infrastructure manager  199  may transfer a full image of the virtual machine to the storage appliance  140  or  170  of  FIG. 1  or a plurality of data blocks corresponding with the full image (e.g., to enable a full image-level backup of the virtual machine to be stored on the storage appliance). In other cases, the virtualized infrastructure manager  199  may transfer a portion of an image of the virtual machine associated with data that has changed since an earlier point in time prior to the particular point in time or since a last snapshot of the virtual machine was taken. In one example, the virtualized infrastructure manager  199  may transfer only data associated with virtual blocks stored on a virtual disk of the virtual machine that have changed since the last snapshot of the virtual machine was taken. In one embodiment, the data management application may specify a first point in time and a second point in time and the virtualized infrastructure manager  199  may output one or more virtual data blocks associated with the virtual machine that have been modified between the first point in time and the second point in time. 
     In some embodiments, the server  160  may or the hypervisor  186  may communicate with a storage appliance, such as storage appliance  140  in  FIG. 1  or storage appliance  170  in  FIG. 1 , using a distributed file system protocol such as Network File System (NFS) Version 3, or Server Message Block (SMB) protocol. The distributed file system protocol may allow the server  160  or the hypervisor  186  to access, read, write, or modify files stored on the storage appliance as if the files were locally stored on the server. The distributed file system protocol may allow the server  160  or the hypervisor  186  to mount a directory or a portion of a file system located within the storage appliance. 
       FIG. 3  depicts one embodiment of storage appliance  170  in  FIG. 1 . The storage appliance may include a plurality of physical machines that may be grouped together and presented as a single computing system. Each physical machine of the plurality of physical machines may comprise a node in a cluster (e.g., a failover cluster). In one example, the storage appliance may be positioned within a server rack within a data center. As depicted, the storage appliance  170  includes hardware-level components and software-level components. The hardware-level components include one or more physical machines, such as physical machine  120  and physical machine  130 . The physical machine  120  includes a network interface  121 , processor  122 , memory  123 , and disk  124  all in communication with each other. Processor  122  allows physical machine  120  to execute computer readable instructions stored in memory  123  to perform processes described herein. Disk  124  may include a hard disk drive and/or a solid-state drive. The physical machine  130  includes a network interface  131 , processor  132 , memory  133 , and disk  134  all in communication with each other. Processor  132  allows physical machine  130  to execute computer readable instructions stored in memory  133  to perform processes described herein. Disk  134  may include a hard disk drive and/or a solid-state drive. In some cases, disk  134  may include a flash-based SSD or a hybrid HDD/SSD drive. In one embodiment, the storage appliance  170  may include a plurality of physical machines arranged in a cluster (e.g., eight machines in a cluster). Each of the plurality of physical machines may include a plurality of multi-core CPUs, 108 GB of RAM, a 500 GB SSD, four 4 TB HDDs, and a network interface controller. 
     In some embodiments, the plurality of physical machines may be used to implement a cluster-based network fileserver. The cluster-based network file server may neither require nor use a front-end load balancer. One issue with using a front-end load balancer to host the IP address for the cluster-based network file server and to forward requests to the nodes of the cluster-based network file server is that the front-end load balancer comprises a single point of failure for the cluster-based network file server. In some cases, the file system protocol used by a server, such as server  160  in  FIG. 1 , or a hypervisor, such as hypervisor  186  in  FIG. 2 , to communicate with the storage appliance  170  may not provide a failover mechanism (e.g., NFS Version 3). In the case that no failover mechanism is provided on the client side, the hypervisor may not be able to connect to a new node within a cluster in the event that the node connected to the hypervisor fails. 
     In some embodiments, each node in a cluster may be connected to each other via a network and may be associated with one or more IP addresses (e.g., two different IP addresses may be assigned to each node). In one example, each node in the cluster may be assigned a permanent IP address and a floating IP address and may be accessed using either the permanent IP address or the floating IP address. In this case, a hypervisor, such as hypervisor  186  in  FIG. 2  may be configured with a first floating IP address associated with a first node in the cluster. The hypervisor may connect to the cluster using the first floating IP address. In one example, the hypervisor may communicate with the cluster using the NFS Version 3 protocol. Each node in the cluster may run a Virtual Router Redundancy Protocol (VRRP) daemon. A daemon may comprise a background process. Each VRRP daemon may include a list of all floating P addresses available within the cluster. In the event that the first node associated with the first floating IP address fails, one of the VRRP daemons may automatically assume or pick up the first floating IP address if no other VRRP daemon has already assumed the first floating IP address. Therefore, if the first node in the cluster fails or otherwise goes down, then one of the remaining VRRP daemons running on the other nodes in the cluster may assume the first floating IP address that is used by the hypervisor for communicating with the cluster. 
     In order to determine which of the other nodes in the cluster will assume the first floating IP address, a VRRP priority may be established. In one example, given a number (N) of nodes in a cluster from node(0) to node(N−1), for a floating IP address (i), the VRRP priority of nodeG) may be G-i) modulo N. In another example, given a number (N) of nodes in a cluster from node(0) to node(N−1), for a floating IP address (i), the VRRP priority of nodeG) may be (i-j) modulo N. In these cases, nodeG) will assume floating IP address (i) only if its VRRP priority is higher than that of any other node in the cluster that is alive and announcing itself on the network. Thus, if a node fails, then there may be a clear priority ordering for determining which other node in the cluster will take over the failed node&#39;s floating IP address. 
     In some cases, a cluster may include a plurality of nodes and each node of the plurality of nodes may be assigned a different floating IP address. In this case, a first hypervisor may be configured with a first floating IP address associated with a first node in the cluster, a second hypervisor may be configured with a second floating IP address associated with a second node in the cluster, and a third hypervisor may be configured with a third floating IP address associated with a third node in the cluster. 
