Embodiments relate to techniques for managing replication of data. More particularly, embodiments relate to techniques for selectively obfuscating selected data (e.g., personally identifiable information) when replicating data.
Data replication generally refers to the process of copying data. Data replication is a common technique to provide data synchronization as well as other advantages. Data replication is usually an ongoing process in which transactions or other data sets are copied and stored in multiple locations. However, there are conditions under which certain data should not be replicated in the standard manner. This has been a complex situation that has been difficult to solve in a clean and efficient manner.
Embodiments of the invention are illustrated by way of example, and not by way of limitation, in the figures of the accompanying drawings in which like reference numerals refer to similar elements.
In the following description, numerous specific details are set forth. However, embodiments of the invention may be practiced without these specific details. In other instances, well-known structures and techniques have not been shown in detail in order not to obscure the understanding of this description.
As used herein, tenant includes a group of users who share a common access with specific privileges to a software instance. A multi-tenant architecture provides a tenant with a dedicated share of the software instance typically including one or more of tenant specific data, user management, tenant-specific functionality, configuration, customizations, non-functional properties, associated applications, etc. Multi-tenancy contrasts with multi-instance architectures, where separate software instances operate on behalf of different tenants.
In one embodiment, a group of tenants (or organizations) are grouped together in an instance, or a pod. In instance is a self-contained unit that has all that is required to provide a multitenant platform including, for example, one or more application servers, one or more database servers, at least one database, search and file systems, etc. Each tenant/organization is allocated a pod in which their data resides.
For example, a replicated table can have user information from all users from all instances (e.g., core.all_users) so that users can have access regardless of the instance they are connected to. In many cases, the replication process runs continually in the background on every instance. Each instances accts as a client (e.g., 120, 170) to ask all known peers for updates and as a server (e.g., 130, 180) to provide data to all known peers. However, as discussed herein, replication of some data can have data residency restrictions.
In one embodiment, each instance detects changes to data made within that instance and can package change information into chunks having associated metadata about the changes. These chunks are sent to other instances where they are persisted locally and applied (e.g., upserted) to the corresponding table. In addition to serving their own changes, instances can also act as a proxy for changes made elsewhere (e.g., if they are acting as a “leader” of a pod or data center), in which case peers can request changes that are not their own and the server can reply with a local copy of the changes.
As described herein, replication mechanisms can be provided that determine whether to obfuscate one or more fields in a replicated entity based on properties of a source zone or pod. In one embodiment, all pods are designated either “standard” or “public,” but additional and/or different designations could also be supported. In various embodiments, unobfuscated replication is not allowed for personally identifiable information (PII) flowing from standard to public pods.
In various embodiments, one or more pods can be grouped into a zone. Zones can be based on, for example, geography. Zones can be based on other considerations as well, for example, security considerations, licensing levels, customer type. In one embodiment, a zone can be a subset of a data center. In another embodiment, a zone can include subsets of multiple data centers so that the zone spans multiple data centers. Conceptually, a zone is a layer above a data center. The techniques described herein can be useful to, for example, prevent PII data from leaving a set of pods that have data residency requirements.
Many of the examples provided herein are related to data residency and/or data sovereignty requirements; however, the embodiments described herein are more broadly applicable. Data residency and data sovereignty refer to the physical location and legal requirements for data stored in the corresponding geographic location.
Each jurisdiction (e.g., United States, European Union) can have its own data residency laws and requirements. These laws and requirements can control what data is used (including movement of data) and what data should be protected. For example, the European Union has privacy laws relating to PII. Entities that store and utilize data must comply with these laws and requirements.
Various embodiments are described that can be utilized to comply with data residency requirements. In one example embodiment, four server categories are utilized: 1) Standard; 2) Standard Data Residency; 3) Public; and 4) Public Data Residency. Using these four categories the following three data residency requirements can be enforced: 1) PII cannot leave Standard Data Residency servers unobfuscated; 2) PII data is not sent to Public or Public Data Residency servers unobfuscated; and 3) PII data in a Public server does not leave its geographic region. This is but one example of a configuration to manage data with specific data residency requirements. Other configurations can also be supported.
