U.S. Pat. No. 8,224,860 granted Jul. 17, 2012 for a Database Management System and assigned to the same assignee as this invention is incorporated in its entirety herein by reference.
Field of the Invention
This invention generally relates to database management systems and more specifically to efficient management of multi-user, on-demand, distributed relational databases at a plurality of database processing resources, each of which may contain a plurality of databases.
Description of Related Art
Over the last few decades interest in databases has been increasing. Databases have been growing in size. A variety of database management systems have been developed to manage such databases. As the size of a database has increased, there has been and continues to be a requirement for providing resources of increased capability to operate such database management systems.
The requirement for increased resources previously has been met by adding or substituting storage resources and by the addition of or the replacement of existing processor resources with new storage and/or processor resources with greater capabilities. Consequently over time the total cost of ownership (“TCO”) that includes hardware, facility and power costs has been increasing and has been threatening to impact the benefit of the database versus the TCO of that database.
The above-identified U.S. Pat. No. 8,224,860 provides an alternative database management system that limits the rate of increase of the total cost of ownership. This system operates as a distributed database processing system. Users connect to the system through transactional nodes (also called “transaction engines”). Each of one or more storage managers (or “archival nodes”) stores all the data and metadata for the entire database. Increases in the database size are compensated by increasing the storage capacity of such storage managers without an upgrade of the hardware that implements the storage manager. However, a transaction engine at any given time must store and process only that data and metadata as required for responding to a query. Operations are performed asynchronously by means of messages transmitted and received between the various transaction engines and storage managers. Transaction engines do not require large memories and the processing of information is simplified, so the resources of a transaction engine are not subject to any significant change as a database grows over time. Consequently, the TCO of such a database management system can be relatively insensitive to changes in database size. Historically, this database management system has been employed to implement management and control over a single, large database with multiple locations, or nodes, from which multiple users access the database.
More recently “cloud computing” has been applied in environments where a provider enables a number of different users to access to a number of different “small” databases. In addition, new server configurations now are available that have somewhat limited resources, but that operate with significantly reduced power, space and related costs. A typical server includes multiple data processors that operate with resources that are limited in comparison to more sophisticated data processing systems. Each server data processor can manipulate multiple databases. In these systems the multiple data server data processors operate collectively. Moreover, each database must be available or “on-line” at all times even during periods during which the database operates with little or no activity. The operational state of such server data processors and databases can be monitored and a database can be made inactive to free up resources. However, when a database is made inactive in such an environment, it is “off-line” and a user must wait for the database to be restored before operations can begin. This introduces a delay which, in many situations and environments, cannot be tolerated. Also, at times operations of a given database in a specific server data processor may tax the available resources to the detriment of processing other databases as, for example, when a user submits a request that initiates a series of rapid transactions. This can also introduce an unacceptable delay.
What is needed is a database management system that is operable in a cloud computing environment, that can disable an inactive database to optimize the operation of a server and can compensate for an allocation of significant resources to one database on the server to the detriment of other databases, all transparently to the user and automatically without direct intervention by administrative personnel.
Therefore it is an object of this invention to provide a database management system that efficiently controls a network with a plurality of servers each comprising a plurality of independent data processors.
Another object of this invention is to provide a database management system that efficiently controls a network with a plurality of servers each comprising a plurality of independent data processors with multiple databases and that can selectively disable an “inactive” database.
Yet another object of this invention is to provide a database management system that efficiently controls a network with a plurality of servers each comprising a plurality of data processors and multiple databases, that selectively disables an “inactive” database and that facilitates reconnection of the inactive database in the network.
Still yet another object of this invention is to provide a database management system that efficiently controls a network with a plurality of servers each comprising a plurality of data processors and multiple databases that can transfer a database from a server data processor to another data processing system with increased resources for processing and thereafter transfer the database back to one of the server data processors.
Yet still another object of this invention is to provide methods for disabling inactive databases and transferring databases that require increase resources independently of and transparently to both a user and network administrators.
In accordance with one aspect of this invention, a database management system includes a server with a plurality of server data processors. Each server data processor assigns resources for processing each of a plurality of databases and each server data processor includes a memory and a processor and means for recording operational information about that server data processor. Each database therein includes a criterion that indicates a lack of activity for that database to enable the removal of an inactive database transparently to and independently of a user for that database by an iterative method of this invention. During each iteration there is an analysis of the criterion with respect each database in the server data processor for determining whether a threshold has been reached that defines an inactive state for that database. When this condition is detected, the database is deactivated thereby to release resources assigned to that database for use by other databases resident in the server data processor.
