Author: claimsbot

1. A distributed intelligent system comprising:
at least one gateway server configured for receiving meter data from one or more nodes of a distributed meter network; and
at least one subscriber station in communication with the at least one gateway server via a communication network;
wherein the at least one gateway server is further configured to selectively distribute the received meter data to the at least one subscriber station in accordance with a policy.
2. The distributed intelligent system of claim 1, wherein each gateway server is remotely located with respect to each node.
3. The distributed intelligent system of claim 1, wherein each subscriber station is remotely located with respect to each gateway server.
4. The distributed intelligent system of claim 1, wherein the distributed meter network comprises a distributed flow meter network.
5. The distributed intelligent system of claim 4, wherein each node of the distributed meter network is associated with a point-of-sale (POS) location, and wherein the meter data comprises at least one of a beverage flow rate or a beverage flow total for each of one or more beverages dispensed at the POS location.
6. The distributed intelligent system of claim 5, wherein the at least one gateway server is configured to transmit an inventory control message based on the meter data.
7. The distributed intelligent system of claim 5, wherein the at least one gateway server is configured to transmit an advertisement message based on the meter data
8. The distributed intelligent system of claim 1, wherein the at least one gateway server is further configured for receiving meter data from one or more of the nodes responsive to polling requests transmitted thereto by the at least one gateway server.
9. The distributed intelligent system of claim 8, wherein the at least one gateway server is further configured for adaptively changing a polling frequency of the one or more polled nodes based upon a characteristic of the meter data received therefrom.
10. The distributed intelligent system of claim 1, wherein the policy is a content-based policy.
11. The distributed intelligent system of claim 10, wherein the content-based policy comprises one or more content-based criteria for identifying the meter data to be selectively distributed.
12. The distributed intelligent system of claim 11, wherein at least one of the one or more content-based criteria is selected from the following: a beverage product, a beverage brand, and a POS location.
13. The distributed intelligent system of claim 1, wherein the policy is a condition-based policy.
14. The distributed intelligent system of claim 13, wherein the condition-based policy comprises one or more predetermined conditions for identifying the meter data to be selectively distributed.
15. The distributed intelligent system of claim 14, wherein at least one of the predetermined conditions is a predetermined flow total condition.
16. The distributed intelligent system of claim 5, wherein the at least one gateway server is configured to generate a consumption pattern model.
17. The distributed intelligent system of claim 16, wherein the at least one gateway server is configured to automatically control a beverage inventory at the POS location in accordance with an inventory control policy, wherein the inventory control policy is based at least in part upon the consumption pattern model.
18. The distributed intelligent system of claim 16, wherein the at least one gateway server is configured to automatically generate an advertisement message in accordance with an advertisement policy, wherein the advertisement policy is based at least in part upon the consumption pattern model.
19. The distributed intelligent system of claim 5, wherein the at least one gateway server is configured to generate a consumer model.
20. The distributed intelligent system of claim 19, wherein the at least one gateway server is configured to automatically generate an advertisement message in accordance with an advertisement policy, wherein the advertisement policy is based at least in part upon the consumer model.
21. The distributed intelligent system of claim 1, wherein the gateway server comprises a load-balancing policy stored therein.
22. The distributed intelligent system of claim 1, further comprising at least one redundant backup gateway server.
23. The distributed intelligent system of claim 1, wherein the communication network comprises the Internet.
24. A method comprising:
receiving meter data from one or more nodes of a distributed meter network at at least one gateway server; and
selectively distributing via a communication network the received meter data to at least one subscriber station in accordance with a policy.
25. The method of claim 24, wherein receiving meter data from one or more nodes of the meter network includes receiving at least one of a beverage flow rate or a beverage flow total for each of one or more beverages dispensed at a POS location.