In one embodiment, replication includes four basic processes: 1) change detection; 2) change serving; 3) change requests; and 4) change upserts. Techniques for each of these processes are described in greater detail below; however, different techniques can also be utilized.
When a row in a replicated table (e.g., core.all_users) is modified, a database trigger writes to an indexing queue table (e.g., core.last_unindexed), containing the partition, entity and date of the change but not the specific rows that changed. A replication change detection chron job periodically runs and pulls aggregates of changed rows and breaks them to manageable segments. The replicator creates chunk definitions based on metadata and caches the chunks to the database so that a subsequent database query is not needed. These chunk definitions are persisted in the database and are ready to serve. This can result in virtual streams of chunks that are independent of each other and can be processed in parallel.
In one embodiment, for deletes, in addition to triggering an indexer, a trigger that writes the deleted key to a table (e.g., core.replication_record_deletion) can be utilized. These delete markers are treated as inserts and updates to that any query that gets modifications from the underlying table gets both together.
In one embodiment, during the change detection process, the underlying records are selected from the data base in order to determine the chunk's properties. In one embodiment, the process can cache a serialized version of the chunk immediately. In one embodiment, to support change detection, a replicated table has a modstamp (or similar) column and a server ID (or similar) column. In general, as a result of the change detection mechanism(s), any modification to the replicated table results in one or more chunks being created that the server can serve on request.
In one embodiment, serving data is a passive process. Requests can be made over a HyperText Transfer Protocol (HTTP) and can be served by a servlet running on a web server. In one embodiment, the data are serialized on the server and deserialized by objects on the receiving client.
In various embodiments, the techniques described herein can provide dynamic management of PII protection based on zones and/or categories. In one embodiment, this provides the ability to virtually partition a cloud-based environment to support multiple data residency requirements based on zones. That is, different data residency requirements/restrictions can be supported for different zones. In one embodiment, each zone includes at least one pod, but pods are not required to be completely in the same physical location.
In one embodiment, obfuscation is accomplished utilizing a one-way hash function that is unique, but non-reversible. The original data is protected because the process is non-reversible. The receiving entity/device receives an encrypted string generated from the original data, but because that encryption is non-reversible, the original data (e.g., PII) is protected. Using these techniques, the following PII protection requirements can be provided: PII data is not replicated in the clear from a zone (or pod) of a first category (e.g., a public cloud pod), and PII data is not replicated in the clear from a secure zone (or pod) of a second category (e.g., a government pod, secure corporate zone). Additional and/or different categories can also be supported.
The example of
Continuing with the geographic region based zone architecture, each pod can be designated to a zone corresponding to the region in which the pod resides. For example, a pod in a data center located in Italy can be in the zone for Italy or for the European Union (EU). Thus, when data is replicated (or otherwise copied or moved), the data residency requirements can be applied to the data moving out of the pod, if necessary.
Data stored in a computing environment can be organized in a multi-tiered structure with privacy, data residency and/or data security requirements associated with the data or the tiers, 210. In one embodiment, the data is stored in an on-demand services environment that can also provide a multitenant architecture. Various embodiments for on-demand service environments are described in greater detail below.
In one embodiment, data is stored by computing platforms (e.g., server computer systems, desktop computer system) that are physically located in one or more data systems that are organized as pods, zones and/or other groupings. As discussed above, zones can be utilized to group pods by geography and apply data residency and/or PII protection requirements and restrictions.
In one embodiment, zones can be groupings of pods based on geographical locations of data and/or the source of data, each of which can have a corresponding restriction (or limitation) on how the data can be handled. In one embodiment, for example, a zone can correspond to national boundaries such that all data centers within the nation are in the same zone. Other zone configurations can be supported, for example, zones can correspond to service level agreements (SLAs), etc. In some embodiments, data obfuscation can be used to satisfy these requirements; however, in other embodiments, data movement or copying may be prevented.