     As depicted in  FIG. 3 , the software-level components of the storage appliance  170  may include data management system  102 , a virtualization interface  104 , a distributed job scheduler  108 , a distributed metadata store  110 , a distributed file system  112 , and one or more virtual machine search indexes, such as virtual machine search index  106 . In one embodiment, the software-level components of the storage appliance  170  may be run using a dedicated hardware-based appliance. In another embodiment, the software-level components of the storage appliance  170  may be run from the cloud (e.g., the software-level components may be installed on a cloud service provider). 
     In some cases, the data storage across a plurality of nodes in a cluster (e.g., the data storage available from the one or more physical machines) may be aggregated and made available over a single file system namespace (e.g., /snapshots/). A directory for each virtual machine protected using the storage appliance  170  may be created (e.g., the directory for Virtual Machine A may be /snapshots/VM_A). Snapshots and other data associated with a virtual machine may reside within the directory for the virtual machine. In one example, snapshots of a virtual machine may be stored in subdirectories of the directory (e.g., a first snapshot of Virtual Machine A may reside in/snapshots/VM_A/sl/ and a second snapshot of Virtual Machine A may reside in/snapshots/VM_A/s2/). 
     The distributed file system  112  may present itself as a single file system, in which as new physical machines or nodes are added to the storage appliance  170 , the cluster may automatically discover the additional nodes and automatically increase the available capacity of the file system for storing files and other data. Each file stored in the distributed file system  112  may be partitioned into one or more chunks or shards. Each of the one or more chunks may be stored within the distributed file system  112  as a separate file. The files stored within the distributed file system  112  may be replicated or mirrored over a plurality of physical machines, thereby creating a load-balanced and fault tolerant distributed file system. In one example, storage appliance  170  may include ten physical machines arranged as a failover cluster and a first file corresponding with a snapshot of a virtual machine (e.g., /snapshots/VM_A/sl/sl.full) may be replicated and stored on three of the ten machines. 
     The distributed metadata store  110  may include a distributed database management system that provides high availability without a single point of failure. In one embodiment, the distributed metadata store  110  may comprise a database, such as a distributed document-oriented database. The distributed metadata store  110  may be used as a distributed key value storage system. In one example, the distributed metadata store  110  may comprise a distributed NoSQL key value store database. In some cases, the distributed metadata store  110  may include a partitioned row store, in which rows are organized into tables or other collections of related data held within a structured format within the key value store database. A table (or a set of tables) may be used to store metadata information associated with one or more files stored within the distributed file system  112 . The metadata information may include the name of a file, a size of the file, file permissions associated with the file, when the file was last modified, and file mapping information associated with an identification of the location of the file stored within a cluster of physical machines. In one embodiment, a new file corresponding with a snapshot of a virtual machine may be stored within the distributed file system  112  and metadata associated with the new file may be stored within the distributed metadata store  110 . The distributed metadata store  110  may also be used to store a backup schedule for the virtual machine and a list of snapshots for the virtual machine that are stored using the storage appliance  170 . 
     In some cases, the distributed metadata store  110  may be used to manage one or more versions of a virtual machine. Each version of the virtual machine may correspond with a full image snapshot of the virtual machine stored within the distributed file system  112  or an incremental snapshot of the virtual machine (e.g., a forward incremental or reverse incremental) stored within the distributed file system  112 . In one embodiment, the one or more versions of the virtual machine may correspond with a plurality of files. The plurality of files may include a single full image snapshot of the virtual machine and one or more incremental aspects derived from the single full image snapshot. The single full image snapshot of the virtual machine may be stored using a first storage device of a first type (e.g., a HDD) and the one or more incremental aspects derived from the single full image snapshot may be stored using a second storage device of a second type (e.g., an SSD). In this case, only a single full image needs to be stored and each version of the virtual machine may be generated from the single full image or the single full image combined with a subset of the one or more incremental aspects. Furthermore, each version of the virtual machine may be generated by performing a sequential read from the first storage device (e.g., reading a single file from a HDD) to acquire the full image and, in parallel, performing one or more reads from the second storage device (e.g., performing fast random reads from an SSD) to acquire the one or more incremental aspects. 
     The distributed job scheduler  108  may be used for scheduling backup jobs that acquire and store virtual machine snapshots for one or more virtual machines over time. The distributed job scheduler  108  may follow a backup schedule to backup an entire image of a virtual machine at a particular point in time or one or more virtual disks associated with the virtual machine at the particular point in time. In one example, the backup schedule may specify that the virtual machine be backed up at a snapshot capture frequency, such as every two hours or every 24 hours. Each backup job may be associated with one or more tasks to be performed in a sequence. Each of the one or more tasks associated with a job may be run on a particular node within a cluster. In some cases, the distributed job scheduler  108  may schedule a specific job to be run on a particular node based on data stored on the particular node. For example, the distributed job scheduler  108  may schedule a virtual machine snapshot job to be run on a node in a cluster that is used to store snapshots of the virtual machine in order to reduce network congestion. 
     The distributed job scheduler  108  may comprise a distributed fault tolerant job scheduler, in which jobs affected by node failures are recovered and rescheduled to be run on available nodes. In one embodiment, the distributed job scheduler  108  may be fully decentralized and implemented without the existence of a master node. The distributed job scheduler  108  may run job scheduling processes on each node in a cluster or on a plurality of nodes in the cluster. In one example, the distributed job scheduler  108  may run a first set of job scheduling processes on a first node in the cluster, a second set of job scheduling processes on a second node in the cluster, and a third set of job scheduling processes on a third node in the cluster. The first set of job scheduling processes, the second set of job scheduling processes, and the third set of job scheduling processes may store information regarding jobs, schedules, and the states of jobs using a metadata store, such as distributed metadata store  110 . In the event that the first node running the first set of job scheduling processes fails (e.g., due to a network failure or a physical machine failure), the states of the jobs managed by the first set of job scheduling processes may fail to be updated within a threshold period of time (e.g., a job may fail to be completed within 30 seconds or within minutes from being started). In response to detecting jobs that have failed to be updated within the threshold period of time, the distributed job scheduler  108  may undo and restart the failed jobs on available nodes within the cluster. 