26. The method of claim 25, further comprising transmitting an inventory control message based on the meter data.
27. The method of claim 25, further comprising transmitting an advertisement message based on the meter data.
28. The method of claim 24, further comprising receiving meter data from the one or more nodes responsive to polling requests transmitted thereto by the at least one gateway server
29. The method of claim 28, further comprising adaptively changing a polling frequency of the one or more polled nodes based upon a characteristic of the meter data received therefrom.
30. The method of claim 24, wherein selectively distributing the received meter data to at least one subscriber station in accordance with a policy comprises selectively distributing the received meter data in accordance with a content-based policy.
31. The method of claim 24, wherein selectively distributing the received meter data to at least one subscriber station in accordance with a policy comprises selectively distributing the received meter data in accordance with a condition-based policy.
32. The method of claim 25, further comprising generating a consumption pattern model based on the meter data.
33. The method of claim 32, further comprising automatically controlling a beverage inventory at the POS location in accordance with an inventory control policy, wherein the inventory control policy is based at least in part upon the consumption pattern model.
34. The method of claim 32, further comprising automatically generating an advertisement message in accordance with an advertisement policy, wherein the advertisement policy is based at least in part upon the consumption pattern model.
35. The method of claim 25, further comprising generating a consumer model based on the meter data.
36. The method of claim 35, further comprising automatically generating an advertisement message in accordance with an advertisement policy, wherein the advertisement policy is based at least in part upon the consumer model.
37. A distributed intelligent system comprising at least one gateway server that generates a real time reconciliation report based on a reconciliation of real time meter data and real time sales data received from a node of a distributed meter network.
38. The distributed intelligent system of claim 37, further comprising a subscriber station in communication with the at least one gateway server for receiving the report.
39. The distributed intelligent system of claim 37, wherein the distributed meter network comprises a distributed flow meter network.
40. The distributed intelligent system of claim 39, wherein the node of the distributed meter network is associated with a point-of-sale (POS) location, wherein the meter data comprises a flow total for each of one or more beverages dispensed at the POS location, and wherein the sales data comprises a sales amount for each of the one or more dispensed beverages.

The claims below are in addition to those above.
All refrences to claim(s) which appear below refer to the numbering after this setence.

1. A server-client network environment, comprising:
a not-as-yet operational client site comprising a client-hardware platform not loaded with any client-software application program;
a fully operational server site comprising a server-hardware platform, a server-software application program, and a client-software application program; and
a client-control utility program installed on the not-as-yet operational client site and providing for an automated download of said client-software application program from the server site.
2. The server-client network environment of claim 1, wherein:
the client-control utility program provides for broadcasts of its identity on a computer network that interconnects the client site and the server site.
3. The server-client network environment of claim 1, wherein:
the server is responsive to broadcasts from the client-control utility program over a computer network that interconnects the client site and the server site.
4. The server-client network environment of claim 1, wherein:
the client-control utility program provides for client initialization after downloading said client-software application program.
5. The server-client network environment of claim 1, further comprising a printing system including:
a plurality of raster-image processors (RIP’s) for converting page description language commands into a bitmap for a printer engine;
a profiler for receiving multiple-page print requests from a computer application program and operating system, and providing a complexity estimate of the command language stream for each print-page and a dependency list of any inter-print-page resources; and
a scheduler connected to receive said complexity estimates and said dependency list, and able to dispatch individual print-page raster-image processor jobs to particular RIP’s depending on said complexity estimates and said dependency list.
6. The server-client network environment and printing system of claim 5, further comprising:
a page manager connected to receive finished raster-image processing jobs from each of the RIP’s in whatever order they are completed, and then able to output such in an original page order.
7. The server-client network environment and printing system of claim 5, wherein:
the scheduler is such that said complexity estimates and said dependency list are used to minimize idle times for the RIP’s.
8. The server-client network environment and printing system of claim 5, wherein:
the profiler is such that it includes an application program interface (API) that is used to provide detailed profile information to the scheduler in a print command stream.
9. The server-client network environment and printing system of claim 5, wherein:
the profiler is connected to a printer driver through an application program interface (API), and thereby provides a profile information to the scheduler in a print command stream.
