SYSTEMS AND METHODS FOR PROVIDING VIDEO-ON-DEMAND SERVICES FOR BROADCASTING SYSTEMS

Abstract: A method for sending data to a client to provide data-on-demand services, for example in a Cable Television System (120), comprises the steps of: receiving a data file, specifying a time interval, parsing the data file into a plurality of data blocks based on the time interval such that each data block is displayable during a time interval, determining a required number of time slots to send the data file, allocating to each time slot at least a first of the plurality of data blocks and optionally one or more additional data blocks, such that starting from any of the time slots, (i) the data file can be displayed by accessing the first of the plurality of data blocks, (ii) at a conservative time slot, a next block sequential to a prior displayed data block is available for displaying, and (iii) repeating step (ii) until all of the plurality of data blocks for the data file has been displayed, and sending the plurality of data blocks based on the allocationg step.

Description: SYSTEMS AND METHODS FOR PROVIDING VIDEO-ON-DEMAND SERVICES FOR BROADCASTING SYSTEMS BRIEF DESCRIPTION OF THE INVENTION This invention relates generally to data-on-demand systems. In particular, this invention relates to video-on-demand systems. BACKGROUND OF THE INVENTION Video-on-demand (NOD) systems are one type of data-on-demand (DOD) systems. In NOD systems, video data files are provided by a server or a network of servers to one or more clients on a demand basis. In a conventional NOD architecture, a server or a network of servers communicates with clients in a standard hierarchical client-server model. For example, a client sends a request to a server for a data file (e.g., a video data file). In response to the client request, the server sends the requested data file to the client. In the standard client-server model, a client's request for a data file can be fulfilled by one or more servers. The client may have the capability to store any received data file locally in non- volatile memory for later use. The standard client-server model requires a two-way communications infrastructure. Currently, two-way communications require building new infrastructure because existing cables can only provide one-way communications. Example of two-way communications infrastructure are hybrid fiber optics coaxial cables (HFC) or all fiber iirfrastructure. Replacing existing cables is very costly and the resulting services may not be affordable by most users. In addition, the standard client-server model has many limitations when a service provider (e.g., a cable company) attempts to provide NOD services to a large number of clients. One limitation of the standard client-server model is that the service provider has to implement a mechanism to continuously listen and fulfill every request from each client within the network; thus, the number of clients who can receive service is dependent on the capacity of such a mechanism. One mechanism uses massively-parallel computers having large and fast disk arrays as local servers. However, even the fastest existing local server can only deliver video data streams to about 1000 to 2000 clients at one time. Thus, in order to service more clients, the number of local servers must increase. Increasing local servers requires more upper level servers to maintain control of the local servers. Another limitation of the standard client-server model is that each client requires its own bandwidth. Thus, the total required bandwidth is directly proportional to the number of subscribing clients. Cache memory within local servers has been used to improve bandwidth limitation but using cache memory does not solve the problem because cache memory is also limited. Presently, in order to make video-on-demand services more affordable for clients, existing service providers are increasing the ratio of clients per local server above the local server's capabilities. Typically, a local server, which is capable of providing service to 1000 clients, is actually committed to service 10,000 clients. This technique may work if most of the subscribing clients do not order videos at the same time. However, this technique is set up for failure because most clients are likely to want to view videos at the same time (i.e., evenings and weekends), thus, causing the local server to become overloaded. Thus, it is desirable to provide a system that is capable of providing on-demand services to a large number of clients over virtually any transmission medium without replacing existing infrastructure. SUMMARY OF THE INVENTION In an exemplary embodiment, at a server side, a method for sending data to a client to provide data-on-demand services comprises the steps of: receiving a data file, specifying a time interval, parsing the data file into a plurality of data blocks based on the time interval such that each data block is displayable during the time interval, determining a required number of time slots to send the data file, allocating to each time slot at least a first of the plurality of data blocks and optionally one or more additional data blocks, such that the plurality of data blocks is available in sequential order to a client accessing the data file during any time slot, and sending the plurality of data blocks based on the allocating step. In one embodiment, the parsing step includes the steps of: determining an estimated data block size, determining a cluster size of a memory in a channel server, and parsing the data file based on the estimated data block size and the cluster size. In another embodiment, the determining step includes the step of assessing resource allocation and bandwidth availability. In an exemplary embodiment, at a client side, a