A request to copy/move/replicate data is received, 220. As discussed above, replication can be an ongoing process that periodically makes backup copies of data and/or changes to existing data. The techniques described herein can also be applied to requests to copy and/or move data. For example, if a user using a computing platform geographically outside of the data residency zone, obfuscation can be applied to the results of the request.
In response to the request, the receiving environment analyzes the structure and corresponding requirements, 230, to determine what (if any) data protection requirements should be applied in servicing the request. In one embodiment, as discussed above, PII portions of the requested data can be obfuscated using various obfuscation techniques, 240 after which the request can be serviced, 250. If obfuscation is not required, 230, the request can be serviced without obfuscation, 250.
Environment 310 is an environment in which an on-demand database service exists. User system 312 may be any machine or system that is used by a user to access a database user system. For example, any of user systems 312 can be a handheld computing device, a mobile phone, a laptop computer, a work station, and/or a network of computing devices. As illustrated in herein
An on-demand database service, such as system 316, is a database system that is made available to outside users that do not need to necessarily be concerned with building and/or maintaining the database system, but instead may be available for their use when the users need the database system (e.g., on the demand of the users). Some on-demand database services may store information from one or more tenants stored into tables of a common database image to form a multi-tenant database system (MTS). Accordingly, “on-demand database service 316” and “system 316” will be used interchangeably herein. A database image may include one or more database objects. A relational database management system (RDMS) or the equivalent may execute storage and retrieval of information against the database object(s). Application platform 318 may be a framework that allows the applications of system 316 to run, such as the hardware and/or software, e.g., the operating system. In an embodiment, on-demand database service 316 may include an application platform 318 that enables creation, managing and executing one or more applications developed by the provider of the on-demand database service, users accessing the on-demand database service via user systems 312, or third party application developers accessing the on-demand database service via user systems 312.
The users of user systems 312 may differ in their respective capacities, and the capacity of a particular user system 312 might be entirely determined by permissions (permission levels) for the current user. For example, where a salesperson is using a particular user system 312 to interact with system 316, that user system has the capacities allotted to that salesperson. However, while an administrator is using that user system to interact with system 316, that user system has the capacities allotted to that administrator. In systems with a hierarchical role model, users at one permission level may have access to applications, data, and database information accessible by a lower permission level user, but may not have access to certain applications, database information, and data accessible by a user at a higher permission level. Thus, different users will have different capabilities with regard to accessing and modifying application and database information, depending on a user's security or permission level.
Network 314 is any network or combination of networks of devices that communicate with one another. For example, network 314 can be any one or any combination of a LAN (local area network), WAN (wide area network), telephone network, wireless network, point-to-point network, star network, token ring network, hub network, or other appropriate configuration. As the most common type of computer network in current use is a TCP/IP (Transfer Control Protocol and Internet Protocol) network, such as the global internetwork of networks often referred to as the “Internet” with a capital “I,” that network will be used in many of the examples herein. However, it should be understood that the networks that one or more implementations might use are not so limited, although TCP/IP is a frequently implemented protocol.
User systems 312 might communicate with system 316 using TCP/IP and, at a higher network level, use other common Internet protocols to communicate, such as HTTP, FTP, AFS, WAP, etc. In an example where HTTP is used, user system 312 might include an HTTP client commonly referred to as a “browser” for sending and receiving HTTP messages to and from an HTTP server at system 316. Such an HTTP server might be implemented as the sole network interface between system 316 and network 314, but other techniques might be used as well or instead. In some implementations, the interface between system 316 and network 314 includes load sharing functionality, such as round-robin HTTP request distributors to balance loads and distribute incoming HTTP requests evenly over a plurality of servers. At least as for the users that are accessing that server, each of the plurality of servers has access to the MTS' data; however, other alternative configurations may be used instead.