In accordance with another aspect of this invention, a database management system includes a server with a plurality of server data processors having a given set of resources for processing a database. Each server data processor assigns resources for processing each of a plurality of databases and includes a memory and a processor and means for recording operational information about server data processor and each database therein including a criterion that indicates that resources required for processing one of the databases is excessive. During a method of this invention such a database is transferred to another data processor with increased resources transparently and independently of a user for that database. The method includes an identification of the database and the server data processor from which the database is to be transferred. Information about the database is transferred to the other data processor. Then the database in the server data processor is disabled thereby to release resources assigned to the transferred database for use by other databases resident in the server data processor.
The appended claims particularly point out and distinctly claim the subject matter of this invention. The various objects, advantages and novel features of this invention will be more fully apparent from a reading of the following detailed description in conjunction with the accompanying drawings in which like reference numerals refer to like parts, and in which:
In
The network 10 additionally includes a server 20 comprising a plurality of server data processors 21, such as the three depicted server data processors 21A, 21B and 21C. Any given server could include any number of server data processors. Such servers are known in the art. By way of example, server data processor 21A includes as major components a CPU 22, a memory 23, a storage component 24 and an interface 25.
Each of the interfaces 15 and 25 provides signal and data paths for interconnecting the various components of their respective data processors. Memory 23 typically will have a multiple gigabyte capacity and each unit of storage will have a storage capacity of hundreds of gigabytes or more. A network interface 26 provides signal and data paths between each of the external data processing systems 11A and the server 20, between the external data processing systems and users, and between the server 20 and users.
The components of the network 10 are formed of conventionally available hardware and control systems. When implementing this invention, commercially available linking software can link the storage components 24 in an integrated disc pool that is available to all of the server data processors, such as server data processors 21A, 21B and 21C. The server 20 can also be characterized as an integrated multi-processing network whereby each server data processor can operate independently of the others.
In accordance with this invention, each of server data processors 21 and of the external data processing systems 11 operates in response to a database management system such as a NuoDB® database management system defined in the above-identified U.S. Pat. No. 8,224,860 and marketed by NuoDB, Inc. of Cambridge, Mass. Each server data processor 21 has the capability of processing multiple independent databases. Although the actual number of databases in any given server data processor 21 depends upon a number of factors, such as database size, each server data processor has the capability of storing hundreds of smaller databases.
A database management system incorporating this invention provides three important functions for facilitating the operation of the network 10 in
Still referring to
As shown in
Still referring to
A transfer DB method 53 enables a server data processor to identify any database that requires such a significant proportion of the available resources that may have a negative effect on the performance of other databases. The transfer DB method 53 monitors the database operations in a server data processor. Upon identifying a database that is using an unacceptable level of resources, the transfer DB method 53 transfers the identified database to one of the external data processing systems 11 in
With these features enabled, resources in each of the server data processors operate with efficiency. For example, there is no need to permanently maintain a database in an active state when it is not being used on a regular basis. If a database at a particular server data processor requires greater resources, that database can be transferred to an external database that may have greater resources. As a result the server data processor from which the database is transferred operates with greater efficiency with respect to other databases therein and the external data processor may process the transferred database more efficiently.
Once such a database becomes inactive due to the operation of the hibernate method 51, nothing further occurs until, as shown in
The architecture of Applicant's database management system enables the processing of a hibernation method 51 and a reactivation method 52 to occur in such a short time interval that the user is not aware of either method having been executed. Consequently, the steps of the hibernation method 51 and the reactivation 52 are transparent to the user.
Now referring to
If the threshold is exceeded, step 81 transfers to step 82 whereupon the management agent 34 identifies a server data processor with the database to be transferred, the database and a recipient for that database, typically one of the external data processing systems 11. However, as will be apparent, the designated recipient might be another of the server data processors 21. During step 83 the management agent unit in step 83 starts a new transaction engine at the recipient data processing system. Step 84 disables the transaction engine in the server data processor. If the transfer is being made to another server data processor, it may not be necessary to generate a new storage manager because the storage management for this database may already exist in the pool of the storage components 24. However, if the transfer is to be made to an external data processing system, it is necessary to update the storage manager associated with the database. In this situation, step 85 transfers control to step 86 whereupon the management agent starts a new storage manager in the recipient for that database being transferred and synchronizes the two the storage managers. Step 87 disables the storage manager in the server data processor from which the database is being transferred. As previously described, the transfer DB method 53 enables two favorable results. First resources in the server data processor required for the transferred database are freed thus improving the server data processor operations. If the transfer is made to an external data processing system 11, its greater resources may process the transferred database more efficiently while it requires increase resources. Both are positive results and the transfer occurs transparently to the user.