     The job scheduling processes running on at least a plurality of nodes in a cluster (e.g., on each available node in the cluster) may manage the scheduling and execution of a plurality of jobs. The job scheduling processes may include run processes for running jobs, cleanup processes for cleaning up failed tasks, and rollback processes for rolling-back or undoing any actions or tasks performed by failed jobs. In one embodiment, the job scheduling processes may detect that a particular task for a particular job has failed and in response may perform a cleanup process to clean up or remove the effects of the particular task and then perform a rollback process that processes one or more completed tasks for the particular job in reverse order to undo the effects of the one or more completed tasks. Once the particular job with the failed task has been undone, the job scheduling processes may restart the particular job on an available node in the cluster. 
     The distributed job scheduler  108  may manage a job in which a series of tasks associated with the job are to be performed atomically (i.e., partial execution of the series of tasks is not permitted). If the series of tasks cannot be completely executed or there is any failure that occurs to one of the series of tasks during execution (e.g., a hard disk associated with a physical machine fails or a network connection to the physical machine fails), then the state of a data management system may be returned to a state as if none of the series of tasks were ever performed. The series of tasks may correspond with an ordering of tasks for the series of tasks and the distributed job scheduler  108  may ensure that each task of the series of tasks is executed based on the ordering of tasks. Tasks that do not have dependencies with each other may be executed in parallel. 
     In some cases, the distributed job scheduler  108  may schedule each task of a series of tasks to be performed on a specific node in a cluster. In other cases, the distributed job scheduler  108  may schedule a first task of the series of tasks to be performed on a first node in a cluster and a second task of the series of tasks to be performed on a second node in the cluster. In these cases, the first task may have to operate on a first set of data (e.g., a first file stored in a file system) stored on the first node and the second task may have to operate on a second set of data (e.g., metadata related to the first file that is stored in a database) stored on the second node. In some embodiments, one or more tasks associated with a job may have an affinity to a specific node in a cluster. 
     In one example, if the one or more tasks require access to a database that has been replicated on three nodes in a cluster, then the one or more tasks may be executed on one of the three nodes. In another example, if the one or more tasks require access to multiple chunks of data associated with a virtual disk that has been replicated over four nodes in a cluster, then the one or more tasks may be executed on one of the four nodes. Thus, the distributed job scheduler  108  may assign one or more tasks associated with a job to be executed on a particular node in a cluster based on the location of data required to be accessed by the one or more tasks. 
     In one embodiment, the distributed job scheduler  108  may manage a first job associated with capturing and storing a snapshot of a virtual machine periodically (e.g., every 30 minutes). The first job may include one or more tasks, such as communicating with a virtualized infrastructure manager, such as the virtualized infrastructure manager  199  in  FIG. 2 , to create a frozen copy of the virtual machine and to transfer one or more chunks (or one or more files) associated with the frozen copy to a storage appliance, such as storage appliance  170  in  FIG. 1 . The one or more tasks may also include generating metadata for the one or more chunks, storing the metadata using the distributed metadata store  110 , storing the one or more chunks within the distributed file system  112 , and communicating with the virtualized infrastructure manager  199  that the frozen copy of the virtual machine may be unfrozen or released for a frozen state. The metadata for a first chunk of the one or more chunks may include information specifying a version of the virtual machine associated with the frozen copy, a time associated with the version (e.g., the snapshot of the virtual machine was taken at 5:30 p.m. on Jun. 29, 2018), and a file path to where the first chunk is stored within the distributed file system  92  (e.g., the first chunk is located at /snapshotsNM_B/sl/sl.chunkl). The one or more tasks may also include deduplication, compression (e.g., using a lossless data compression algorithm such as LZ4 or LZ77), decompression, encryption (e.g., using a symmetric key algorithm such as Triple DES or AES-256), and decryption related tasks. 
     The virtualization interface  104  may provide an interface for communicating with a virtualized infrastructure manager managing a virtualization infrastructure, such as virtualized infrastructure manager  199  in  FIG. 2 , and requesting data associated with virtual machine snapshots from the virtualization infrastructure. The virtualization interface  104  may communicate with the virtualized infrastructure manager using an API for accessing the virtualized infrastructure manager (e.g., to communicate a request for a snapshot of a virtual machine). In this case, storage appliance  170  may request and receive data from a virtualized infrastructure without requiring agent software to be installed or running on virtual machines within the virtualized infrastructure. The virtualization interface  104  may request data associated with virtual blocks stored on a virtual disk of the virtual machine that have changed since a last snapshot of the virtual machine was taken or since a specified prior point in time. Therefore, in some cases, if a snapshot of a virtual machine is the first snapshot taken of the virtual machine, then a full image of the virtual machine may be transferred to the storage appliance. However, if the snapshot of the virtual machine is not the first snapshot taken of the virtual machine, then only the data blocks of the virtual machine that have changed since a prior snapshot was taken may be transferred to the storage appliance. 
     The virtual machine search index  106  may include a list of files that have been stored using a virtual machine and a version history for each of the files in the list. Each version of a file may be mapped to the earliest point in time snapshot of the virtual machine that includes the version of the file or to a snapshot of the virtual machine that include the version of the file (e.g., the latest point in time snapshot of the virtual machine that includes the version of the file). In one example, the virtual machine search index  106  may be used to identify a version of the virtual machine that includes a particular version of a file (e.g., a particular version of a database, a spreadsheet, or a word processing document). In some cases, each of the virtual machines that are backed up or protected using storage appliance  170  may have a corresponding virtual machine search index. 
