Patent Application
20120117189
1. Field of the Invention
This invention relates generally to a system and method of utilizing user feedback of a user device and more specifically to obtaining and analyzing user feedback.
2. Background Discussion
Generally, customer feedback of a user device, such as a personal computer, cell phone, PDA, television, PLAYSTATION™, PSP™ and the like, can be collected through surveys, call centers, or focus groups. Typically, conventional processing of feedback has several disadvantages. First, the customer feedback collected by this process does not have an effect on the development process since the development cycle is over by the time the machine is in the customers' hands. Second, it is too costly to conduct focus groups. It is also costly to have customers call in for software issues, for example, questions like “How do I burn a disc”, “Where do I go to find help”. Third, the manufacturer cannot directly gauge if customers are actually using their computer's software and hardware. Indeed, in many instances, when customers were asked about pre-installed device software on their computer many customers claimed to have used software that was not even installed on their device.
One embodiment of the present invention is directed to a method and apparatus (the method) for utilizing user feedback of a user device. The method includes identifying CPU state information for the user device and obtaining CPU usage when CPU is at p-state. An average CPU usage is calculated and the CPU is upgraded based on the calculated average CPU usage.
Another embodiment of the present invention is directed to the method described above and also includes determining whether the calculated average CPU usage is greater than a predetermined threshold usage.
Yet another embodiment of the present invention is directed to the method described above wherein the CPU state information indicates the CPU is at p-state, c-state and s-state.
Yet another embodiment of the present invention is directed to the method described above and also includes making recommendations for upgrading the CPU, when the calculated average CPU usage is greater than the predetermined threshold.
Yet another embodiment of the present invention is directed to the method described above and further includes upgrading the CPU based on a product bucket identification (ID).
Yet another embodiment of the present invention is directed to the method described above and also includes creating a user account for each user and collecting use pattern data for each user.
Yet another embodiment of the present invention is directed to the method described above and also includes identifying the product bucket identification (ID) and collecting usage information for a plurality of products having a same product bucket identification (ID). The collected usage information is used to generate recommendations for upgrading the CPU based on the product bucket identification (ID).
Yet another embodiment of the present invention is directed to the method described above and also includes upgrading CPU based on the user's request.
Yet another embodiment of the present invention is directed to the method described above wherein the upgrading step includes design modifications for other CPU devices.
Yet another embodiment of the present invention is directed to a client device that includes a user account module that stores use pattern data for a user, the use pattern data including CPU state information for the user device. A transmission module transmits the use pattern data to a remote location. A reception module receives processed data, the processed data being a function of the use pattern data and the CPU state information. A processor module utilizes the processed data to upgrade the CPU based on the received processed data.
Yet another embodiment of the present invention is directed to the client device described above and also includes a display unit that displays an indication of the CPU status.
Yet another embodiment of the present invention is directed to the client device as described above, wherein the use pattern data is updated at a predetermined time interval.
Yet another embodiment of the present invention is directed to the client device as described above, wherein the CPU state information indicates the CPU is at p-state, c-state and s-state.
Yet another embodiment of the present invention is directed to the client device as described above, wherein the processed data includes recommendations for upgrading the CPU, when a calculated average CPU usage is greater than a predetermined threshold.
Other embodiments of the present invention include the methods described above but implemented using apparatus or programmed as computer code to be executed by one or more processors operating in conjunction with one or more electronic storage media.