As now can be understood, the transfer DB method 53 is particularly appropriate for use when a server data processor database undergoes an interval of high resource requirement. For example, a theatre ticket sales database application may involve intervals of high activity for a short interval after an announced date of availability. The transfer DB method 53 allows that database to be transferred to an external data processor with greater resources for handling the burst of activity thereby eliminating any impact on the other databases in the server data processor. The operation of this method is transparent to the user and occurs without intervention by a network administrator.
Most databases alternate between intervals of high and low demands for resources. As represented by step 90 in
If the connection broker determines that an existing storage manager is available to the server data processor as in the previously described memory pool, step 95 terminates the operation. Otherwise step 95 transfers control to step 96 whereupon the connection broker produces a copy of the storage manager for the database in the identified server data processor and initiates a transfer to that new storage manager from an archive of the database. After the information has been synchronized, step 97 disables the storage manager in the external data processing system and thereby eliminates and removes the database from that external data processing system. That is, after the return DB method 54 has been completed, the originating external data processing system no longer contains a transaction engine or storage manager and the identified server data processor has a storage manager and transaction engine for the database.
As will now be understood, the existence of the four methods described with respect to
This invention has been disclosed in terms of certain embodiments. It will be apparent that many modifications can be made to the disclosed embodiment of this invention. Therefore, it is the intent of the appended claims to cover all such variations and modifications as come within the true spirit and scope of this invention.
This application claims priority from U.S. Provisional Patent Application Ser. No. 61/809,701 filed Apr. 8, 2013 for a Database Management System which is incorporated by referenced in its entirety herein.
Number | Name | Date | Kind |
---|---|---|---|
4853843 | Ecklund | Aug 1989 | A |
5446887 | Berkowitz | Aug 1995 | A |
5524240 | Barbara et al. | Jun 1996 | A |
5555404 | Torbjornsen et al. | Sep 1996 | A |
5568638 | Hayashi et al. | Oct 1996 | A |
5701467 | Freeston | Nov 1997 | A |
5764877 | Lomet et al. | Jun 1998 | A |
5960194 | Choy et al. | Sep 1999 | A |
6216151 | Antoun | Apr 2001 | B1 |
6226650 | Mahajan et al. | May 2001 | B1 |
6275863 | Leff et al. | Aug 2001 | B1 |
6334125 | Johnson et al. | Nov 2001 | B1 |
6401096 | Zellweger | Jun 2002 | B1 |
6424967 | Johnson et al. | Jul 2002 | B1 |
6480857 | Chandler | Nov 2002 | B1 |
6499036 | Gurevich | Dec 2002 | B1 |
6523036 | Hickman et al. | Feb 2003 | B1 |
6748394 | Shah et al. | Jun 2004 | B2 |
6792432 | Kodavalla et al. | Sep 2004 | B1 |
6862589 | Grant | Mar 2005 | B2 |
7026043 | Bleizeffer et al. | Apr 2006 | B2 |
7080083 | Kim et al. | Jul 2006 | B2 |
7096216 | Anonsen | Aug 2006 | B2 |
7219102 | Zhou et al. | May 2007 | B2 |
7233960 | Boris et al. | Jun 2007 | B1 |
7293039 | Deshmukh et al. | Nov 2007 | B1 |
7353227 | Wu | Apr 2008 | B2 |