In one embodiment, system 316, shown in
One arrangement for elements of system 316 is shown in
Several elements in the system shown in
According to one embodiment, each user system 312 and all of its components are operator configurable using applications, such as a browser, including computer code run using a central processing unit such as an Intel Core series processor or the like. Similarly, system 316 (and additional instances of an MTS, where more than one is present) and all of their components might be operator configurable using application(s) including computer code to run using a central processing unit such as processor system 317, which may include an Intel Core series processor or the like, and/or multiple processor units. A computer program product embodiment includes a machine-readable storage medium (media) having instructions stored thereon/in which can be used to program a computer to perform any of the processes of the embodiments described herein. Computer code for operating and configuring system 316 to intercommunicate and to process webpages, applications and other data and media content as described herein are preferably downloaded and stored on a hard disk, but the entire program code, or portions thereof, may also be stored in any other volatile or non-volatile memory medium or device as is well known, such as a ROM or RAM, or provided on any media capable of storing program code, such as any type of rotating media including floppy disks, optical discs, digital versatile disk (DVD), compact disk (CD), microdrive, and magneto-optical disks, and magnetic or optical cards, nanosystems (including molecular memory ICs), or any type of media or device suitable for storing instructions and/or data. Additionally, the entire program code, or portions thereof, may be transmitted and downloaded from a software source over a transmission medium, e.g., over the Internet, or from another server, as is well known, or transmitted over any other conventional network connection as is well known (e.g., extranet, VPN, LAN, etc.) using any communication medium and protocols (e.g., TCP/IP, HTTP, HTTPS, Ethernet, etc.) as are well known. It will also be appreciated that computer code for implementing embodiments can be implemented in any programming language that can be executed on a client system and/or server or server system such as, for example, C, C++, HTML, any other markup language, Java™, JavaScript, ActiveX, any other scripting language, such as VBScript, and many other programming languages as are well known may be used. (Java™ is a trademark of Sun Microsystems, Inc.).
According to one embodiment, each system 316 is configured to provide webpages, forms, applications, data and media content to user (client) systems 312 to support the access by user systems 312 as tenants of system 316. As such, system 316 provides security mechanisms to keep each tenant's data separate unless the data is shared. If more than one MTS is used, they may be located in close proximity to one another (e.g., in a server farm located in a single building or campus), or they may be distributed at locations remote from one another (e.g., one or more servers located in city A and one or more servers located in city B). As used herein, each MTS could include one or more logically and/or physically connected servers distributed locally or across one or more geographic locations. Additionally, the term “server” is meant to include a computer system, including processing hardware and process space(s), and an associated storage system and database application (e.g., OODBMS or RDBMS) as is well known in the art. It should also be understood that “server system” and “server” are often used interchangeably herein. Similarly, the database object described herein can be implemented as single databases, a distributed database, a collection of distributed databases, a database with redundant online or offline backups or other redundancies, etc., and might include a distributed database or storage network and associated processing intelligence.
User system 312, network 314, system 316, tenant data storage 322, and system data storage 324 were discussed above in
Application platform 318 includes an application setup mechanism 438 that supports application developers' creation and management of applications, which may be saved as metadata into tenant data storage 322 by save routines 436 for execution by subscribers as one or more tenant process spaces 404 managed by tenant management process 410 for example. Invocations to such applications may be coded using PL/SOQL 434 that provides a programming language style interface extension to API 432. A detailed description of some PL/SOQL language embodiments is discussed in commonly owned U.S. Pat. No. 7,730,478 entitled, “Method and System for Allowing Access to Developed Applicants via a Multi-Tenant Database On-Demand Database Service”, issued Jun. 1, 2010 to Craig Weissman, which is incorporated in its entirety herein for all purposes. Invocations to applications may be detected by one or more system processes, which manage retrieving application metadata 416 for the subscriber making the invocation and executing the metadata as an application in a virtual machine.