     In one embodiment, as each snapshot of a virtual machine is ingested each virtual disk associated with the virtual machine is parsed in order to identify a file system type associated with the virtual disk and to extract metadata (e.g., file system metadata) for each file stored on the virtual disk. The metadata may include information for locating and retrieving each file from the virtual disk. The metadata may also include a name of a file, the size of the file, the last time at which the file was modified, and a content checksum for the file. Each file that has been added, deleted, or modified since a previous snapshot was captured may be determined using the metadata (e.g., by comparing the time at which a file was last modified with a time associated with the previous snapshot). Thus, for every file that has existed within any of the snapshots of the virtual machine, a virtual machine search index may be used to identify when the file was first created (e.g., corresponding with a first version of the file) and at what times the file was modified (e.g., corresponding with subsequent versions of the file). Each version of the file may be mapped to a particular version of the virtual machine that stores that version of the file. 
     In some cases, if a virtual machine includes a plurality of virtual disks, then a virtual machine search index may be generated for each virtual disk of the plurality of virtual disks. For example, a first virtual machine search index may catalog and map files located on a first virtual disk of the plurality of virtual disks and a second virtual machine search index may catalog and map files located on a second virtual disk of the plurality of virtual disks. In this case, a global file catalog or a global virtual machine search index for the virtual machine may include the first virtual machine search index and the second virtual machine search index. A global file catalog may be stored for each virtual machine backed up by a storage appliance within a file system, such as distributed file system  112  in  FIG. 3 . 
     The data management system  102  may comprise an application running on the storage appliance that manages and stores one or more snapshots of a virtual machine. In one example, the data management system  102  may comprise a highest-level layer in an integrated software stack running on the storage appliance. The integrated software stack may include the data management system  102 , the virtualization interface  104 , the distributed job scheduler  108 , the distributed metadata store  110 , and the distributed file system  112 . 
     In some cases, the integrated software stack may run on other computing devices, such as a server or computing device  154  in  FIG. 1 . The data management system  102  may use the virtualization interface  104 , the distributed job scheduler  108 , the distributed metadata store  110 , and the distributed file system  112  to manage and store one or more snapshots of a virtual machine. Each snapshot of the virtual machine may correspond with a point in time version of the virtual machine. The data management system  102  may generate and manage a list of versions for the virtual machine. Each version of the virtual machine may map to or reference one or more chunks and/or one or more files stored within the distributed file system  112 . Combined together, the one or more chunks and/or the one or more files stored within the distributed file system  112  may comprise a full image of the version of the virtual machine. 
     Some examples of the present disclosure identify and capture specific file system data and auditable events (also termed audit events, herein). Such system data and events may be classified and/or filtered to assist in identifying anomalous activity such as unauthorized user access to files in a file system and the infiltration of ransomware therein. 
     Some examples of the present disclosure identify and capture other specific file system data to assist in identifying anomalous activity such as unauthorized user access to files in a file system. In this regard, some examples extract spatial data from spreadsheet formatted text. This additional data is used to increase the speed and accuracy of mini-filters or text content verifiers, identifying various types of data. 
     Traditional content analyzers process text and utilize just a single dimension of text position in the string. For spreadsheet analysis, some examples of the present disclosure extract additional spatial data by parsing the spreadsheet formatted text which allows an examination of spreadsheet row and column dimensions too. Data constructs within the spreadsheet such as tables and headers can be identified. Extracting and processed spatial data can be used to improve text content verifiers. 
     In some examples, extracted spreadsheet metadata may increase the speed and reach of text content verifiers. For example, spatial data may only need to be extracted once per document, saving computation time. This extracted data also allows a tiered approach to be applied to content analysis in some examples. For example, a tiered arrangement for an array of text content verifiers may include splitting the verifiers into a first tier for fast keyword searches on prioritized or expedited areas of the document, and a second tier identifying high-risk sub-tables on which slower, more complicated verifiers are run. The spreadsheet metadata may also allow a significant reduction in the size of sub-tables on which the verifiers may be instructed to run, further reducing computation time. 
     In some examples, the use of spreadsheet metadata in content verifiers may increase their accuracy. For example, while other approaches rely on character proximity-based keyword searches, the utilization of spreadsheet metadata allows the implementation of row proximity-based keyword searches. This may be particularly useful for verifying spreadsheets and tables in which a single column header is used as a keyword for the entire column of data below the header. In contrast, when using conventional character proximity, potential “hits” of anomalous data occurring outside a proximity range (for example, a specified number of rows below the column header) would not contain keywords, resulting in false positives. 
     Some embodiments of the present disclosure include methods. With reference to  FIG. 4 , an example method  400  may include, at operation  402 , identifying a spreadsheet among a base file and one or more forward incremental files, the spreadsheet including formatted text and row and column dimensions; at operation  404 , generating spreadsheet spatial metadata by parsing the formatted text and row and column dimensions; and, at operation  406 , supplying the spreadsheet spatial metadata to the text content verifier. 
     With reference to  FIG. 5 , an example method  500  may include, at operation  502 , identifying a spreadsheet stored in a file in a monitored computer system, the spreadsheet including formatted text and row and column dimensions; at operation  504 , generating spreadsheet spatial metadata by parsing the formatted text and row and column dimensions; and, at operation  506 , supplying the spreadsheet spatial metadata to the text content verifier. 
     With reference to  FIG. 6 , an example method  600  may include, at operation  602 , identifying a spreadsheet stored in a file in the storage device, the spreadsheet including formatted text and row and column dimensions; at operation  604 , generating spreadsheet spatial metadata by parsing the formatted text and row and column dimensions, and, at operation  606 , supplying the spreadsheet spatial metadata to the text content verifier. 