7395352 | Lam et al. | Jul 2008 | B1 |
7401094 | Kesler | Jul 2008 | B1 |
7403948 | Ghoneimy et al. | Jul 2008 | B2 |
7562102 | Sumner et al. | Jul 2009 | B1 |
7853624 | Friedlander et al. | Dec 2010 | B2 |
7890508 | Gerber et al. | Feb 2011 | B2 |
8108343 | Wang et al. | Jan 2012 | B2 |
8224860 | Starkey | Jul 2012 | B2 |
8266122 | Newcombe et al. | Sep 2012 | B1 |
8504523 | Starkey | Aug 2013 | B2 |
8756237 | Stillerman et al. | Jun 2014 | B2 |
9501363 | Ottavio | Nov 2016 | B1 |
9734021 | Sanocki et al. | Aug 2017 | B1 |
20020112054 | Hatanaka | Aug 2002 | A1 |
20020152261 | Arkin et al. | Oct 2002 | A1 |
20020152262 | Arkin et al. | Oct 2002 | A1 |
20020178162 | Ulrich et al. | Nov 2002 | A1 |
20030051021 | Hirschfeld et al. | Mar 2003 | A1 |
20030149709 | Banks | Aug 2003 | A1 |
20030204486 | Berks et al. | Oct 2003 | A1 |
20030220935 | Vivian et al. | Nov 2003 | A1 |
20040153459 | Whitten | Aug 2004 | A1 |
20040263644 | Ebi | Dec 2004 | A1 |
20050013208 | Hirabayashi et al. | Jan 2005 | A1 |
20050086384 | Ernst | Apr 2005 | A1 |
20050198062 | Shapiro | Sep 2005 | A1 |
20050216502 | Kaura et al. | Sep 2005 | A1 |
20060010130 | Leff et al. | Jan 2006 | A1 |
20070067349 | Jhaveri et al. | Mar 2007 | A1 |
20080086470 | Graefe | Apr 2008 | A1 |
20080228795 | Lomet | Sep 2008 | A1 |
20080320038 | Liege | Dec 2008 | A1 |
20090113431 | Whyte | Apr 2009 | A1 |
20100094802 | Luotojarvi et al. | Apr 2010 | A1 |
20100153349 | Schroth | Jun 2010 | A1 |
20100191884 | Holenstein et al. | Jul 2010 | A1 |
20100235606 | Oreland et al. | Sep 2010 | A1 |
20100297565 | Waters et al. | Nov 2010 | A1 |
20110087874 | Timashev et al. | Apr 2011 | A1 |
20110231447 | Starkey | Sep 2011 | A1 |
20120136904 | Venkata Naga Ravi | May 2012 | A1 |
20120254175 | Horowitz et al. | Oct 2012 | A1 |
20130060922 | Koponen et al. | Mar 2013 | A1 |
20130110766 | Promhouse et al. | May 2013 | A1 |
20130110774 | Shah et al. | May 2013 | A1 |
20130110781 | Golab et al. | May 2013 | A1 |
20130159265 | Peh et al. | Jun 2013 | A1 |
20130159366 | Lyle et al. | Jun 2013 | A1 |
20130232378 | Resch et al. | Sep 2013 | A1 |
20130262403 | Milousheff et al. | Oct 2013 | A1 |
20130311426 | Erdogan et al. | Nov 2013 | A1 |
20140108414 | Stillerman et al. | Apr 2014 | A1 |
20140279881 | Tan et al. | Sep 2014 | A1 |
20140297676 | Bhatia et al. | Oct 2014 | A1 |
20150019739 | Attaluri et al. | Jan 2015 | A1 |
20150032695 | Tran et al. | Jan 2015 | A1 |
20150066858 | Sabdar et al. | Mar 2015 | A1 |
20150370505 | Shuma et al. | Dec 2015 | A1 |
20160134490 | Balasubramanyan et al. | May 2016 | A1 |
20170039099 | Ottavio | Feb 2017 | A1 |
Number | Date | Country |
---|---|---|
002931 | Oct 2001 | EA |
1403782 | Mar 2004 | EP |
2003-256256 | Sep 2003 | JP |
2006-048507 | Feb 2006 | JP |
2007-058275 | Mar 2007 | JP |
2315349 | Jan 2008 | RU |
2008106904 | Aug 2009 | RU |
Entry |
---|
Veerman, Database Load Balancing, MySQL 5.5 vs PostgreSQL 9.1, Apr. 2, 2012, pp. i-51. |
Amazon CloudWatch Developer Guide API, Create Alarms That or Terminate an Instance, Jan. 2013, pp. 1-11. |
Amazon RDS FAQs, Oct. 4, 2012, 39 pages. |
Garding, Alerting on Database Mirroring Events, Apr. 7, 2006, 24 pages. |
Iqbal, Performance TradeoH's in Static and Dynamic Load Balancing Strategies, 1986, pp. 1-23. |
Roy, Efficient Autoscaling in the Cloud using Predictive Models forWorkload Forecasting, 2011, pp. 500-507. |
Searchcloudapplications.techtarget.com, Autoscaling Definition, Aug. 2012, 1 page. |
