초록 ▼

A method and system for executing a streamed application on a client system utilizes a virtual file system installed in the client which is configured to appear to the operating system as a local storage device containing all of the application files required by the application. Prior to streaming,

A method and system for executing a streamed application on a client system utilizes a virtual file system installed in the client which is configured to appear to the operating system as a local storage device containing all of the application files required by the application. Prior to streaming, the application files are broken up into streamlets corresponding generally to various portions of the application files and these streamlets are delivered to the client by the server, preferably using a predictive algorithm to determine an optimal transmission order. After an initial set of streamlets is received, the application is executed from the virtual file system. File loads issued by the operating system to the virtual file system are translated to determine which streamlets correspond to the load request and the appropriate data is returned. If a needed streamlet is not present, a streamlet request is issued to the server and the virtual file system maintains a busy status until the necessary streamlets have been provided.

대표청구항 ▼

A method and system for executing a streamed application on a client system utilizes a virtual file system installed in the client which is configured to appear to the operating system as a local storage device containing all of the application files required by the application. Prior to streaming,

A method and system for executing a streamed application on a client system utilizes a virtual file system installed in the client which is configured to appear to the operating system as a local storage device containing all of the application files required by the application. Prior to streaming, the application files are broken up into streamlets corresponding generally to various portions of the application files and these streamlets are delivered to the client by the server, preferably using a predictive algorithm to determine an optimal transmission order. After an initial set of streamlets is received, the application is executed from the virtual file system. File loads issued by the operating system to the virtual file system are translated to determine which streamlets correspond to the load request and the appropriate data is returned. If a needed streamlet is not present, a streamlet request is issued to the server and the virtual file system maintains a busy status until the necessary streamlets have been provided. unction and the profiles of previously chosen images. 11. An image search system comprising: a computer; a plurality of images accessible by said computer, each of the plurality of images having associated therewith a plurality of characteristic functions for a plurality of categories accessible by said computer, at least one of the plurality of categories relating to the subject matter of the associated image; a plurality of selection probability functions, each of said selection probability functions corresponding to one of the categories, said plurality of selection probability functions being set to initial values; software executing on said computer for selecting and displaying a plurality of images, the plurality of images being selected based upon the relationship between the characteristic functions for each image and the values of the selection probability functions; software executing on said computer for receiving an indication of at least one chosen image and for adjusting the value of each of the selection probability functions based upon the characteristic functions of the chosen images; and wherein said software selects and displays, receives an indication of at least one chosen image, and adjusts the value of each of the selection probability functions iteratively until the search is terminated. 12. The image search system of claim 11 wherein each of the plurality of characteristic functions comprises a probability distribution function which describes the probability of an image being selected given user preferences within a category. 13. The image search system of claim 12 wherein one or more of the plurality of characteristic functions comprises a Gaussian function. 14. The image search system of claim 12 wherein one or more of the plurality of characteristic functions comprises a bell curve. 15. The image search system of claim 11 wherein each of the selection probability functions comprises a probability distribution function which describes the probability of a desired image being found given the initial value of the selection probability function and the characteristic functions of previously chosen images. 16. The image search system of claim 11 wherein the initial values of said plurality of selection probability functions are set such that statistical weighting among the categories is even and no category is favored. 17. The image search system of claim 11 wherein said software executing on said computer for selecting and displaying a plurality of images randomly selects values for each category, which value is in accordance with the selection probability function for that category, and selects images having characteristic functions corresponding to the randomly selected values for the categories. 18. An image search system comprising: a computer; a database accessible by said computer; a plurality of images stored on said database, each of the plurality of images having associated therewith information about the subject matter of the associated image; and software executing on said computer for iteratively selecting images randomly from said plurality of images by using a stochastic process which takes into account the subject matter of the associated images, for gathering user suggestions, and for skewing the random selection toward the user suggestions. 19. The image search system of claim 18 wherein said software iteratively selects images randomly from said plurality of images by using a stochastic process based upon at least one probability distribution function. 20. A method for searching and retrieving a desired image comprising the steps of: providing a computer; providing a plurality of images accessible by the computer, each of the plurality of images having associated therewith an image profile accessible by the computer, the image profile comprising information about the subject matter of the associated image; providing a plurality of selection probability functions ; setting the plurality of selection probability functions to initial values; selecting a plurality of images based upon the relationship between the profile for each image and the values of the selection probability functions; displaying the selected images; receiving an indication of at least one chosen image; adjusting the value of each of the selection probability functions based upon the profiles of the chosen images; and repeating said selecting step, said displaying step, said receiving step and said adjusting step until the search is terminated. 21. The method of claim 20 wherein each image profile comprises a plurality of rankings for a plurality of categories. 22. The method of claim 21 wherein the plurality of rankings comprise a plurality of characteristic functions. 23. The method of claim 22 wherein each of the plurality of characteristic functions comprises a probability distribution function which describes the probability of an image being selected given user preferences within a category. 