[Not Applicable]
[Not Applicable]
Smartphones are devices running feature rich operating systems such as Symbian, PalmOS, Microsoft WinCE, BREW (Binary Runtime Environment for Wireless) and Java MIDP compliant devices. Due to the complex nature and multitude of new features, these Smartphone devices are difficult to configure; compounded with limited keyboards, entering information such as personal details and configuration settings is not only difficult but also highly prone to human errors. A combination of complex features and associated configuration requirements requires great improvement upon current customer support solutions for wireless network operators.
With the wide availability of downloadable services and applications available for Smartphone users and the increasing costs of customer care, ensuring efficient and less-cumbersome support when problems arise is an increasing necessity. In contrast to traditional customer service applications that are available in Contact Center's today, CSRs (Customer Service Representatives) must undertake the extensive and time-consuming task of asking customer's complex questions pertaining to their wireless devices for problem diagnosis. This requires CSRs to be experts on Smartphones and their applications, and also requires customers to spend increased time on the telephone to receive support for their applications. The result is increased support costs, increased call handling times, complex diagnostic processes and overall frustration.
The current method of call routing is based on a simple queue where the next available CSR gets the next call. In this method there is no specialization since each CSR can get a call related to any phone or problem. Each CSR is a generalist and tries to solve all sorts of problems.
Gathering and obtaining Smartphone information required for diagnostics is manual and therefore complex, time consuming and prone to human errors. This problematic approach is an ineffective method of just-in-time customer support and does not guarantee effective problem resolution. This current method of call routing leave both the subscribers and customer support staff frustrated. In addition, obtaining diagnostic information requires a specialized support staff and Contact Centers must therefore hire and train specialized staff For specific tasks. For the Service Provider this means increased hiring and operational costs.
The customer Support process is increasing in complexity. The level of expertise required by the CSR to understand numerous Smartphone devices and to search for up-to-date configuration data leads to increased costs in training, call-durations, and the overall operational costs.
With the emergence of Smartphones and wireless PDAs and their ability to download and install applications, the wireless industry is poised to see explosive growth in application usage by subscribers. Mobile operator customer care centers are focused on solutions for closed, voice-centric mobile phones. This infrastructure is not suited to efficiently solve the intelligent mobile data device and application problems described above. The proliferation of next generation “Smartphone” devices and the level of issues and problem solving needed has made existing customer care applications obsolete or unsuitable to meet these emerging business needs.
In general, incoming calls from callers to a call center supported by an operator network goes into a queue, called the incoming call queue. Irrespective of phone and subscriber profile each person who responds to a call is a generalist. Often, nothing is known about the subscriber, and even less about the subscriber's device, when a subscriber makes a call for customer service into an operator's call center. Several minutes are initially taken up just to collect the most basic information about the subscriber and the subscriber's device.
Further limitations and disadvantages of conventional and traditional approaches will become apparent to one of skill in the art, through comparison of such systems with some aspects of the present invention as set forth in the remainder of the present application with reference to the drawings.
A method and/or system for routing customer care calls such that the right customer service representative receives an incoming customer care call, substantially as shown in and/or described in connection with at least one of the figures, as set forth more completely in the claims.
These and other advantages, aspects and novel features of the present invention, as well as details of an illustrated embodiment thereof, will be more fully understood from the following description and drawings.
The numerous objects and advantages of the present invention may be better understood by those skilled in the art by reference to the accompanying figures in which:
Aspects of the present invention relate generally to the routing of calls to customer care, and, more specifically, to the use of an intelligent routing system for routing such customer care calls such that the right customer service representative receives an incoming customer care call. The following discussion makes reference to the term “electronic device” that is used herein to refer to mobile electronic devices such as, for example, a mobile handset, a cellular phone, a personal digital assistant (PDA), a pager, and a personal computer, to name just a few. Although the listed example electronic devices are mobile devices, application of the present invention is not limited in this manner, as representative embodiments of the present invention may be employed in a wide variety of electronic devices, both fixed and mobile. The following discussion makes reference to the term “customer care system” that is used herein to refer to customer facing systems such as, for example, those maintained by an wireless network operator, or an enterprise. The following discussion also makes reference to the term “network” that is used herein to refer to networks such as, for example, an operator network, an enterprise network, an Internet based network, a management network for a service, etc.