Each application server 400 may be communicably coupled to database systems, e.g., having access to system data 325 and tenant data 323, via a different network connection. For example, one application server 4001 might be coupled via the network 314 (e.g., the Internet), another application server 400N-1 might be coupled via a direct network link, and another application server 400N might be coupled by yet a different network connection. Transfer Control Protocol and Internet Protocol (TCP/IP) are typical protocols for communicating between application servers 400 and the database system. However, it will be apparent to one skilled in the art that other transport protocols may be used to optimize the system depending on the network interconnect used.
In certain embodiments, each application server 400 is configured to handle requests for any user associated with any organization that is a tenant. Because it is desirable to be able to add and remove application servers from the server pool at any time for any reason, there is preferably no server affinity for a user and/or organization to a specific application server 400. In one embodiment, therefore, an interface system implementing a load balancing function (e.g., an F5 BIG-IP load balancer) is communicably coupled between the application servers 400 and the user systems 312 to distribute requests to the application servers 400. In one embodiment, the load balancer uses a least connections algorithm to route user requests to the application servers 400. Other examples of load balancing algorithms, such as round robin and observed response time, also can be used. For example, in certain embodiments, three consecutive requests from the same user could hit three different application servers 400, and three requests from different users could hit the same application server 400. In this manner, system 316 is multi-tenant, wherein system 316 handles storage of, and access to, different objects, data and applications across disparate users and organizations.
As an example of storage, one tenant might be a company that employs a sales force where each salesperson uses system 316 to manage their sales process. Thus, a user might maintain contact data, leads data, customer follow-up data, performance data, goals and progress data, etc., all applicable to that user's personal sales process (e.g., in tenant data storage 322). In an example of a MTS arrangement, since all of the data and the applications to access, view, modify, report, transmit, calculate, etc., can be maintained and accessed by a user system having nothing more than network access, the user can manage his or her sales efforts and cycles from any of many different user systems. For example, if a salesperson is visiting a customer and the customer has Internet access in their lobby, the salesperson can obtain critical updates as to that customer while waiting for the customer to arrive in the lobby.
While each user's data might be separate from other users' data regardless of the employers of each user, some data might be organization-wide data shared or accessible by a plurality of users or all of the users for a given organization that is a tenant. Thus, there might be some data structures managed by system 316 that are allocated at the tenant level while other data structures might be managed at the user level. Because an MTS might support multiple tenants including possible competitors, the MTS should have security protocols that keep data, applications, and application use separate. Also, because many tenants may opt for access to an MTS rather than maintain their own system, redundancy, up-time, and backup are additional functions that may be implemented in the MTS. In addition to user-specific data and tenant specific data, system 316 might also maintain system level data usable by multiple tenants or other data. Such system level data might include industry reports, news, postings, and the like that are sharable among tenants.
In certain embodiments, user systems 312 (which may be client systems) communicate with application servers 400 to request and update system-level and tenant-level data from system 316 that may require sending one or more queries to tenant data storage 322 and/or system data storage 324. System 316 (e.g., an application server 400 in system 316) automatically generates one or more SQL statements (e.g., one or more SQL queries) that are designed to access the desired information. System data storage 324 may generate query plans to access the requested data from the database.
Each database can generally be viewed as a collection of objects, such as a set of logical tables, containing data fitted into predefined categories. A “table” is one representation of a data object, and may be used herein to simplify the conceptual description of objects and custom objects. It should be understood that “table” and “object” may be used interchangeably herein. Each table generally contains one or more data categories logically arranged as columns or fields in a viewable schema. Each row or record of a table contains an instance of data for each category defined by the fields. For example, a CRM database may include a table that describes a customer with fields for basic contact information such as name, address, phone number, fax number, etc. Another table might describe a purchase order, including fields for information such as customer, product, sale price, date, etc. In some multi-tenant database systems, standard entity tables might be provided for use by all tenants. For CRM database applications, such standard entities might include tables for Account, Contact, Lead, and Opportunity data, each containing pre-defined fields. It should be understood that the word “entity” may also be used interchangeably herein with “object” and “table”.