10. A method of printing multi-page documents with multiple raster-image processors (RIP’s), the method comprising:
deploying a not-as-yet operational client site comprising a client-hardware platform not loaded with any client-software application program;
placing on-line a fully operational server site comprising a server-hardware platform, a server-software application program, and a client-software application program;
installing a client-control utility program on the not-as-yet operational client site and providing for an automated download of said client-software application program from the server site;
profiling the command stream complexities and resource dependencies of a series of pages to be printed;
associating a profile of the command stream complexities and resource dependencies of a series of pages to be printed with a printing command stream; and
dispatching individual raster-image processor jobs for each of said pages to be printed to particular RIP’s according to said profile.
11. The method of claim 10, wherein:
the step of dispatching is such that said complexity estimates and said dependency list are used to minimize idle times for the RIP’s.
12. The method of claim 10, further comprising:
collecting the individual outputs of each raster-image processor and recombining them back into a page-ordered sequence for a print engine.

1. A data processing apparatus comprising:
a configuration data storing unit that stores, for each device that executes data processing assigned to itself, pieces of configuration data defining respective logic circuits that demonstrate different processing performances when the logic circuits are configured onto the devices, respectively;
a logic circuit configuration unit that configures a combination of the logic circuits onto the devices by reading a piece of the configuration data for each device, from among the pieces of the configuration data stored in the configuration data storing unit, and inputting the read pieces of the configuration data to the devices, respectively;
a total power consumption measuring unit that measures total power consumption required at a time of execution of the data processing by the devices onto which the logic circuits are configured by the logic circuit configuration unit; and
a logic circuit determining unit that determines, from among combinations of the logic circuits configured by the logic circuit configuration unit, a combination in which an actually measured value of the total power consumption measured by the total power consumption measuring unit falls within a predetermined target value of the total power consumption and which demonstrates optimum processing performance as the logic circuits to be configured onto the devices at a time of actual execution of the data processing.
2. The data processing apparatus according to claim 1, further comprising:
a priority order table that stores a priority order indicating the decreasing order of the processing performance predetermined by a user in correspondence with combination information for specifying a combination of the pieces of the configuration data to be input to the devices, wherein
the logic circuit configuration unit refers to the combination information stored on the priority order table, in the decreasing order of the processing performance, based on the priority order, and reads the pieces of the configuration data to be input to the devices from the configuration data configuration unit so as to configure the logic circuits onto the devices, respectively,
the total power consumption measuring unit measures the total power consumption every time the logic circuits are configured onto the devices by the logic circuit configuration unit, and
the logic circuit determining unit determines whether the actually measured value of the total power consumption is within the target value of the total power consumption every time the total power consumption is measured by the total power consumption measuring unit and, in the case of obtaining determination results to the effect that the actually measured value of the total power consumption falls within the target value of the total power consumption, determines the combination of the logic circuits configured by the logic circuit configuration unit as the logic circuits to be configured onto the devices at the time of actual execution of the data processing and, in the case of obtaining determination results to the effect that the actually measured value of the total power consumption does not fall within the target value of the total power consumption, changes the combination information to be referred to by the logic circuit configuration unit to the combination information of one rank lower priority order.
3. A data processing method comprising:
storing, for each device that executes data processing assigned to itself, pieces of configuration data defining respective logic circuits that demonstrate different processing performances when the logic circuits are configured onto the devices, respectively;
configuring a combination of the logic circuits onto the devices by reading a piece of the configuration data for each device, from among the pieces of the configuration data stored in the storing, and inputting the read pieces of the configuration data to the devices, respectively;
measuring total power consumption required at a time of execution of the data processing by the devices onto which the logic circuits are configured in the configuring; and
determining, from among combinations of the logic circuits configured in the configuring, a combination in which an actually measured value of the total power consumption measured in the measuring falls within a predetermined target value of the total power consumption and which demonstrates optimum processing performance as the logic circuits to be configured onto the devices at a time of actual execution of the data processing.