Electronic devices may be adapted to access servers to retrieve update information for updating memory in the electronic devices. An electronic device may be, for example, a mobile electronic device having firmware/software such as mobile cellular phone handsets, personal digital assistants (PDAs), pagers, MP-3 players, digital cameras, to name just a few. Update information may comprise information that modifies or changes firmware/software and/or software components installed in the electronic device. In a representative embodiment of the present invention, update information may comprise a set of executable instructions for converting a first version of code to an updated/second version of code. The update information may add new services to the electronic device, as desired by a service provider, device manufacturer, or an end-user, and/or may fix bugs (e.g., errors) in the operating code of the electronic device. In a representative embodiment of the present invention, update information may comprise an update package.
A customer care representative may help diagnose a problem with a device and update the configurations, settings, parameters, firmware, etc. in the device. The user experience in dealing with a customer care representative is improved by a system built in accordance with the present invention.
The operator network 105 is capable of routing incoming customer care calls to specific customer care representatives (CSRs) based on a subscriber profile and customer service representative (CSR) skill set. A device profile is retrieved from the mobile handset while the incoming customer care call is in a queue waiting to be connected to a CSR. The retrieved device profile is also used to determine an appropriate CSR.
In general, the operator network 105 implements a call routing system that relies on the fact that each CSR, if limited to a narrower scope of problems, can become an expert over time and will require less and less time to solve the same problem or trouble shoot a particular phone or particular OS based devices. Each CSR is assumed to employ one of the CSR units 123 available in the operator network 105 to conduct their work. Information on what skills a CSR possesses or what types of problems or what devices they are good at solving is maintained in the CSR skill set database 125. The CSR skill set database 125 is continuously updated in one embodiment.
When a user employs the mobile handset 131 to report a problem or seek help from a CSR, the incoming call is queued up by the operator network 105 into the incoming call queue 119. The incoming call is typically put on hold, or made to wait, in the incoming call queue 119 until a CSR is assigned to the incoming call. The call routing unit 121 determines the CSR to be assigned the incoming call from the mobile handset 131, while the incoming call is put on hold or made to wait in the incoming call queue 119. While the user waits to be connected to the CSR, such as a CSR currently using the CSR unit 123, in one embodiment, the call routing unit 121 solicits a device profile from the mobile handset 131. It process the user profile received to determine the appropriate CSR to forward the incoming customer service call from the mobile handset 131.
In another related embodiment, while the user waits to be connected to the CSR, such as a CSR currently using the CSR unit 123, the call routing unit 121 retrieves a device profile from the mobile handset 131 and checks the mobile care engine 113 to determine which CSR unit 123 to connect the incoming call to.
The analytics engine 115 is based on analytic rules that are automatically generated or enter manually. Similarly, the rules engine 117 is based on rules that are automatically generated or manually entered or both.
In general, the mobile care engine 113 is capable of processing the device profile retrieved from the mobile handset 131, and rules retrieved from the rules repository 111, to determine which of the currently available CSR's are considered to be experts capable of efficiently addressing the users anticipated problem. It then instructs the call routing unit 121 to forward the queued up call from the mobile handset 131 to the appropriate CSR (determined to be the expert) currently using the CSR unit 123. The CSR, currently working on the unit 123, is also provided with a list of known problems (or the most frequent ones encountered) with devices of the type (make, model, versions, OS, etc.) to which the mobile handset 131 belongs.
Thus, the CSR is empowered with the information needed to solve the known problems, employing known solutions, diagnosing problems by known symptoms, etc. The CSR views the device profile, known problem-solution pairs, etc. even before the user of the mobile handset 131 has spoken to the CSR to explain the problem encountered, or details of service interruptions experienced.
The present invention provides a customer care system and supports a method for call routing in the CSR call-centers (such as those located within typical wireless operator networks) that is based on a subscriber's problem to be solved, Smartphone usage, behavioral profiles and device profiles. This approach allows for an incoming call, which is typically queued at the incoming call queue 119, to be routed to a CSR unit 123, based on the best match between the CSR skill set, a phone type, a subscriber's area of problem and other related information. Such a best match is conducted by the mobile care engine 113, employing the rules engine 117 and/or the analytics engine 115.