In some multi-tenant database systems, tenants may be allowed to create and store custom objects, or they may be allowed to customize standard entities or objects, for example by creating custom fields for standard objects, including custom index fields. U.S. patent application Ser. No. 10/817,161, filed Apr. 2, 2004, entitled “Custom Entities and Fields in a Multi-Tenant Database System”, and which is hereby incorporated herein by reference, teaches systems and methods for creating custom objects as well as customizing standard objects in a multi-tenant database system. In certain embodiments, for example, all custom entity data rows are stored in a single multi-tenant physical table, which may contain multiple logical tables per organization. It is transparent to customers that their multiple “tables” are in fact stored in one large table or that their data may be stored in the same table as the data of other customers.
Reference in the specification to “one embodiment” or “an embodiment” means that a particular feature, structure, or characteristic described in connection with the embodiment is included in at least one embodiment of the invention. The appearances of the phrase “in one embodiment” in various places in the specification are not necessarily all referring to the same embodiment.
While the invention has been described in terms of several embodiments, those skilled in the art will recognize that the invention is not limited to the embodiments described, but can be practiced with modification and alteration within the spirit and scope of the appended claims. The description is thus to be regarded as illustrative instead of limiting.
This application is a continuation of, and claims the benefit of, U.S. patent application Ser. No. 15/600,521 entitled “TECHNIQUES AND ARCHITECTURES FOR SELECTIVE OBFUSCATION OF PERSONALLY IDENTIFIABLE INFORMATION (PII) IN ENVIRONMENTS CAPABLE OF REPLICATING DATA”, filed May 19, 2017, which claims the benefit of U.S. Provisional Patent Application No. 62/501,003 entitled “TECHNIQUES AND ARCHITECTURES FOR SELECTIVE OBFUSCATION OF PERSONALLY IDENTIFIABLE INFORMATION (PII) IN ENVIRONMENTS CAPABLE OF REPLICATING DATA”, filed May 3, 2017, the entire contents of which are incorporated herein by reference.
Number | Name | Date | Kind |
---|---|---|---|
5577188 | Zhu | Nov 1996 | A |
5608872 | Schwartz et al. | Mar 1997 | A |
5649104 | Carleton et al. | Jul 1997 | A |
5715450 | Ambrose et al. | Feb 1998 | A |
5761419 | Schwartz et al. | Jun 1998 | A |
5819038 | Carleton et al. | Oct 1998 | A |
5821937 | Tonelli et al. | Oct 1998 | A |
5831610 | Tonelli et al. | Nov 1998 | A |
5873096 | Lim et al. | Feb 1999 | A |
5918159 | Fomukong et al. | Jun 1999 | A |
5963953 | Cram et al. | Oct 1999 | A |
6092083 | Brodersen et al. | Jul 2000 | A |
6169534 | Raffel et al. | Jan 2001 | B1 |
6178425 | Brodersen et al. | Jan 2001 | B1 |
6189011 | Lim et al. | Feb 2001 | B1 |
6216135 | Brodersen et al. | Apr 2001 | B1 |