     In some aspects of the above example methods, the operations further comprise identifying a data construct in the spreadsheet, the data construct including a table or a header; and incorporating the identified data structure in the spreadsheet spatial metadata. The text content verifier may be included in a tiered array of text content verifiers and wherein the spreadsheet special metadata is supplied to the tiered array of text content verifiers. 
     In some examples, a first text content verifier in the array of tiered text content verifiers is supplied spreadsheet spatial metadata comprising keyword data sourced from a first ranked region of the spreadsheet, and a second text content verifier in the tiered array of text content verifiers is supplied spreadsheet spatial comprising aspects of the data construct sourced from a second ranked region of the spreadsheet. In some examples, the keyword data is sourced from a proximity-based keyword search based on a selection of a row or column dimension of the spreadsheet. In some examples, the operations further comprise incorporating at least some of the spreadsheet spatial metadata in a key to verify an audit event in a series of audit events including at least a create event, a write event, a read event, or a cleanup event. 
       FIG. 7  is a block diagram illustrating an example of a computer software architecture for data classification and information security that may be installed on a machine, according to some example embodiments.  FIG. 7  is merely a non-limiting example of a software architecture, and it will be appreciated that many other architectures may be implemented to facilitate the functionality described herein. The software architecture  702  may be executing on hardware such as a machine  800  of  FIG. 8  that includes, among other things, processors  910 , memory  930 , and I/O components  950 . A representative hardware layer  704  of  FIG. 7  is illustrated and can represent, for example, the machine  900  of  FIG. 9 . The representative hardware layer  804  of  FIG. 7  comprises one or more processing units  706  having associated executable instructions  708 . The executable instructions  708  represent the executable instructions of the software architecture  702 , including implementation of the methods, modules, and so forth described herein. The hardware layer  704  also includes memory or storage modules  710 , which also have the executable instructions  708 . The hardware layer  704  may also comprise other hardware  710 , which represents any other hardware of the hardware layer  704 , such as the other hardware illustrated as part of the machine  700 . 
     In the example architecture of  FIG. 7 , the software architecture  702  may be conceptualized as a stack of layers, where each layer provides particular functionality. For example, the software architecture  702  may include layers such as an operating system  714 , libraries  716 , frameworks/middleware  718 , applications  720 , and a presentation layer  744 . Operationally, the applications  720  or other components within the layers may invoke API calls  724  through the software stack and receive a response, returned values, and so forth (illustrated as messages  726 ) in response to the API calls  724 . The layers illustrated are representative in nature, and not all software architectures have all layers. For example, some mobile or special purpose operating systems may not provide a frameworks/middleware  718  layer, while others may provide such a layer. Other software architectures may include additional or different layers. 
     The operating system  714  may manage hardware resources and provide common services. The operating system  714  may include, for example, a kernel  728 , services  730 , and drivers  732 . The kernel  728  may act as an abstraction layer between the hardware and the other software layers. For example, the kernel  728  may be responsible for memory management, processor management (e.g., scheduling), component management, networking, security settings, and so on. The services  730  may provide other common services for the other software layers. The drivers  732  may be responsible for controlling or interfacing with the underlying hardware. For instance, the drivers  732  may include display drivers, camera drivers, Bluetooth® drivers, flash memory drivers, serial communication drivers (e.g., Universal Serial Bus (USB) drivers), Wi-Fi® drivers, audio drivers, power management drivers, and so forth depending on the hardware configuration. 
     The libraries  716  may provide a common infrastructure that may be utilized by the applications  720  and/or other components and/or layers. The libraries  716  typically provide functionality that allows other software modules to perform tasks in an easier fashion than by interfacing directly with the underlying operating system  714  functionality (e.g., kernel  728 , services  730 , or drivers  732 ). The libraries  716  may include system libraries  734  (e.g., C standard library) that may provide functions such as memory allocation functions, string manipulation functions, mathematic functions, and the like. In addition, the libraries  716  may include API libraries  736  such as media libraries (e.g., libraries to support presentation and manipulation of various media formats such as MPEG4, H.264, MP3, AAC, AMR, JPG, PNG), graphics libraries (e.g., an OpenGL framework that may be used to render 2D and 3D graphic content on a display), database libraries (e.g., SQLite that may provide various relational database functions), web libraries (e.g., WebKit that may provide web browsing functionality), and the like. The libraries  716  may also include a wide variety of other libraries  738  to provide many other APIs to the applications  720  and other software components/modules. 
     The frameworks  718  (also sometimes referred to as middleware) may provide a higher-level common infrastructure that may be utilized by the applications  720  or other software components/modules. For example, the frameworks  718  may provide various graphic user interface (GUI) functions, high-level resource management, high-level location services, and so forth. The frameworks  718  may provide a broad spectrum of other APIs that may be utilized by the applications  720  and/or other software components/modules, some of which may be specific to a particular operating system or platform. 
     The applications  720  include built-in applications  740  and/or third-party applications  742 . Examples of representative built-in applications  740  may include, but are not limited to, a home application, a contacts application, a browser application, a book reader application, a location application, a media application, a messaging application, or a game application. 
     The third-party applications  742  may include any of the built-in applications  740 , as well as a broad assortment of other applications. In a specific example, the third-party applications  742  (e.g., an application developed using the Android™ or iOS™ software development kit (SDK) by an entity other than the vendor of the particular platform) may be mobile software running on a mobile operating system such as iOS™, Android™, Windows® Phone, or other mobile operating systems. In this example, the third-party applications  742  may invoke the API calls  724  provided by the mobile operating system such as the operating system  714  to facilitate functionality described herein. 
     The applications  720  may utilize built-in operating system functions (e.g., kernel  728 , services  730 , or drivers  732 ), libraries (e.g., system  734 , APIs  736 , and other libraries  738 ), or frameworks/middleware  718  to create user interfaces to interact with users of the system. Alternatively, or additionally, in some systems, interactions with a user may occur through a presentation layer, such as the presentation layer  744 . In these systems, the application/module “logic” can be separated from the aspects of the application/module that interact with the user. 