Hull, Autoscaling MYSQL on Amazon EC2, Apr. 9, 2012, 7 pages. |
Oracle Database Concepts 10g Release 2 (10.2) Oct. 2005, 14 pages. |
International Preliminary Report on Patentability received for PCT/US2014/033270, dated Oct. 13, 2015. 4 pages. |
International Search Report for PCT/US2014/033270(2 sheets) and Written Opinion of the International Searching Authority (3 sheets). |
Final Office Action dated Sep. 9, 2016 from U.S. Appl. No. 14/215,461, 26 pp. |
International Search Report and Written Opinion dated Jul. 15, 2016 from PCT/US2016/27658, 37 pp. |
International Search Report and Written Opinion dated Sep. 8, 2016 from PCT/US16/37977, 11 pp. |
International Search Report and Written Opinion dated Sep. 9, 2016 from PCT/US16/34646, 12 pp. |
Non-Final Office Action dated Sep. 23, 2016 from U.S. Appl. No. 14/616,713, 8 pp. |
Notice of Allowance dated Jul. 27, 2016 from U.S. Appl. No. 14/215,372, 12 pp. |
U.S. Appl. No. 14/215,372, filed Mar. 17, 2014, Ottavio. |
U.S. Appl. No. 14/215,401, filed Mar. 17, 2014, Palmer. |
U.S. Appl. No. 14/215,461, filed Mar. 17, 2014, Palmer. |
U.S. Appl. No. 14/616,713, filed Feb. 8, 2015, Levin. |
U.S. Appl. No. 14/688,396, filed Apr. 16, 2015, Shaull. |
U.S. Appl. No. 14/725,916, filed May 29, 2015, Rice. |
U.S. Appl. No. 14/726,200, filed May 29, 2015, Palmer. |
U.S. Appl. No. 14/744,546, filed Jun. 19, 2015, Massari. |
“Album Closing Policy,” Background, retrieved from the Internet at URL:http://tools/wiki/display/ENG/Album+Closing+Policy (Jan. 29, 2015), 4 pp. |
Bergsten et al., “Overview of Parallel Architectures for Databases,” The Computer Journal vol. 36, No. 8, pp. 734-740 (1993). |
Dan et al., “Performance Comparisons of Buffer Coherency Policies,” Proceedings of the International Conference on Distributed Computer Systems, IEEE Comp. Soc. Press vol. 11, pp. 208-217 (1991). |
“Distributed Coordination in NuoDB,” YouTube, retrieved from the Internet at URL:https://www.youtube.com/watch?feature=player_embedded&v=URoeHvflVKg on Feb. 4, 2015, 2 pp. |
Durable Distributed Cache Architecture, retrieved from the Internet at URL: http://www.nuodb.com/explore/newsql-cloud-database-ddc-architecture on Feb. 4, 2015, 3 pp. |
“Glossary—NuoDB 2.1 Documentation / NuoDB,” retrieved from the Internet at URL: http://doc.nuodb.com/display/doc/Glossary on Feb. 4, 2015, 1 pp. |
“How It Works,” retrieved from the Internet at URL: http://www.nuodb.com/explore/newsql-cloud-database-how-it-works?mkt_tok=3RkMMJW on Feb. 4, 2015, 4 pp. |
“How to Eliminate MySQL Performance Issues,” NuoDB Technical Whitepaper, Sep. 10, 2014, Version 1, 11 pp. |
“Hybrid Transaction and Analytical Processing with NuoDB,” NuoDB Technical Whitepaper, Nov. 5, 2014, Version 1, 13 pp. |
International Search Report dated Sep. 26, 2012 from PCT/US2011/029056, 4 pp. |
Leverenz et al., “Oracle8i Concepts, Partitioned Tables and Indexes,” Chapter 11, pp. 11-2-11/66 (1999). |
“No Knobs Administration,” retrieved from the Internet at URL: http://www.nuodb.com/explore/newsql-cloud-database-product/auto-administration on Feb. 4, 2015, 4 pp. |
Non-Final Office Action dated Jan. 21, 2016 from U.S. Appl. No. 14/215,401, 19 pp. |
Non-Final Office Action dated Feb. 1, 2016 from U.S. Appl. No. 14/251,461, 19 pp. |
Non-Final Office Action dated Feb. 6, 2014 from U.S. Appl. No. 13/933,483, 14 pp. |
Non-Final Office Action dated Oct. 10, 2012 from U.S. Appl. No. 13/525,953, 8 pp. |
Notice of Allowance dated Feb. 29, 2012 from U.S. Appl. No. 13/051,750, 8 pp. |