To the accomplishment of the foregoing and related ends, certain illustrative embodiments of the invention are described herein in connection with the following description and the annexed drawings. These embodiments are indicative, however, of but a few of the various ways in which the principles of the invention may be employed and the present invention is intended to include all such aspects and their equivalents. Other advantages, embodiments and novel features of the invention may become apparent from the following description of the invention when considered in conjunction with the drawings. The following description, given by way of example, but not intended to limit the invention solely to the specific embodiments described, may best be understood in conjunction with the accompanying drawings, in which:
It is noted that in this disclosure and particularly in the claims and/or paragraphs, terms such as “comprises,” “comprised,” “comprising,” and the like can have the meaning attributed to it in U.S. patent law; that is, they can mean “includes,” “included,” “including,” “including, but not limited to” and the like, and allow for elements not explicitly recited. Terms such as “consisting essentially of” and “consists essentially of” have the meaning ascribed to them in U.S. patent law; that is, they allow for elements not explicitly recited, but exclude elements that are found in the prior art or that affect a basic or novel characteristic of the invention. These and other embodiments are disclosed or are apparent from and encompassed by, the following description. As used in this application, the terms “component” and “system” are intended to refer to a computer-related entity, either hardware, a combination of hardware and software, software, or software in execution. For example, a component may be, but is not limited to being, a process running on a processor, a processor, an object, an executable, a thread of execution, a program, and/or a computer. By way of illustration, both an application running on a server and the server can be a component. One or more components may reside within a process and/or thread of execution and a component may be localized on one computer and/or distributed between two or more computers.
Furthermore, the detailed description describes various embodiments of the present invention for illustration purposes and embodiments of the present invention include the methods described and may be implemented using one or more apparatus, such as processing apparatus coupled to electronic media. Embodiments of the present invention may be stored on an electronic media (electronic memory, RAM, ROM, EEPROM) or programmed as computer code (e.g., source code, object code or any suitable programming language) to be executed by one or more processors operating in conjunction with each other and/or one or more electronic storage media.
Embodiments of the present invention may be implemented using one or more processing devices, or processing modules. The processing devices, or modules, may be coupled such that portions of the processing and/or data manipulation may be performed at one or more processing devices and shared or transmitted between a plurality of processing devices or modules.
Indeed, the present invention may be implemented in a distributed or “cloud” computing environment in which shared resources, software and information are provided to computers and other devices over a network, which may be, for example, the Internet. “Cloud computing” typically involves delivering hosted services over the Internet. A cloud service typically has three distinct characteristics that differentiate it from traditional hosting. One characteristic is that it is sold on demand, typically by the minute or the hour; secondly, it is elastic—a user can have as much or as little of a service as they want at any given time; and thirdly, the service is usually fully managed by the provider (the consumer needs nothing but a personal computer and Internet access). Significant innovations in virtualization and distributed computing, as well as improved access to high-speed Internet have accelerated interest in cloud computing. The cloud can be private or public. A public cloud typically sells services to anyone on the Internet. (Currently, Amazon Web Services™ is the largest public cloud provider.) A private cloud is a proprietary network or a data center that supplies hosted services to a limited number of people. When a service provider uses public cloud resources to create their private cloud, the result is called a virtual private cloud. Private or public, the goal of cloud computing is to provide easy, scalable access to computing.
“Distributed computing”, or “distributed systems” relate to a system of multiple autonomous computers or processing devices or facilities that communicate through a network. The computers interact with each other in order to achieve a particular goal. A computer program that runs in a distributed system is typically referred to as a “distributed program” and “distributed programming” is the process of writing such programs. Distributed computing also refers to the use of distributed systems to solve computational problems. Typically, in distributed computing, a problem is divided into multiple tasks, each of which is solved by one or more computers. In general, distributed computing is any computing that involves multiple computers remote from each other that each has a role in a computation problem or information processing.
The network 102 is, for example, any combination of linked computers, or processing devices, adapted to transfer and process data. The network 102 may be private Internet Protocol (IP) networks, as well as public IP networks, such as the Internet that can utilize World Wide Web (www) browsing functionality. An example of a wired network is a network that uses communication buses and MODEMS, or DSL lines, or a local area network (LAN) or a wide area network (WAN) to transmit and receive data between terminals. An example of a wireless network is a wireless LAN. Global System for Mobile Communication (GSM) is another example of a wireless network. The GSM network is divided into three major systems which are the switching system, the base station system, and the operation and support system (GSM). Also, IEEE 802.11 (Wi-Fi) is a commonly used wireless network in computer systems, which enables connection to the Internet or other machines that have Wi-Fi functionality. Wi-Fi networks broadcast radio waves that can be picked up by Wi-Fi receivers that are attached to different computers.