method for processing data received from a server to provide data-on-demand services comprises the steps of: (a) receiving a selection of a data file during a first time slot; (b) receiving at least one data block of the data file during a second time slot; (c) during a next time slot: receiving any data block not already received, sequentially displaying a data block of the data file, and repeating step (c) until all data blocks of the data file has been received and displayed. In one embodiment, the method for processing data received from a server is performed by a set-top box at the client side. In an exemplary embodiment, a data file is divided into a number of data blocks and a scheduling matrix is generated based on the number of data blocks. At the server side, the scheduling matrix provides a send order for sending the data blocks, such that a client can access the data blocks in sequential order at a random time. In an exemplary embodiment, a method for generating a scheduling matrix for a data file comprises the steps of: (a) receiving a number of data blocks [x] for a data file; (b) setting a first variable [j] to zero; (c) setting a second variable [i] to zero; (d) clearing all entries in a reference array; (e) writing at least one data block stored in matrix positions of a column [(i+j) modulo x] in a matrix to a reference array, if the reference array does not already contain the data block; (f) writing a data block [i] into the reference array and a matrix position [(i+j) modulo x, j] of the matrix, if the reference array does not contain the data block [i]; (g) incrementing the second variable [i] by one and repeating step (e) until the second variable [i] is equal to the number of data blocks [x]; and (h) incrementing the first variable [j] by one and repeating the step (c) until the first variable [j] is equal to the number of data blocks [x]. In one embodiment, a scheduling matrix is generated for each data file in a set of data files and a convolution method is applied to generate a delivery matrix based on the scheduling matrices for sending the set of data files. A data-on-demand system comprises a first set of channel servers, a central controlling server for controlling the first set of channel servers, a first set of up- converters coupled to the first set of channel servers, a combiner/amplifier coupled to the first set of up-converters, and a combiner/amplifier adapted to transmit data via a transmission medium. In an exemplary embodiment, the data-on-demand system further comprises a channel monitoring module for monitoring the system, a switch matrix, a second set of channel servers, and a second set of up-converters. The channel monitoring module is configured to report to the central controlling server when system failure occurs. The central controlling server, in response to report from the channel monitoring module, instructs the switch matrix to replace a defective channel server in the first set of channel servers with a channel server in the second set of channel servers and a defective up-converter in the first set of up-converters with an up-converter in the second set of up-converters. A method for providing data-on-demand services comprises the steps of calculating a delivery matrix of a data file, sending the data file in accordance with the delivery matrix, such that a large number of clients is capable of viewing the data file on demand. In one embodiment, the data file includes a video file. BRIEF DESCRIPTION OF THE DRAWINGS FIGURE 1 A illustrates an exemplary DOD system in accordance with an embodiment of the invention. FIGURE IB illustrates an exemplary DOD system in accordance with another embodiment of the invention. FIGURE 2 illustrates an exemplary channel server in accordance with an embodiment of the invention. FIGURE 3 illustrates an exemplary set-top box in accordance with an embodiment of the invention. FIGURE 4 illustrates an exemplary process for generating a scheduling matrix in accordance with an embodiment of the invention. DETAILED DESCRIPTION OF THE INVENTION Figure 1A illustrates an exemplary DOD system 100 in accordance with an embodiment of the invention. In this embodiment, the DOD system 100 provides data files, such as video files, on demand. However, the DOD system 100 is not limited to providing video files on demand but is also capable of providing other data files, for example, game files on demand. The DOD system 100 includes a central controlling server 102, a central storage 103, a plurality of channel servers 104a-104n, a plurality of up-converters 106a-106n , and a combiner/amplifier 108. The central controlling server 102 controls the channel servers 104. The central storage 103 stores data files in digital format. In an exemplary embodiment, data files stored in the central storage 103 is accessible via a standard network interface (e.g., ethernet connection) by any authorized computer, such as the central controlling server 102, connected to the network. Each channel server 104 is assigned to a channel and is coupled to an up-converter 106. The channel servers 104 provide data files that are retrieved from the central storage 103 in accordance with instructions from the central controlling server 102. The output of each channel server 104 is a quadrature amplitude modulation (QAM) modulated intermediate frequency (IF) signal having a suitable frequency for the corresponding up-converter 106. The QAM-modulated IF signals are dependent upon adopted standards. The current adopted standard in the United States is the data-over-cable-systems-interface-specification (DOCSIS) standard, which requires an approximately 43.75MHz IF frequency. The up- converters 106 convert IF signals received from the channel servers 104 to radio frequency signals (RF