6233617 | Rothwein et al. | May 2001 | B1 |
6266669 | Brodersen et al. | Jul 2001 | B1 |
6295530 | Ritchie et al. | Sep 2001 | B1 |
6324568 | Diec | Nov 2001 | B1 |
6324693 | Brodersen et al. | Nov 2001 | B1 |
6336137 | Lee et al. | Jan 2002 | B1 |
D454139 | Feldcamp | Mar 2002 | S |
6367077 | Brodersen et al. | Apr 2002 | B1 |
6393605 | Loomans | May 2002 | B1 |
6405220 | Brodersen et al. | Jun 2002 | B1 |
6434550 | Warner et al. | Aug 2002 | B1 |
6446089 | Brodersen et al. | Sep 2002 | B1 |
6535909 | Rust | Mar 2003 | B1 |
6549908 | Loomans | Apr 2003 | B1 |
6553563 | Ambrose et al. | Apr 2003 | B2 |
6560461 | Fomukong et al. | May 2003 | B1 |
6574635 | Stauber et al. | Jun 2003 | B2 |
6577726 | Huang et al. | Jun 2003 | B1 |
6601087 | Zhu et al. | Jul 2003 | B1 |
6604117 | Lim et al. | Aug 2003 | B2 |
6604128 | Diec | Aug 2003 | B2 |
6609150 | Lee et al. | Aug 2003 | B2 |
6621834 | Scherpbier et al. | Sep 2003 | B1 |
6654032 | Zhu et al. | Nov 2003 | B1 |
6665648 | Brodersen et al. | Dec 2003 | B2 |
6665655 | Warner et al. | Dec 2003 | B1 |
6684438 | Brodersen et al. | Feb 2004 | B2 |
6711565 | Subramaniam et al. | Mar 2004 | B1 |
6724399 | Katchour et al. | Apr 2004 | B1 |
6728702 | Subramaniam et al. | Apr 2004 | B1 |
6728960 | Loomans | Apr 2004 | B1 |
6732095 | Warshavsky et al. | May 2004 | B1 |
6732100 | Brodersen et al. | May 2004 | B1 |
6732111 | Brodersen et al. | May 2004 | B2 |
6754681 | Brodersen et al. | Jun 2004 | B2 |
6763351 | Subramaniam et al. | Jul 2004 | B1 |
6763501 | Zhu et al. | Jul 2004 | B1 |
6768904 | Kim | Jul 2004 | B2 |
6782383 | Subramaniam et al. | Aug 2004 | B2 |
6804330 | Jones et al. | Oct 2004 | B1 |
6826565 | Ritchie et al. | Nov 2004 | B2 |
6826582 | Chatterjee et al. | Nov 2004 | B1 |
6826745 | Coker et al. | Nov 2004 | B2 |
6829655 | Huang et al. | Dec 2004 | B1 |
6842748 | Warner et al. | Jan 2005 | B1 |
6850895 | Brodersen et al. | Feb 2005 | B2 |
6850949 | Warner et al. | Feb 2005 | B2 |
7289976 | Kihneman et al. | Oct 2007 | B2 |
7340411 | Cook | Mar 2008 | B2 |
7620655 | Larsson et al. | Nov 2009 | B2 |
9288184 | Kvamme | Mar 2016 | B1 |
9946895 | Kruse et al. | Apr 2018 | B1 |
10079842 | Brandwine et al. | Sep 2018 | B1 |
20010044791 | Richter et al. | Nov 2001 | A1 |
20020022986 | Coker et al. | Feb 2002 | A1 |
20020029161 | Brodersen et al. | Mar 2002 | A1 |
20020029376 | Ambrose et al. | Mar 2002 | A1 |
20020035577 | Brodersen et al. | Mar 2002 | A1 |
20020042264 | Kim | Apr 2002 | A1 |
20020042843 | Diec | Apr 2002 | A1 |
20020072951 | Lee et al. | Jun 2002 | A1 |
20020082892 | Raffel et al. | Jun 2002 | A1 |
20020129352 | Brodersen et al. | Sep 2002 | A1 |
20020140731 | Subramaniam et al. | Oct 2002 | A1 |
20020143997 | Huang et al. | Oct 2002 | A1 |
20020152102 | Brodersen et al. | Oct 2002 | A1 |
20020161734 | Stauber et al. | Oct 2002 | A1 |
20020162090 | Parnell et al. | Oct 2002 | A1 |
20020165742 | Robins | Nov 2002 | A1 |
20030004971 | Gong et al. | Jan 2003 | A1 |
20030018705 | Chen et al. | Jan 2003 | A1 |