The HTTPs server module, or facility, or unit, 104 is typically one or more processors with associated memory, such as computers, or other processing devices such as a desktop computer and the like. The HTTPs server 104 may also be used as an external server to which gather usage data is sent from the user devices. The HTTPs server 104 includes CPU 160, which is operatively coupled to memory 164 via interconnection medium 162. The CPU 160 is a processing unit that typically includes an ALU and is configured to perform processing operations and manipulations. Memory 164 is typically an electronic storage medium that stores data in electronic format.
The file server module, or facility, or unit, 106 is typically a server, computer, or other processing devices such as a desktop computer, laptop computer, and the like. The server module 106 includes one or more processors 120 bi-directionally coupled with associated memory module 124 via wired or wireless medium 122. The memory module 124 of the file server 106 may comprise a plurality of algorithm storage modules 500, 600, 700, 800, 900, 1000, 1100 and 1200. The file server 106 may also be an internal server for processing data sent from the HTTPs server 104.
The database server module, or facility, or unit, 108 typically includes one or more processors 126 bi-directionally coupled with associated memory 130 via wired or wireless medium 128. Database server module 108 is typically a computer, server or other processing device such as a desktop computer, laptop computer, and the like. The memory 130 comprises an algorithm 138 for data analysis and a plurality of databases, database (1) 132, database (2) 134 . . . database (n) 136, (where “n” is any suitable number) for storing data. The database server 108 is used as a server for data analysis.
Similarly, the web server module, or facility, or unit, 110 typically includes one or more processors 140 bi-directionally coupled with associated memory 144 via wired or wireless medium 142. Web server module 110 includes computers, or other processing devices such as a desktop computer, laptop computer, and the like. The memory 144 comprises an algorithm 146, output means 148, such as a monitor, input means 150, such as a keyboard or mouse, and browser software 152. The web server 110 is used as a server to host and build website.
It is noted that the file server 106, the database server 108 and the web storage 110 may be a single server, and also may be implemented as one or more separate servers, which may be used in a cloud computing or distributed computing environment.
User devices 112(a), 112(b) . . . 112(n) (where “n” is any suitable number) are connected directly to the communication network 102, via associated communication medium 113(a) . . . (n). User device 112 may be any suitable consumer electronic (CE) unit or module or device. As shown in
The HTTPs server 104, the file server 106 and the user devices 112(a), 112(b) . . . 112(n) are coupled to network 102 via an associated bi-directional communication medium, which may be for example a serial bus such as IEEE 1394, or other wire or wireless transmission medium. Also, web server 110 is in bi-directional communication with database server 108 via communication medium 180, which may be a wire or wireless connection. Database server 108 is in bi-directional communication with file server 106 via communication medium 170, which may be a wire or wireless connection.
Application Usage Data (AUD) (
The invention disclosed herein may be practiced using programmable digital computers.
One skilled in the art will recognize that, although the data storage device, or unit 369 and memory 362, 363 are depicted as different units, the data storage unit 369 and memory 362, 363 can be parts of the same unit or units, and that the functions of one can be shared in whole or in part by the other, e.g., as RAM disks, virtual memory, etc. It will also be appreciated that any particular computer may have multiple components of a given type, e.g., processors 361, input devices 367, communications unit 370, etc.
The data storage device 369 and/or memory 362, 363 may store an operating system such as Microsoft Windows 7®, Windows XP® or Vista™, Linux®, Mac OS®, or Unix®, Other programs may be stored instead of or in addition to the operating system. It will be appreciated that a computer system may also be implemented on platforms and operating systems other than those mentioned. Any operating system or other program, or any part of either, may be written using one or more programming languages such as, e.g., Java®, C, C++, C#, Visual Basic®, VB.NET®, Peri, Ruby, Python, or other programming languages, possibly using object oriented design and/or coding techniques. These platforms and operating systems may be accessed in a cloud computing or distributed computing environment.