4. A computer readable storage medium containing instructions that, when executed by a computer, causes the computer to perform:
storing, for each device that executes data processing assigned to itself, pieces of configuration data defining respective logic circuits that demonstrate different processing performances when the logic circuits are configured onto the devices, respectively;
configuring a combination of the logic circuits onto the devices by reading a piece of the configuration data for each device, from among the pieces of the configuration data stored in the storing, and inputting the read pieces of the configuration data to the devices, respectively;
measuring total power consumption required at a time of execution of the data processing by the devices onto which the logic circuits are configured in the configuring; and
determining, from among combinations of the logic circuits configured in the configuring, a combination in which an actually measured value of the total power consumption measured in the measuring falls within a predetermined target value of the total power consumption and which demonstrates optimum processing performance as the logic circuits to be configured onto the devices at a time of actual execution of the data processing.

The claims below are in addition to those above.
All refrences to claim(s) which appear below refer to the numbering after this setence.

1. A method for storing and retrieving data comprising:
storing at least one magnetic field strength;
utilizing said at least one stored magnetic field strength to cause splitting or shifting of at least one frequency in at least one material;
detecting at least one of a split frequency, a shifted frequency and a splitting frequency in said at least one material;
assigning a data value to said splitting or shifting of frequency; and
reading said splitting or shifting of frequency as said assigned data value.
2. The method of claim 1, wherein said detecting comprises interrogating said at least one material with electromagnetic energy to determine said shifting or splitting of frequency.
3. The method of claim 1, wherein said at least one material comprises at least one magnetic material.
4. The method of claim 3, wherein said at least one material comprises at least one material contiguous to at least one magnetic material.
5. The method of claim 1, wherein said method for storing data comprises a base-2 data storage system.
6. The method of claim 1, wherein said method for storing data comprises greater than a base-2 data storage system.
7. The method of claim 1, wherein said splitting or shifting of frequency comprises at least one Zeeman effect.
8. A method for reading data comprising:
utilizing at least one stored magnetic field strength which results in a splitting or shifting of at least one frequency in at least one material;
detecting at least one of a split frequency, a shifted frequency and a splitting frequency in said at least one material;
assigning a data value to said splitting or shifting of frequency; and
reading said shifting or splitting of frequency as said assigned data value.
9. A data storage apparatus comprising:
means for determining at least one stored magnetic field strength to be stored, which stored field strength results in at least one of a split frequency, a shifted frequency and a splitting frequency in at least one material;
means for assigning a data value to said shifting or splitting of frequency; and means for storing said at least one stored magnetic field strength.
10. A data reading apparatus comprising:
means for utilizing at least one stored magnetic field strength which results in a splitting or shifting of at least one frequency in at least one material;
means for detecting at least one of a split frequency, a shifted frequency and a splitting frequency in said at least one material due to said at least one stored magnetic field strength;
means for assigning a data value to said amount of splitting or shifting of frequency; and
means for reading said splitting or shifting of frequency as said assigned data value.
11. The apparatus of claim 9, wherein said at least one material comprises at least one magnetic material.
12. The apparatus of claim 9, wherein said at least one material comprises at least one member selected from the group consisting of magnetic tapes, magnetic cards, and magnetic disks and magnetic hard drives.
13. The apparatus of claim 10, wherein said at least one material comprises at least one magnetic material.
14. The apparatus of claim 10, wherein said at least one material comprises at least one member selected from the group consisting of magnetic tapes, magnetic cards, magnetic disks and magnetic hard drives.
15. A method for storing data comprising;
determining at least one stored magnetic field strength to be stored, which stored field strength results in at least one of a split frequency, a shifted frequency and a splitting frequency in at least one material;
assigning a data value to said splitting or shifting of at least one frequency; and
storing said splitting or shifting of frequency as said assigned data value.