20030018830 | Chen et al. | Jan 2003 | A1 |
20030066031 | Laane | Apr 2003 | A1 |
20030066032 | Ramachadran et al. | Apr 2003 | A1 |
20030069936 | Warner et al. | Apr 2003 | A1 |
20030070000 | Coker et al. | Apr 2003 | A1 |
20030070004 | Mukundan et al. | Apr 2003 | A1 |
20030070005 | Mukundan et al. | Apr 2003 | A1 |
20030074418 | Coker | Apr 2003 | A1 |
20030088545 | Subramaniam et al. | May 2003 | A1 |
20030120675 | Stauber et al. | Jun 2003 | A1 |
20030151633 | George et al. | Aug 2003 | A1 |
20030159136 | Huang et al. | Aug 2003 | A1 |
20030187921 | Diec | Oct 2003 | A1 |
20030189600 | Gune et al. | Oct 2003 | A1 |
20030191743 | Brodersen et al. | Oct 2003 | A1 |
20030204427 | Gune et al. | Oct 2003 | A1 |
20030206192 | Chen et al. | Nov 2003 | A1 |
20030225730 | Warner et al. | Dec 2003 | A1 |
20040001092 | Rothwein et al. | Jan 2004 | A1 |
20040010489 | Rio | Jan 2004 | A1 |
20040015981 | Coker et al. | Jan 2004 | A1 |
20040027388 | Berg et al. | Feb 2004 | A1 |
20040128001 | Levin et al. | Jul 2004 | A1 |
20040186860 | Lee et al. | Sep 2004 | A1 |
20040193510 | Catahan, Jr. et al. | Sep 2004 | A1 |
20040199489 | Barnes-Leon et al. | Oct 2004 | A1 |
20040199536 | Barnes-Leon et al. | Oct 2004 | A1 |
20040199543 | Braud et al. | Oct 2004 | A1 |
20040249854 | Barnes-Leon et al. | Dec 2004 | A1 |
20040260534 | Pak et al. | Dec 2004 | A1 |
20040260659 | Chan et al. | Dec 2004 | A1 |
20040268299 | Lei et al. | Dec 2004 | A1 |
20050050555 | Exley et al. | Mar 2005 | A1 |
20050091098 | Brodersen et al. | Apr 2005 | A1 |
20080118150 | Balakrishnan et al. | May 2008 | A1 |
20090177744 | Marlow et al. | Jul 2009 | A1 |
20090204599 | Morris | Aug 2009 | A1 |
20110277037 | Burke et al. | Nov 2011 | A1 |
20120066769 | Latchem et al. | Mar 2012 | A1 |
20120108237 | Schatzmayr | May 2012 | A1 |
20120259894 | Varley et al. | Oct 2012 | A1 |
20130091350 | Gluck | Apr 2013 | A1 |
20140108262 | Plateaux | Apr 2014 | A1 |
20160019402 | Khandelwal | Jan 2016 | A1 |
20160085982 | Guirguis et al. | Mar 2016 | A1 |
20160119289 | Jain | Apr 2016 | A1 |
20160127289 | Papa et al. | May 2016 | A1 |
20160164924 | Rosenberg | Jun 2016 | A1 |
20160191341 | Sivasankaran | Jun 2016 | A1 |
20170116343 | Wu | Apr 2017 | A1 |
20170116428 | Wu et al. | Apr 2017 | A1 |
20170155655 | Spaulding | Jun 2017 | A1 |
20170270317 | Spaulding | Sep 2017 | A1 |
20180082296 | Brashers | Mar 2018 | A1 |
20180241569 | Harmon | Aug 2018 | A1 |
20180276414 | Beckman | Sep 2018 | A1 |
20180276553 | Redkar | Sep 2018 | A1 |
20180300496 | Shriver | Oct 2018 | A1 |
20180314981 | Chen | Nov 2018 | A1 |
20180349631 | Illendula et al. | Dec 2018 | A1 |
Entry |
---|
Notice of Allowance for U.S. Appl. No. 15/600,521 dated Jun. 10, 2019, 9 pages. |
Number | Date | Country | |
---|---|---|---|
20190354719 A1 | Nov 2019 | US |
Number | Date | Country | |
---|---|---|---|
62501003 | May 2017 | US |
Number | Date | Country | |
---|---|---|---|
Parent | 15600521 | May 2017 | US |
Child | 16530937 | US |