The computer system 300 may also include additional components and/or systems, such as network connections, additional memory, additional processors, network interfaces, input/output ports or busses. Also the programs and data may be received by and stored in the system in alternative ways. For example, a computer-readable storage medium (CRSM) reader, such as, e.g., a magnetic disk drive, magneto-optical drive, optical disk drive, or flash drive, may be coupled to the communications bus 364 for reading from a computer-readable storage medium (CRSM) such as, e.g., a magnetic disk, a magneto-optical disk, an optical disk, or flash RAM. Accordingly, the computer system 300 may receive programs and/or data via the CRSM reader. Further, it will be appreciated that the term “memory” herein is intended to include various types of suitable data storage media, whether permanent or temporary, such as transitory electronic memories, non-transitory computer-readable medium and/or computer-writable medium.
Two or more computer systems 300 may be connected, e.g., in one or more networks, via, e.g., their respective communications interfaces and/or network interfaces (not depicted).
AUD 404 is comprised of Generic System information 406 and an Application Usage Log 416. The Generic System Information 406 is comprised of a randomly generated ID for the system called a Globally Unique Identifier (GUID) 408 which allows the system to maintain a history of data recorded on a computer without reporting any personal identifiable information this maintaining user privacy, model information 410, which is the model of the system, region information 412, which includes information on what language the user of the system selected, and OS information 414, which includes what operating system and what version of that operating system that the system is running.
The Application Usage Log 416 comprises date information 418, time information 420, area information 42, which includes data indicating where an action occurred, action information 424, which includes data on what action occurred, e.g. a click, and result information 426, which includes data indicating the result from the action.
SUD 428 is comprised of Hardware information 430 and Software information 446. Hardware information 430 comprises CPU usage data 432, network usage data 434, disk bandwidth data 436, and operation mode information 438. The operation mode information may comprise P-State information 440 indicating the voltage and frequency of the CPU, C-State information 442 indicating which of several included power state modes that the CPU is operating in, and S-State information 444 indicating a system in Standby/Sleep/Hibernate mode.
The software information 446 comprises Process Information 448, which comprises a list of all processes ran on the system, their descriptions, when it was ran, how much CPU, Disk, and Network bandwidth was used, and how often it was used. The software information 446 further comprises DLL information 450, which is a list of all DLLs associated with each process, their descriptions, when it was run, how much CPU, Disk, and Network bandwidth, was used and how often it was used.
After the Application Usage Data (AUD) and System Usage Data (SUD) are gathered, an upload process zips and encrypts a data file. The data file is then transmitted using HTTPS protocol for secure transaction. The zipping, encrypting, and uploading can be written as generic code so that other applications may use the same methods. AUD and SUD may be sent to the file server at any predetermined or requested time. For example, AUD may be sent to the file server once per month and SUD may be sent to the file server once per week.
Portion 702 shows an example of statistics. This is illustrated as three columns of “statistic” “interval 1” and “interval 2”. The statistic column lists various categories, such as “Sust Disk BW(MB/sec)”; “Disk BW (conf)”; “Max Disk BW(MB/Sec)”; “Sust NetBW(KB/Sec)” and others, as shown in area 702.
Portion 704 shows a list of processes that may be executed. As shown in portion 704, these may include “devenv.exe”; “svchost.exe”; “chrome.exe”; “System” and others, as shown in portion 704. The software information 704 may be organized with different color highlighting. While
Portion 706 shows sample processes. This includes, for example, a listing of a “process”, “process time”, “i0Bytes”, “nInvoke”; “runtime”. The “process” list includes sample processes of the portion 704.
Portion 708 shows a menu sub-screen with headings “Slow Pct”; “Net”; “Disk”; “Proc” and “All”. Additional headings may also be used in portion 708.
Portions 1002 and 1004 are areas used to display graphical representations. Specifically, graphical representations 1002 and 1004 illustrate a pictorial representation of collected data.
Portion 1008 shows a summary area that provides a display or output in tabulated or written form.