In one embodiment, after obtaining device-specific profiles from subscriber devices, such as the mobile handset 131, the call routing unit 121 of the operator network 105 matches them with the CSR skill set available in a repository or database, such as the CSR skill set database 125, to determine at least one CSR unit 123 (or associated CSR) determined to be capable of addressing the subscriber's support needs. The CSR identified for the assignment is expected to be an expert on such mobile handsets 131, thus making it possible to provide customer service geared towards the highly specialized nature of these mobile handsets 131.
In general, in most wireless customer care scenarios, the same problem is solved over and over again by different CSR from ab initio. The present invention provides a mechanism where business logic is translated in to rules that can be reused, shared and modified on the fly, whereby tremendous efficiency is achieved. This way, once a problem has been solved for a particular mobile handset 131, such as a Smartphone (of a specific make, model and version), the next time another Smartphone subscriber calls with the same problem or issue, the CSR associated with the call does not have to start from scratch; instead the CSR leverages the known/existing solution previously encountered and saved in a database or repository (such as the rules repository 111). Now furthering this argument, the present invention incorporates a method of automating rule creation through analytics that automates the rule creation process, based on device profile data analysis, the trends in the data and Smartphone issues/problems. The automatic creation of rules speeds up the process and thus improves response time; thereby increasing customer satisfaction.
In one embodiment, a customized device emulator that emulates the mobile handset 131 is pre-spawned on a CSR desk (top based on the Smartphone profile retrieved from the mobile handset or from the rules repository 111, to further increase the effectiveness of customer care and to reduce the duration of customer service calls.
In one embodiment, the CSR skill set is measured and ranked based on the data gathered, or loaded from external system, over a period of time and analyzed at regular intervals. The CSR skill set is used to determine an appropriate CSR to handle an incoming customer service call from the mobile handset 131.
In one embodiment, a system based on the present invention conducts call routing based on subscriber profile, device profile, CSR skill set and wireless data device problems. It results in faster, more efficient and more accurate customer support for the rapid resolution of issues. Benefits of this method of routing customer service calls to CSRs include:
In one embodiment, the call routing unit 121 of the operator network 105 relies on matching phone type, problem type and the CSR skill set that may be retrieved from the CSR skill set database 125. The profile of the phone is extracted, either from the mobile handset 131 or from a database, such as the rules repository 111 or a different device capability database, and matched against the information retrieved from the CSR skill set database 125. The CSR skill sets that are provided by the CSR skill set database 125 can be defined in two different ways, manually or automatically:
1) Manually defining CSR skill sets
2) Intelligent system that learns over time
In one embodiment based on manually defining CSR skill sets, the operator network (or more specifically, the CSR skill set database 125) provides an interface through which the skill set can be added, when setting up CSR users for the system. At setup or at the creation of each CSR account, the CSR's skill set is manually entered into the CSR skill set database 125. For example, two new CSR accounts may be added; one CSR as an expert in the PalmOS and the other as an expert in SymbianOS. At the time of account creation for one PalmOS is chosen and for the other SymbianOS preferably from a drop down menu. When a subscriber calls into the support center, the subscriber's device is profiled, and based on the OS of the subscriber's mobile handset 131, the call is routed to the appropriate CSR.
In another embodiment, that is based on an intelligent CSR database system that learns over time, the CSR's prior performance is taken into consideration. The CSR's skill set is continuously (or periodically) assessed based on the type of problem the CSR is determined to be adept at solving, and the time it took to resolve those problems. If the CSR consistently performs better than the defined thresholds, then the CSR's skill set level is upgraded. In this approach, prior performance examination both long term and short term performance is taken into account.
In one embodiment, if a CSR is having a bad day and consistently performing under par, his skill set level is dropped. Different weights and time periods lengths is used and these are configurable parameters.
In one embodiment, an intelligent and automated process of populating the CSR skill set database 125 is employed, that relies on the data being gathered by the operator network 105 over a period of time. This accumulated historical data regarding problems and the solutions, provided by different CSRs, and the time it took to solve the problem, are used for decision making.