     Some software architectures utilize virtual machines. In the example of  FIG. 7 , this is illustrated by a virtual machine  748 . A virtual machine creates a software environment where applications/modules can execute as if they were executing on a hardware machine e.g., the machine  900  of  FIG. 9 , for example). A virtual machine  748  is hosted by a host operating system (e.g., operating system  714 ) and typically, although not always, has a virtual machine monitor  746 , which manages the operation of the virtual machine  748  as well as the interface with the host operating system (e.g., operating system  714 ). A software architecture executes within the virtual machine  748 , such as an operating system  750 , libraries  752 , frameworks/middleware  754 , applications  756 , or a presentation layer  758 . These layers of software architecture executing within the virtual machine  748  can be the same as corresponding layers previously described or may be different. 
       FIG. 8  is a block diagram  800  illustrating an architecture of software  802 , which can be installed on any one or more of the devices described above.  FIG. 8  is merely a non-limiting example of a software architecture, and it will be appreciated that many other architectures can be implemented to facilitate the functionality described herein. In various embodiments, the software  802  is implemented by hardware such as a machine  900  of  FIG. 9  that includes processors  1110 , memory  1130 , and I/O components  1150 . In this example architecture, the software  802  can be conceptualized as a stack of layers where each layer may provide a particular functionality. For example, the software  802  includes layers such as an operating system  804 , libraries  806 , frameworks  808 , and applications  810 . Operationally, the applications  810  invoke application programming interface (API) calls  812  through the software stack and receive messages  814  in response to the API calls  812 , consistent with some embodiments. 
     In various implementations, the operating system  804  manages hardware resources and provides common services. The operating system  804  includes, for example, a kernel  820 , services  822 , and drivers  824 . The kernel  820  acts as an abstraction layer between the hardware and the other software layers, consistent with some embodiments. For example, the kernel  820  provides memory management, processor management (e.g., scheduling), component management, networking, and security settings, among other functionality. The services  822  can provide other common services for the other software layers. The drivers  824  are responsible for controlling or interfacing with the underlying hardware, according to some embodiments. For instance, the drivers  824  can include display drivers, camera drivers, BLUETOOTH® or BLUETOOTH® Low Energy drivers, flash memory drivers, serial communication drivers (e.g., Universal Serial Bus (USB) drivers), WI-FI® drivers, audio drivers, power management drivers, and so forth. 
     In some embodiments, the libraries  806  provide a low-level common infrastructure utilized by the applications  810 . The libraries  806  can include system libraries  830  (e.g., C standard library) that can provide functions such as memory allocation functions, string manipulation functions, mathematic functions, and the like. In addition, the libraries  806  can include API libraries  832  such as media libraries (e.g., libraries to support presentation and manipulation of various media formats such as Moving Picture Experts Group-4 (MPEG4), Advanced Video Coding (H.264 or AVC), Moving Picture Experts Group Layer-3 (MP3), Advanced Audio Coding (AAC), Adaptive Multi-Rate (AMR) audio codec, Joint Photographic Experts Group (JPEG or JPG), or Portable Network Graphics (PNG)), graphics libraries (e.g., an OpenGL framework used to render in two dimensions (2D) and three dimensions (3D) in a graphic content on a display), database libraries (e.g., SQLite to provide various relational database functions), web libraries (e.g., WebKit to provide web browsing functionality), and the like. The libraries  806  can also include a wide variety of other libraries  834  to provide many other APIs to the applications  810 . 
     The frameworks  808  provide a high-level common infrastructure that can be utilized by the applications  810 , according to some embodiments. For example, the frameworks  808  provide various graphic user interface (GUI) functions, high-level resource management, high-level location services, and so forth. The frameworks  808  can provide a broad spectrum of other APIs that can be utilized by the applications  810 , some of which may be specific to a particular operating system or platform. 
     In an example embodiment, the applications  810  include a home application  850 , a contacts application  852 , a browser application  854 , a book reader application  856 , a location application  858 , a media application  860 , a messaging application  862 , a game application  864 , and a broad assortment of other applications such as a third-party application  866 . According to some embodiments, the applications  810  are programs that execute functions defined in the programs. Various programming languages can be employed to create one or more of the applications  810 , structured in a variety of manners, such as object-oriented programming languages (e.g., Objective-C, Java, or C++) or procedural programming languages (e.g., C or assembly language). In a specific example, the third-party application  866  (e.g., an application developed using the ANDROID™ or IOS™ software development kit (SDK) by an entity other than the vendor of the particular platform) may be mobile software running on a mobile operating system such as IOS™, ANDROID™ WINDOWS® Phone, or another mobile operating system. In this example, the third-party application  866  can invoke the API calls  810  provided by the operating system  804  to facilitate functionality described herein. 
       FIG. 9  illustrates a diagrammatic representation of a machine  900  in the form of a computer system within which a set of instructions may be executed for causing the machine to perform any one or more of the methodologies discussed herein, according to an example embodiment. Specifically,  FIG. 9  shows a diagrammatic representation of the machine  900  in the example form of a computer system, within which instructions  916  (e.g., software, a program, an application, an applet, an app, or other executable code) for causing the machine  900  to perform any one or more of the methodologies discussed herein may be executed. Additionally, or alternatively, the instructions  916  may implement the operations of the methods shown in  FIGS. 4-6 , or as elsewhere described herein. 
