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.