In one embodiment, every time a CSR provides a solution to a particular wireless data device and a particular bug, the data regarding the solution is captured by SmartNotes, a component that is part of the CSR skill set database 125. This historical data can also be imported from existing systems in an operator's network, a “Trouble Ticket Systems”, if they are being captured there.
In general, incoming calls from callers to a call center supported by an operator network 105 goes in to a queue, called the incoming call queue 119. Irrespective of phone and subscriber profile each person who responds to a call is now sent to a CSR who is either an expert in the device or has displayed sufficient expertise in solving problems related to similar devices. Thus, the time taken to ascertain and fix problems with the subscriber's mobile handsets 131 by CSRs is significantly reduced. If the operator network 105 provides subscriber profile (rate plan, etc.) it is possible to provide a higher priority to subscriber's of a specific rate plan or subscriber class (such as premier subscribers are corporate subscribers).
In one embodiment, based on the kind of mobile handset 131, an incoming call for customer care is forwarded to a CSR. For example, one of N CSRs determined to be experts on a particular problem is assigned to an incoming call for customer care, based on of mobile handset 131 and a device profile retrieved from the mobile handset 131.
In one embodiment, the rules engine 217 and the analytics engine 215 retrieve rules and raw data from the repository 225. Similarly, a CSR's problem solving records, performance information, a CSR expertise information, etc. are saved in the repository 225. The call routing system 221 routes incoming calls queued up in the incoming call queue 219 to an appropriate CSR unit 223 based on rules executed by the rules engine 217. The CSR unit 223 determines potential solutions based oil analytical rules executed by the analytical engine 215.
Then, at a next block 313, based on the device profile retrieved, the subscriber's subscriber class information retrieved, and other related information, the potential problems, such as known problems, are determined. Then, at a next block 315, potential solutions, that are either known solutions or solutions suggested by the rules engine, are retrieved.
Later, at a next block 317, the user's customer care call that is queued up is connected to a CSR determined to be an appropriate CSR to handle the incoming call. Such determination is done based on rules executed by the rules engine. The CSR reviews the potential problems, associated solutions and device profile information while interacting with the user.
Then, at a next block 319, the user determines an appropriate solution and solves the user's problem. In one embodiment, the solution is determined to be a change in configuration, such as a change in an SMTP server, a POP server setting or connectivity parameters. The CSR initiates a configuration change and verifies that the change did take place. In another embodiment, the solution to the problem is determined to be a firmware update and the CSR initiates a firmware update of the mobile handset being used by the user. In yet another embodiment, the CSR determines that the solution requires a combination of firmware update, a software update and a configuration change, and the CSR sets up these update activities for subsequent update of the mobile handset. In a different embodiment, the CSR initiates diagnostic data collection in the mobile handset for further analysis.
Finally, at an end block 321, the processing ends with a satisfied user and a mobile handset that functions better due to the solution of a problem or the fixing of a configuration setting, etc.
Then, at a next block 413, historical data is also gathered by SmartNotes database of the smart customer care system, based on point solutions provided by the CSRs. Then, at a next block 415, using the “Auto Rule Criteria”, the auto rule generator sifts through the different data stores that contains all the collect data, historical or otherwise. Then, at a next block 417, any patterns detected in the data are analyzed further. Once a criteria for the creation of a rule is met in a detected pattern, and enough patterns emerge in the historical data that satisfies the conditions set by the criteria, the auto rule generator creates a new rule.
Then, at a next block 419, the newly generated (auto generated) rule is then stored in the rules repository. These rules at first may then be only applied to a limited number of wireless data devices, and once proven to be robust, are put into production. Finally, at the end block 421, the processing stops.
The smart customer care system 507 employs rules that are executed by the rules engine 517 to determine which customer care representative should be handling an incoming customer care call from the mobile handset 531. The rules employ a device profile and a subscriber profile, as necessary, to determine to which CSR the customer care should be routed. It also employs a CSR skill set database to determine which CSR has the necessary expertise to handle the call. It attempts to find a best match and determines a target CSR for the incoming customer care call. If a best match cannot be found, or if multiple CSRs are determined to be capable of handling the call, it targets one of them for handling the incoming call. Such targeting being based on additional rules used to resolve targeting or on preset default behavior.