     The instructions  916  transform the general, non-programmed machine  900  into a particular machine  900  programmed to carry out the described and illustrated functions in the manner described. In alternative embodiments, the machine  900  operates as a standalone device or may be coupled (e.g., networked) to other machines. In a networked deployment, the machine  900  may operate in the capacity of a server machine or a client machine in a server-client network environment, or as a peer machine in a peer-to-peer (or distributed) network environment. The machine  900  may comprise, but not be limited to, a server computer, a client computer, a personal computer (PC), a tablet computer, a laptop computer, a netbook, a set-top box (STB), a PDA, an entertainment media system, a cellular telephone, a smart phone, a mobile device, a wearable device (e.g., a smart watch), a smart home device (e.g., a smart appliance), other smart devices, a web appliance, a network router, a network switch, a network bridge, or any machine capable of executing the instructions  916 , sequentially or otherwise, that specify actions to be taken by the machine  900 . Further, while only a single machine  900  is illustrated, the term “machine” shall also be taken to include a collection of machines  900  that individually or jointly execute the instructions  916  to perform any one or more of the methodologies discussed herein. 
     The machine  900  may include processors  910 , memory  930 , and I/O components  950 , which may be configured to communicate with each other such as via a bus  902 . In an example embodiment, the processors  910  (e.g., a Central Processing Unit (CPU), a Reduced Instruction Set Computing (RISC) processor, a Complex Instruction Set Computing (CISC) processor, a Graphics Processing Unit (GPU), a Digital Signal Processor (DSP), an ASIC, a Radio-Frequency Integrated Circuit (RFIC), another processor, or any suitable combination thereof) may include, for example, a processor  912  and a processor  914  that may execute the instructions  916 . The term “processor” is intended to include multi-core processors that may comprise two or more independent processors (sometimes referred to as “cores”) that may execute instructions contemporaneously. Although  FIG. 9  shows multiple processors  910 , the machine  900  may include a single processor with a single core, a single processor with multiple cores (e.g., a multi-core processor), multiple processors with a single core, multiple processors with multiples cores, or any combination thereof. 
     The memory  930  may include a main memory  932 , a static memory  934 , and a storage unit  936 , each accessible to the processors  910  such as via the bus  902 . The main memory  930 , the static memory  934 , and storage unit  936  store the instructions  916  embodying any one or more of the methodologies or functions described herein. The instructions  916  may also reside, completely or partially, within the main memory  932 , within the static memory  934 , within the storage unit  936 , within at least one of the processors  910  (e.g., within the processor&#39;s cache memory), or any suitable combination thereof, during execution thereof by the machine  900 . 
     The I/O components  950  may include a wide variety of components to receive input, provide output, produce output, transmit information, exchange information, capture measurements, and so on. The specific I/O components  950  that are included in a particular machine will depend on the type of machine. For example, portable machines such as mobile phones will likely include a touch input device or other such input mechanisms, while a headless server machine will likely not include such a touch input device. It will be appreciated that the I/O components  950  may include many other components that are not shown in  FIG. 9 . The I/O components  950  are grouped according to functionality merely for simplifying the following discussion and the grouping is in no way limiting. In various example embodiments, the I/O components  950  may include output components  952  and input components  954 . The output components  952  may include visual components (e.g., a display such as a plasma display panel (PDP), a light emitting diode (LED) display, a liquid crystal display (LCD), a projector, or a cathode ray tube (CRT)), acoustic components (e.g., speakers), haptic components (e.g., a vibratory motor, resistance mechanisms), other signal generators, and so forth. The input components  954  may include alphanumeric input components (e.g., a keyboard, a touch screen configured to receive alphanumeric input, a photo-optical keyboard, or other alphanumeric input components), point-based input components (e.g., a mouse, a touchpad, a trackball, a joystick, a motion sensor, or another pointing instrument), tactile input components (e.g., a physical button, a touch screen that provides location and/or force of touches or touch gestures, or other tactile input components), audio input components (e.g., a microphone), and the like. 
     In further example embodiments, the I/O components  950  may include biometric components  956 , motion components  958 , environmental components  960 , or position components  962 , among a wide array of other components. For example, the biometric components  956  may include components to detect expressions (e.g., hand expressions, facial expressions, vocal expressions, body gestures, or eye tracking), measure biosignals (e.g., blood pressure, heart rate, body temperature, perspiration, or brain waves), identify a person (e.g., voice identification, retinal identification, facial identification, fingerprint identification, or electroencephalogram-based identification), and the like. The motion components  958  may include acceleration sensor components (e.g., accelerometer), gravitation sensor components, rotation sensor components (e.g., gyroscope), and so forth. The environmental components  960  may include, for example, illumination sensor components (e.g., photometer), temperature sensor components (e.g., one or more thermometers that detect ambient temperature), humidity sensor components, pressure sensor components (e.g., barometer), acoustic sensor components (e.g., one or more microphones that detect background noise), proximity sensor components (e.g., infrared sensors that detect nearby objects), gas sensors (e.g., gas detection sensors to detection concentrations of hazardous gases for safety or to measure pollutants in the atmosphere), or other components that may provide indications, measurements, or signals corresponding to a surrounding physical environment. The position components  962  may include location sensor components (e.g., a GPS receiver component), altitude sensor components (e.g., altimeters or barometers that detect air pressure from which altitude may be derived), orientation sensor components (e.g., magnetometers), and the like. 
     Communication may be implemented using a wide variety of technologies. The I/O components  950  may include communication components  964  operable to couple the machine  900  to a network  980  or devices  970  via a coupling  982  and a coupling  972 , respectively. For example, the communication components  964  may include a network interface component or another suitable device to interface with the network  980 . In further examples, the communication components  964  may include wired communication components, wireless communication components, cellular communication components, Near Field Communication (NFC) components, Bluetooth® components (e.g., Bluetooth® Low Energy), Wi-Fi® components, and other communication components to provide communication via other modalities. The devices  970  may be another machine or any of a wide variety of peripheral devices (e.g., a peripheral device coupled via a USB). 