Notice of Allowance dated Apr. 1, 2013 from U.S. Appl. No. 13/525,953, 10 pp. |
Notice of Allowance dated May 14, 2012 from U.S. Appl. No. 13/051,750, 8 pp. |
“NuoDB at a Glance,” retrieved from the Internet at URL: http://doc.nuodb.com/display/doc/NuoDB+at+a+Glance on Feb. 4, 2015, 1 pp. |
Rahimi, S. K. et al., “Distributed Database Management Systems: A Practical Approach,” IEEE Computer Society, John Wiley & Sons, Inc. Publications (2010), 765 pp. |
Shaull, R. et al., “A Modular and Efficient Past State System for Berkeley DB,” Proceedings of USENIX ATC '14:2014 USENIX Annual Technical Conference, 13 pp. (Jun. 19-20, 2014). |
Shaull, R. et al., “Skippy: a New Snapshot Indexing Method for Time Travel in the Storage Manager,” SIGMOD'08, Jun. 9-12, 2008, 12 pp. |
Shaull, R., “Retro: A Methodology for Retrospection Everywhere,” A Dissertation Presented to the Faculty of the Graduate School of Arts and Sciences of Brandeis University, Waltham, Massachusetts, Aug. 2013, 174 pp. |
“SnapShot Albums,” Transaction Ordering, retrieved from the Internet at URL:http://tools/wiki/display/ENG/Snapshot+Albums (Aug. 12, 2014), 4 pp. |
“Table Partitioning and Storage Groups (TPSG),” Architect's Overview, NuoDB Technical Design Document, Version 2.0 (2014), 12 pp. |
“The Architecture & Motivation for NuoDB,” NuoDB Technical Whitepaper, Oct. 5, 2014, Version 1, 27 pp. |
“Welcome to NuoDB Swifts Release 2.1 GA,” retrieved from the Internet at URL: http:.//dev.nuodb.com/techblog/welcome-nuodb-swifts-release-21-ga on Feb. 4, 2015, 7 pp. |
“What Is a Distributed Database? and Why Do You Need One,” NuoDB Technical Whitepaper, Jan. 23, 2014, Version 1, 9 pp. |
Yousif, M. “Shared-Storage Clusters,” Cluster Computing, Baltzer Science Publishers, Bussum, NL, vol. 2, No. 4, pp. 249-257 (1999). |
U.S. Appl. No. 15/296,439, filed Oct. 18, 2016, Ottavio. |
Non-Final Office Action dated Feb. 1, 2016 from U.S. Appl. No. 14/215,461, 19 pp. |
International Search Report and Written Opinion dated Oct. 28, 2016 from PCT/US16/34651, 16 pp. |
Decision to Grant dated Nov. 14, 2016 from Belarus Patent Application No. a20121441 with English Translation, 15 pp. |
Final Office Action dated Nov. 3, 2016 from U.S. Appl. No. 14/215,401, 36 pp. |
First Examination Report issued by the Canadian Intellectual Property Office for Application No. 2,793,429, dated Feb. 14, 2017, 3 pages. |
Advisory Action issued by the United States Patent and Trademark Office for U.S. Appl. No. 14/215,461, dated Jan. 10, 2017, 9 pages. |
Non-Final Office Action dated Jun. 2, 2017 from U.S. Appl. No. 14/744,546, 25 pp. |
Non-Final Office Action dated Jun. 1, 2017 from U.S. Appl. No. 14/215,461, 21 pp. |
Non-Final Office Action dated May 31, 2017 from U.S. Appl. No. 14/215,401, 27 pp. |
Connectivity Testing with Ping, Telnet, Trace Route and NSlookup (hereafter help.webcontrolcenter), Article ID:1757, Created: Jun. 17, 2013 at 10:45 a.m., https://help.webcontrolcenter.com/kb/a1757/connectivity-testing-with-ping-telnet-trace-route-and-nslookup.aspx, 6 pages. |
Final Office Action dated Nov. 24, 2017 from U.S. Appl. No. 14/215,401, 33 pages. |
Non-Final Office Action dated Sep. 19, 2017 from U.S. Appl. No. 14/726,200, 37 pages. |
Non-Final Office Action dated Sep. 21, 2017 from U.S. Appl. No. 14/688,396, 31 pages. |
Number | Date | Country | |
---|---|---|---|
20140304306 A1 | Oct 2014 | US |
Number | Date | Country | |
---|---|---|---|
61809701 | Apr 2013 | US |