The analytics engine 515 employs additional rules to determine what is wrong with the mobile handset. It employs information retrieved from the mobile handset, such as the device profile, to determine problems with connectivity, configuration, application behavior, etc. It also flags additional information that is needed for problem resolution, and highlights them to the CSR so that the CSR might ask the user for such information or retrieve them from the device, or from a self-care portal to which the user of the mobile handset 531 may have used previously.
In one embodiment, the smart customer care system 507 is part of the operator network 541. In another embodiment, the smart customer care system 507 is part of a customer care center that is external to the operator network 541, such as one managed by an OEM.
While the present invention has been described with reference to certain embodiments, it will be understood by those skilled in the art that various changes may be made and equivalents may be substituted without departing from the scope of the present invention. In addition, many modifications may be made to adapt a particular situation or material to the teachings of the present invention without departing from its scope. Therefore, it is intended that the present invention not be limited to the particular embodiment disclosed, but that the present invention will include all embodiments falling within the scope of the appended claims.
The present application is a continuation of U.S. patent application Ser. No. 11/247,459, filed Oct. 11, 2005, makes reference to, claims benefit of, and claims priority to U.S. Provisional Patent Application Ser. No. 60/618,849, entitled “OPERATOR NETWORK THAT ROUTES CUSTOMER CARE CALLS BASED ON SUBSCRIBER/ DEVICE PROFILE AND CSR SKILL SET”, filed Oct. 13, 2004, the complete subject matter of each of which is hereby incorporated herein by reference, in its entirety. With respect to the present application, Applicant hereby rescinds any disclaimer of claim scope made in the parent application or any predecessor or related application. The Examiner is advised that any previous disclaimer of claim scope, if any, and the alleged prior art that it was made to allegedly avoid, may need to be revisited. Nor should a discalimer of claim scope, if any, in the present application be read back into any predecessor or related application. The present application makes reference to PCT Application with publication number WO/02/41147 A1, PCT number PCT/US01/44034, filed 19 Nov. 2001, which in turn is based on a provisional application 60/249,606 filed 17, Nov. 2000, each of which is hereby incorporated herein by reference in its entirety. The present application also hereby makes reference to provisional applications, Ser. Nos. 60/461,886, filed on Apr. 11, 2003, Ser. No. 60/525,794 filed on Dec. 1, 2003 and Ser. No. 60/534,426 filed on Jan. 7, 2004, each of which is hereby incorporated herein by reference, in its entirety.
Number | Name | Date | Kind |
---|---|---|---|
5261055 | Moran et al. | Nov 1993 | A |
5442771 | Filepp et al. | Aug 1995 | A |
5479637 | Lisimaque et al. | Dec 1995 | A |
5563931 | Bishop et al. | Oct 1996 | A |
5579522 | Christeson et al. | Nov 1996 | A |
5596738 | Pope | Jan 1997 | A |
5598534 | Haas | Jan 1997 | A |