Portion 1006 shows a listing a various folders and categories of the system, as described herein. These categories include, for example, “One Click and Tune Up”; “Trouble Shoot and Diag.”; “Restore/Recovery”; “Help and Support”; “Performance”; “Time To Desktop”; “Online Crash Analysis” etc.
Next, in step 1110, the process determines whether the CPU is a P-state, based on the obtained state information. If it is determined that the CPU is not in at P-state, the process goes back to step 1108. The process may check again immediately, whether the CPU is in a P-State or wait a pre-determined amount of time. If, at step 1110, the CPU is determined to be at a P-state, CPU usage information is obtained, as shown in step 1112. After the CPU usage information is obtained, the information is stored and previously acquired information may be updated, re-calculated, or calculated. For example, an average CPU usage calculation may be performed using previously obtained CPU usage information and the current CPU usage information. Once the calculation is made, the previously stored average CPU usage information may be updated.
As another example, a maximum CPU usage may be stored in memory. If the CPU usage information obtained in 1112 is determined to be greater than the stored SPU usage information, the newly obtained information is stored. As another example, CPU usage (average or maximum) may be calculated over a predetermined period of time or at an instantaneous point in time, or a predetermined time of day. In step 1114, average maximum CPU usage information is calculated and updated.
After the CPU usage information is obtained, the process determines whether an average maximum CPU usage is greater than a threshold in step 1116. If during the process, the determination is no, the process proceeds to step 1120, which will be described later. However, if at step 1116, the process determines yes, e.g. the average maximum CPU usage is greater than a threshold, the process proceeds to step 1118. At step 1118, an upgrade recommendation based on the average maximum CPU usage information is made. For example, one recommendation may be made if the average maximum CPU usage is meets a specific threshold and another for a different specific threshold, or one recommendation may be made if the average maximum SPU usage falls within a specific range and another recommendation is made if the average maximum CPU usage is in a different specific range.
In step 1120, a user is presented with a choice to upgrade the CPU. The process arrives at step 1120 when (1) the user does not agree to provide product use pattern data or setting information, (2) when the calculated average maximum CPU usage is below a certain threshold, or (3) when the average maximum CPU usage is greater than a threshold and the process has made a recommendation. From step 1120, the process may proceed to perform an upgrade when the user answers yes at step 1120 and chooses to upgrade the CPU. If the user instead chooses no at step 1120, the process proceeds to end at 1124. After the upgrade is performed in step 1122, the process proceeds to end 1124.
It is also noted that according to the recommender program described above, the obtained usage information, such as use patterns and setting information of a user's account, could also be used for data mining based on other components of the user device. For example, similar to the program for making CPU upgrading recommendations, the system may also make upgrading recommendations to other components, such as motherboard, power supply, removable media devices, secondary storage, graphics card, sound card, input and output peripherals, Network Interface Card (NIC), screen size, etc. The system may also provide recommendations for upgrading frequently used applications for the user's account. Therefore, the system may provide the user with upgrading recommendations for the complete system of the user device.
It is also an embodiment of the present invention that the CPU usage data may be stored in association with the user account and when the user wishes to make a future purchase, the CPU usage data can be used to make a recommendation.
It is also an embodiment of the present invention that the CPU usage data may be used to design other computing or consumer electronic devices. Thus, the embodiments of the present invention are directed to improving an existing computing device; providing recommendations to a user based on their specific usage requirements (as obtained from their usage data); and utilization of the CPU usage data to design the next generation of computing devices.
Transmission module 1206 transmits the use pattern data to a remote location. The remote location may be one or more of remote devices, such as one or more of the server devices (104, 106, 108, and/or 10) shown in
A reception module 1208 receives processed data, the processed data being a function of the use pattern data. The processed data may also identify one or more CPU upgrades or CPU modifications for the user device.