24. The method of claim 23 wherein one or more of the plurality of characteristic functions comprises a Gaussian function. 25. The method of claim 23 wherein one or more of the plurality of characteristic functions comprises a bell curve. 26. The method of claim 21 wherein each of said selection probability functions corresponds to one of the categories. 27. The method of claim 26 wherein said setting the plurality of selection probability functions to initial values step comprises the step of setting the initial values of the plurality of selection probability functions such that statistical weighting among the categories is even and no category is favored. 28. The method of claim 26 wherein said step of selecting a plurality of images comprises randomly selecting values for each category, which value is in accordance with the selection probability function for that category, and selecting images having characteristic functions corresponding to the randomly selected values for the categories. 29. The method of claim 20 wherein each of the selection probability functions comprises a probability distribution function which describes the probability of a desired image being found given the initial value of the selection probability function and the profiles of previously chosen images. 30. A method for searching and retrieving a desired image comprising the steps of: providing a computer; providing a plurality of images accessible by the computer, each of the plurality of images having associated therewith a plurality of characteristic functions for a plurality of categories accessible by the computer, at least one of the plurality of categories relating to the subject matter of the associated image; providing a plurality of selection probability functions, each of the selection probability functions corresponding to one of the categories; setting the plurality of selection probability functions to initial values; selecting a plurality of images based upon the relationship between the characteristic functions for each image and the values of the selection probability functions; displaying the selected images; receiving an indication of at least one chosen image; adjusting the value of each of the selection probability functions based upon the characteristic functions of the chosen images; and repeating said selecting step, said displaying step, said receiving step and said adjusting step until the search is terminated. 31. The method of claim 30 wherein each of the plurality of characteristic functions comprises a probability distribution function which describes the probability of an image being selected given user preferences within a category. 32. The method of claim 31 wherein one or more of the plurality of characteristic functions comprises a Gaussian function. 33. The method of claim 31 wherein one or more of the plurality of characteristic functions comprises a bell curve. 34. The method of claim 3 0 wherein each of the selection probability functions comprises a probability distribution function which describes the probability of a desired image being found given the initial value of the selection probability function and the characteristic functions of previously chosen images. 35. The image search system of claim 30 wherein said setting the plurality of selection probability functions to initial values step comprises the step of setting the initial values of the plurality of selection probability functions such that statistical weighting among the categories is even and no category is favored. 36. The method of claim 30 wherein said selecting a plurality of images step comprises the step of randomly selecting values for each category, which value is in accordance with the selection probability function for that category, and selecting images having characteristic functions corresponding to the randomly selected values for the categories. 37. A method for searching and retrieving a desired image comprising the steps of: providing a computer; providing a database accessible by the computer; storing a plurality of images on the database, each of the plurality of images having associated therewith information about the subject matter of the associated image; selecting images randomly from the plurality of images by using a stochastic process which takes into account the subject matter of the associated images; gathering user suggestions; skewing the random selection toward the user suggestions; and iteratively repeating said selecting step, said gathering step and said skewing step until the search is terminated. 38. The method of claim 37 wherein said selecting step comprises the step of selecting images randomly from the plurality of images by using a stochastic process based upon at least one probability distribution function. 39. An image search system comprising: a computer; a plurality of images accessible by said computer, each of the plurality of images having associated therewith an image profile accessible by said computer; a plurality of selection probability functions, said plurality of selection probability functions being set to initial values, wherein each of said selection probability functions is a statistical function; software executing on said computer for iteratively selecting and displaying a plurality of images, the plurality of images being selected based upon the relationship between the profile for each image and the values of the selection probability functions; and software executing on said computer being responsive to a selection of one or more chosen images and iteratively adjusting the value of one or more of the selection probability functions based upon the profiles of the chosen images, wherein said software selects and displays, receives an indication of at least one chosen image, and adjusts the value of each of the selection probability functions iteratively until the search is terminated. 40. The image search system of claim 39 wherein each image profile comprises a plurality of categories, with a ranking of the image for one or more of said plurality of categories. 41. The image search system of claim 40 wherein each ranking comprises a characteristic function. 42. The image search system of claim 41 wherein said characteristic function comprises a probability distribution function which describes the probability of an image being selected given user preferences within a category. 43. The image search system of claim 42 wherein said characteristic function comprises a Gaussian function. 44. The image search system of claim 42 wherein said characteristic function comprises a bell curve. 45. The image search system of claim 40 wherein each of said selection probability functions corresponds to one of the categories. 46. The image search system of claim 45 wherein the initial values of said plurality of selection probability functions are set such that statistical w eighting among the categories is even and no category is favored. 47. The image search system of claim 45 wherein said software executing on said computer for selecting and displaying a plurality of images randomly selects values for each category, which value is in accordance with the selection probability function for that category, and selects images having characteristic functions corresponding to the randomly selected values for the categories. 48. The image search system of claim 39 wherein each of the selection probability functions comprises a probability distribution function which describes the probability of a desired image being found given the initial value of the selection probability function and the profiles of previously chosen images.