5608910 | Shimakura | Mar 1997 | A |
5623604 | Russell et al. | Apr 1997 | A |
5666293 | Metz et al. | Sep 1997 | A |
5704031 | Mikami et al. | Dec 1997 | A |
5752039 | Tanimura | May 1998 | A |
5778440 | Yiu et al. | Jul 1998 | A |
5790974 | Tognazzini | Aug 1998 | A |
5826012 | Lettvin | Oct 1998 | A |
5878256 | Bealkowski et al. | Mar 1999 | A |
5944839 | Isenberg | Aug 1999 | A |
5960445 | Tamori et al. | Sep 1999 | A |
6009497 | Wells et al. | Dec 1999 | A |
6021428 | Miloslavsky et al. | Feb 2000 | A |
6038636 | Brown, III et al. | Mar 2000 | A |
6058435 | Sassin et al. | May 2000 | A |
6064814 | Capriles et al. | May 2000 | A |
6070142 | McDonough et al. | May 2000 | A |
6073206 | Piwonka et al. | Jun 2000 | A |
6073214 | Fawcett | Jun 2000 | A |
6081518 | Bowman-Amuah | Jun 2000 | A |
6088759 | Hasbun et al. | Jul 2000 | A |
6105063 | Hayes, Jr. | Aug 2000 | A |
6112024 | Almond et al. | Aug 2000 | A |
6112197 | Chatterjee et al. | Aug 2000 | A |
6115693 | McDonough et al. | Sep 2000 | A |
6126327 | Bi et al. | Oct 2000 | A |
6128695 | Estakhri et al. | Oct 2000 | A |
6134530 | Bunting et al. | Oct 2000 | A |
6157559 | Yoo | Dec 2000 | A |
6163274 | Lindgren | Dec 2000 | A |
6178452 | Miyamoyo | Jan 2001 | B1 |
6198946 | Shin et al. | Mar 2001 | B1 |
6233332 | Anderson et al. | May 2001 | B1 |
6266810 | Tanaka et al. | Jul 2001 | B1 |
6279153 | Bi et al. | Aug 2001 | B1 |
6311322 | Ikeda et al. | Oct 2001 | B1 |
6330715 | Razzaghe | Dec 2001 | B1 |
6333980 | Hollatz et al. | Dec 2001 | B1 |
6381454 | Tiedemann et al. | Apr 2002 | B1 |
6393018 | Miloslavsky | May 2002 | B2 |
6426955 | Gossett Dalton et al. | Jul 2002 | B1 |
6438585 | Mousseau et al. | Aug 2002 | B2 |
6449270 | Miloslavsky | Sep 2002 | B1 |
6470496 | Kato et al. | Oct 2002 | B1 |
6477531 | Sullivan et al. | Nov 2002 | B1 |
6530036 | Frey, Jr. | Mar 2003 | B1 |
6542504 | Mahler et al. | Apr 2003 | B1 |
6553113 | Dhir et al. | Apr 2003 | B1 |
6581105 | Miloslavsky et al. | Jun 2003 | B2 |
6603854 | Judkins et al. | Aug 2003 | B1 |
6606744 | Mikurak | Aug 2003 | B1 |
6615240 | Sullivan et al. | Sep 2003 | B1 |
6622017 | Hoffman | Sep 2003 | B1 |
6668049 | Koch et al. | Dec 2003 | B1 |
6687341 | Koch et al. | Feb 2004 | B1 |
6694314 | Sullivan et al. | Feb 2004 | B1 |
6704303 | Bowman-Amuah | Mar 2004 | B1 |
6704410 | McFarlane et al. | Mar 2004 | B1 |
6714642 | Dhir et al. | Mar 2004 | B2 |
6754181 | Elliot et al. | Jun 2004 | B1 |
6763104 | Judkins et al. | Jul 2004 | B1 |
6798876 | Bala | Sep 2004 | B1 |
6850614 | Collins | Feb 2005 | B1 |
6879685 | Peterson et al. | Apr 2005 | B1 |
6956846 | Lewis et al. | Oct 2005 | B2 |
6981020 | Miloslavsky et al. | Dec 2005 | B2 |
6993328 | Oommen | Jan 2006 | B1 |
6996603 | Srinivasan | Feb 2006 | B1 |
6999990 | Sullivan et al. | Feb 2006 | B1 |
7002919 | El-Sayed | Feb 2006 | B1 |
7027586 | Bushey et al. | Apr 2006 | B2 |
7047004 | Tolbert, II | May 2006 | B1 |
7050566 | Becerra et al. | May 2006 | B2 |
7062031 | Becerra et al. | Jun 2006 | B2 |
7076051 | Brown et al. | Jul 2006 | B2 |
7103172 | Brown et al. | Sep 2006 | B2 |
7110525 | Heller et al. | Sep 2006 | B1 |
7145898 | Elliot | Dec 2006 | B1 |
7146002 | Smith et al. | Dec 2006 | B1 |
7230951 | Mizell et al. | Jun 2007 | B2 |
7277529 | Wuthnow et al. | Oct 2007 | B1 |
7386846 | Rajaram | Jun 2008 | B2 |