The processor module (CPU) 1202 utilizes the processed data, including the CPU recommendations and/or CPU upgrade data to modify operation of the client device. Display module 1220, which may be an LCD, plasma, CRT or other suitable display device that can display text and/or image data, displays an indication of the received processed data and displays an indication of the modified operation of the client device, and/or recommendations or a combination thereof. The modified operation may include, for example, what software is operating on the client device, the CPU operating conditions, memory allocation, troubleshooting routines, anti-virus software and other hardware and/or software operations of the client device.
Thus, a user at a client device, or terminal, 1200 can receive an indication of how their device operation has been modified based on the processed use data and what recommendations are being generated based on the use pattern data. This indication may also include device parameters and/or functions that have been optimized and parameters and/or functions that have not been optimized. It can also indicate the status of one or more troubleshooting routines or algorithms. The troubleshooting routines may be updated and/or modified based on additional use pattern data that is acquired subsequent to execution of a previous troubleshooting routine.
The use pattern data may be updated at a predetermined time interval, such as every 24 hours, every month or after new software and/or hardware has been introduced. Thus, the use pattern data module is iterative by updating the use pattern data of the device at a predetermined time interval and/or operational status.
The processed use pattern data including the CPU state information may then be used to modify operation of the client device and/or provide recommendations, as shown in step 1310. This modification may include retrieving additional software, suggesting additional software upgrades, suggesting additional hardware upgrades, changing the operational status of the device, troubleshooting, downloading one or more software patches, or other modification or recommendation based on the received processed data.
The result of the processed data and/or recommendations may be displayed on a display device, as shown in step 1312. This may include displaying a message regarding software upgrades, hardware upgrades, optimization of one or more device parameters, such as CPU operation, detected virus, anti-virus software or other messages and/or recommendation to a user to improve operation of the device or suggest a more suitable device or other additional devices that the user may find enhance the computing experience.
In step 1314, a determination is made whether there is any additional use pattern data. This includes use pattern data that has been generated since the previous collection of use pattern data or use pattern data that results from modified operation of the device and/or additional software/hardware. If there is additional use pattern data, “yes” line 1316 leads to step 1304 and the process repeats, as described above. If there is no additional use pattern data, “no” line 1318 leads to end step 1320.
Thus, the CPU state information obtained from the user device may be used to indicate the CPU is at p-state, c-state and s-state. The processed data includes recommendations for upgrading the CPU, when a calculated average CPU usage is greater than a predetermined threshold.
It will be appreciated from the above that the invention may be implemented as computer software, which may be supplied on a storage medium or via a transmission medium such as a local-area network or a wide-area network, such as the Internet. It is to be further understood that, because some of the constituent system components and method steps depicted in the accompanying Figures can be implemented in software, the actual connections between the systems components (or the process steps) may differ depending upon the manner in which the present invention is programmed. Given the teachings of the present invention provided herein, one of ordinary skill in the related art will be able to contemplate these and similar implementations or configurations of the present invention.
It is to be understood that the present invention can be implemented in various forms of hardware, software, firmware, special purpose processes, or a combination thereof. In one embodiment, the present invention can be implemented in software as an application program tangible embodied on a computer readable program storage device. The application program can be uploaded to, and executed by, a machine comprising any suitable architecture.
The particular embodiments disclosed above are illustrative only, as the invention may be modified and practiced in different but equivalent manners apparent to those skilled in the art having the benefit of the teachings herein. Furthermore, no limitations are intended to the details of construction or design herein shown, other than as described in the claims below. It is therefore evident that the particular embodiments disclosed above may be altered or modified and all such variations are considered within the scope and spirit of the invention. Although illustrative embodiments of the invention have been described in detail herein with reference to the accompanying drawings, it is to be understood that the invention is not limited to those precise embodiments, and that various changes and modifications can be effected therein by one skilled in the art without departing from the scope and spirit of the invention as defined by the appended claims.
This application claims the benefit of previously filed U.S. Provisional Application 61/412,030 filed Nov. 10, 2010 entitled “VAIO Care Metrics” by Lam et al. The entirety of which is hereby incorporated by reference herein.
| Number | Date | Country | |
|---|---|---|---|
| 61412030 | Nov 2010 | US |