     Moreover, the communication components  964  may detect identifiers or include components operable to detect identifiers. For example, the communication components  964  may include Radio Frequency Identification (RFID) tag reader components, NFC smart tag detection components, optical reader components (e.g., an optical sensor to detect one-dimensional bar codes such as Universal Product Code (UPC) bar code, multi-dimensional bar codes such as Quick Response (QR) code, Aztec code, Data Matrix, Dataglyph, MaxiCode, PDF417, Ultra Code, UCC RSS-2D bar code, and other optical codes), or acoustic detection components (e.g., microphones to identify tagged audio signals). In addition, a variety of information may be derived via the communication components  964 , such as location via Internet Protocol (IP) geolocation, location via Wi-Fi® signal triangulation, location via detecting an NFC beacon signal that may indicate a particular location, and so forth. 
     The various memories (i.e.,  930 ,  932 ,  934 , and/or memory of the processor(s)  910 ) and/or storage unit  936  may store one or more sets of instructions and data structures (e.g., software) embodying or utilized by any one or more of the methodologies or functions described herein. These instructions (e.g., the instructions  916 ), when executed by processor(s)  910 , cause various operations to implement the disclosed embodiments. 
     As used herein, the terms “machine-storage medium,” “device-storage medium,” “computer-storage medium” mean the same thing and may be used interchangeably in this disclosure. The terms refer to a single or multiple storage devices and/or media (e.g., a centralized or distributed database, and/or associated caches and servers) that store executable instructions and/or data. The terms shall accordingly be taken to include, but not be limited to, solid-state memories, and optical and magnetic media, including memory internal or external to processors. Specific examples of machine-storage media, computer-storage media and/or device-storage media include non-volatile memory, including by way of example semiconductor memory devices, e.g., erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), FPGA, and flash memory devices; magnetic disks such as internal hard disks and removable disks; magneto-optical disks; and CD-ROM and DVD-ROM disks. The terms “machine-storage media,” “computer-storage media,” and “device-storage media” specifically exclude carrier waves, modulated data signals, and other such media, at least some of which are covered under the term “signal medium” discussed below. 
     In various example embodiments, one or more portions of the network  980  may be an ad hoc network, an intranet, an extranet, a VPN, a LAN, a WLAN, a WAN, a WWAN, a MAN, the Internet, a portion of the Internet, a portion of the PSTN, a plain old telephone service (POTS) network, a cellular telephone network, a wireless network, a Wi-Fi® network, another type of network, or a combination of two or more such networks. For example, the network  980  or a portion of the network  980  may include a wireless or cellular network, and the coupling  982  may be a Code Division Multiple Access (CDMA) connection, a Global System for Mobile communications (GSM) connection, or another type of cellular or wireless coupling. In this example, the coupling  982  may implement any of a variety of types of data transfer technology, such as Single Carrier Radio Transmission Technology (1×RTT), Evolution-Data Optimized (EVDO) technology, General Packet Radio Service (GPRS) technology, Enhanced Data rates for GSM Evolution (EDGE) technology, third Generation Partnership Project (3GPP) including 3G, fourth generation wireless (4G) networks, Universal Mobile Telecommunications System (UMTS), High Speed Packet Access (HSPA), Worldwide Interoperability for Microwave Access (WiMAX), Long Term Evolution (LTE) standard, others defined by various standard-setting organizations, other long range protocols, or other data transfer technology. 
     The instructions  916  may be transmitted or received over the network  980  using a transmission medium via a network interface device (e.g., a network interface component included in the communication components  964 ) and utilizing any one of a number of well-known transfer protocols (e.g., hypertext transfer protocol (HTTP)). Similarly, the instructions  916  may be transmitted or received using a transmission medium via the coupling  972  (e.g., a peer-to-peer coupling) to the devices  970 . The terms “transmission medium” and “signal medium” mean the same thing and may be used interchangeably in this disclosure. The terms “transmission medium” and “signal medium” shall be taken to include any intangible medium that is capable of storing, encoding, or carrying the instructions  916  for execution by the machine  900 , and includes digital or analog communications signals or other intangible media to facilitate communication of such software. Hence, the terms “transmission medium” and “signal medium” shall be taken to include any form of modulated data signal, carrier wave, and so forth. The term “modulated data signal” means a signal that has one or more of its characteristics set or changed in such a matter as to encode information in the signal. 
     The terms “machine-readable medium,” “computer-readable medium” and “device-readable medium” mean the same thing and may be used interchangeably in this disclosure. The terms are defined to include both machine-storage media and transmission media. Thus, the terms include both storage devices/media and carrier waves/modulated data signals. 
     Although an embodiment has been described with reference to specific example embodiments, it will be evident that various modifications and changes may be made to these embodiments without departing from the broader spirit and scope of the invention. Accordingly, the specification and drawings are to be regarded in an illustrative rather than a restrictive sense. The accompanying drawings that form a part hereof, show by way of illustration, and not of limitation, specific embodiments in which the subject matter may be practiced. The embodiments illustrated are described in sufficient detail to enable those skilled in the art to practice the teachings disclosed herein. Other embodiments may be utilized and derived therefrom, such that structural and logical substitutions and changes may be made without departing from the scope of this disclosure. This Detailed Description, therefore, is not to be taken in a limiting sense, and the scope of various embodiments is defined only by the appended claims, along with the full range of equivalents to which such claims are entitled. 
     Such embodiments of the inventive subject matter may be referred to herein, individually and/or collectively, by the term “invention” merely for convenience and without intending to voluntarily limit the scope of this application to any single invention or inventive concept if more than one is in fact disclosed. Thus, although specific embodiments have been illustrated and described herein, it should be appreciated that any arrangement calculated to achieve the same purpose may be substituted for the specific embodiments shown. This disclosure is intended to cover any and all adaptations or variations of various embodiments. Combinations of the above embodiments, and other embodiments not specifically described herein, will be apparent to those of skill in the art upon reviewing the above description.