20010029178 | Criss et al. | Oct 2001 | A1 |
20010047363 | Peng | Nov 2001 | A1 |
20010048728 | Peng | Dec 2001 | A1 |
20010053688 | Rignell et al. | Dec 2001 | A1 |
20020053044 | Gold et al. | May 2002 | A1 |
20020078209 | Peng | Jun 2002 | A1 |
20020116261 | Moskowitz et al. | Aug 2002 | A1 |
20020124209 | Faust et al. | Sep 2002 | A1 |
20020131404 | Mehta et al. | Sep 2002 | A1 |
20020152005 | Bagnordi | Oct 2002 | A1 |
20020156863 | Peng | Oct 2002 | A1 |
20020157090 | Anton, Jr. | Oct 2002 | A1 |
20030005362 | Miller et al. | Jan 2003 | A1 |
20030009753 | Brodersen et al. | Jan 2003 | A1 |
20030022663 | Rajaram et al. | Jan 2003 | A1 |
20030033599 | Rajaram et al. | Feb 2003 | A1 |
20030037075 | Hannigan et al. | Feb 2003 | A1 |
20030061384 | Nakatani | Mar 2003 | A1 |
20030084283 | Pixton | May 2003 | A1 |
20030110484 | Famolari | Jun 2003 | A1 |
20040031030 | Kidder et al. | Feb 2004 | A1 |
20040123153 | Wright et al. | Jun 2004 | A1 |
20050050538 | Kawamata et al. | Mar 2005 | A1 |
20050210458 | Moriyama et al. | Sep 2005 | A1 |
Number | Date | Country |
---|---|---|
2339923 | Mar 2000 | CA |
1052571 | Nov 2000 | EP |
1282989 | Feb 2003 | EP |
8202626 | Aug 1996 | JP |
20020034228 | May 2000 | KR |
20010100328 | Nov 2001 | KR |
Entry |
---|
“Focus on OpenView A guide to Hewlett-Packard's Network and Systems Management Platform”, Nathan J. Muller, pp. 1-291, CBM Books, published 1995. |
“Client Server computing in mobile environments”, J. Jing et al. ACM Computing Surveys, vol. 31, Issue 2, pp. 117-159, ACM Press, Jul. 1999. |
“ESW4: enhanced scheme for WWW computing in wireless communication environments”, S. Hadjiefthymiades, et al, ACM SIGCOMM Computer Communication Review, vol. 29, Issue 5, pp. 24-35, ACM Press, Oct. 1999. |
“Introducing quality-of-service and traffic classes in wireless mobile networks”, J. Sevanto, et al. Proceedings of the 1st ACM International workshop on Wireless mobile multimedia, pp. 21-29, ACM Press, 1998. |
“Any Network, Any Terminal, Anywhere”, A. Fasbender et al. IEEE Personal Communications, Apr. 1999, pp. 22-30, IEEE Press, 1999. |
Douglas B. Terry et al., “Managing Update Conflicts in Bayou, a Weakly Connected Replicated Storage System,” Proceedings of the 15th ACM Symposium on Operating Systems Principles, 1995, pp. 172-182, Available at: <dl.acm.org/citation.cfm?id=224070>. |
Hewlett-Packard Development Company, L.P., Office Action, European Application No. 04754355.8, Date: Jul. 5, 2013, pp. 1-11. |
Hewlett-Packard Development Company, L.P., Office Action, European Application No. 04782849.6, Date: Jul. 3, 2013, pp. 1-5. |
Jonathan P. Munson and Prasun Dewan, “Sync: A Java Framework for Mobile Collaborative Applications,” IEEE, Jun. 1997, pp. 59-66, Available at: <ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=587549>. |
Teck Chia et al., U.S. Appl. No. 10/943,455, Notice of Allowance, Date Mailed: May 28, 2013, pp. 1-69. |
Tim Farnham et al., “IST-TRUST: A Perspective on the Reconfiguration of Future Mobile Terminals using Software Download,” The 11th IEEE International Symposium on Personal, Indoor and Mobile Radio Communications, 2000, pp. 1054-1059, Available at: <ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=881582>. |
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Parent | 11247459 | Oct 2005 | US |
Child | 12057004 | US |