signals). The RF signals, which include frequency and bandwidth, are dependent on a desired channel and adopted standards. For example, under the current standard in the United States for a cable television channel 80, the RF signal has a frequency of approximately 559.25MHz and a bandwidth of approximately 6MHz. The outputs of the up-converters 106 are applied to the combiner/amplifier 108. The combiner/amplifier 108 amplifies, conditions, and combines the received RF signals then outputs the signals out to a transmission medium 110. In an exemplary embodiment, the central controlling server 102 includes a graphics user interface (not shown) to enable a service provider to schedule data delivery by a drag-and-drop operation. Further, the central controlling server 102 authenticates and controls the channel servers 104 to start or stop according to delivery matrices. In an exemplary embodiment, the central controlling server 102 automatically selects a channel and calculates delivery matrices for transmitting data files in the selected channel. The central controlling server 102 provides offline addition, deletion, and update of data file information (e.g., duration, category, rating, and/or brief description). Further, the central controlling server 102 controls the central storage 103 by updating data files and databases stored therein. In an exemplary embodiment, an existing cable television system 120 may continue to feed signals into the combiner/amplifier 108 to provide non-DOD services to clients. Thus, the DOD system 100 in accordance with the invention does not disrupt present cable television services. Figure IB illustrates another exemplary embodiment of the DOD system 100 in accordance with the invention. In addition to the elements illustrated in Figure 1 A, the DOD system 100 includes a switch matrix 112, a channel monitoring module 114, a set of back-up channel servers 116a-l 16b, and a set of back-up up-converters 118a- 118b. In one embodiment, the switch matrix 112 is physically located between the up- converters 106 and the combiner/amplifier 108. The switch matrix 112 is controlled by the central controlling server 102. The channel monitoring module 114 comprises a plurality of configured set-top boxes, which simulate potential clients, for monitoring the health of the DOD system 100. Monitoring results are communicated by the channel monitoring module 114 to the central controlling server 102. In case of a channel failure (i.e., a channel server failure, an up-converter failure, or a communication link failure), the central controlling server 102 through the switch matrix 112 disengages the malfunctioning component and engages a healthy backup component 116 and/or 118 to resume service. In an exemplary embodiment, data files being broadcasted from the DOD system 100 are contained in motion pictures expert group (MPEG) files. Each MPEG file is dynamically divided into data blocks and sub-blocks mapping to a particular portion of a data file along a time axis. These data blocks and sub-blocks are sent during a pre-determined time in accordance with three-dimensional delivery matrices provided by the central controlling server 102. A feedback channel is not necessary for the DOD system 100 to provide DOD services. However, if a feedback channel is available, the feedback channel can be used for other purpose, such as billing or providing Internet services. Figure 2 illustrates an exemplary channel server 104 in accordance with an embodiment of the invention. The channel server 104 comprises a server controller 202, a CPU 204, a QAM modulator 206, a local memory 208, and a network interface 210. The server controller 202 controls the overall operation of the channel server 104 by instructing the CPU 204 to divide data files into blocks (further into sub-blocks and data packets), select data blocks for transmission in accordance with a delivery matrix provided by the central controlling server 102, encode selected data, compress encoded data, then deliver compressed data to the QAM modulator 206. The QAM modulator 206 receives data to be transmitted via a bus (i.e., PCI, CPU local bus) or Ethernet connections. In an exemplary embodiment, the QAM modulator 206 may include a downstream QAM modulator, an upstream quadrature amplitude modulation /quadrature phase shift keying (QAM/QPSK) burst demodulator with forward error correction decoder, and/or an upstream tuner. The output of the QAM modulator 206 is an IF signal that can be applied directly to an up-converter 106. The network interface 210 connects the channel server 104 to other channel servers 104 and to the central controlling server 102 to execute the scheduling and controlling instructions from the central controlling server 102, reporting status back to the central controlling server 102, and receiving data files from the cental storage 103. Any data file retrieved from the central storage 103 can be stored in the local memory 208 of the channel server 104 before the data file is processed in accordance with instructions from the server controller 202. In an exemplary embodiment, the channel server 104 may send one or more DOD data streams depending on the bandwidth of a cable channel (e.g., 6, 6.5, or 8MHz), QAM modulation (e.g., QAM 64 or QAM 256), and a compression standard/bit rate of the DOD data stream (i.e., MPEG-l or MPEG-2). Figure 3 illustrates an exemplary set-top box (STB) 300 in accordance with an embodiment of the invention. The STB 300 comprises a QAM demodulator 302, a CPU 304, a conditional access module 306 (e.g., a smart card system), a local memory 308, a buffer memory 309, a STB controller 310, a decoder 312, and a graphics overlay module 314. The STB controller 310 controls the overall operation of the STB 300 by controlling the CPU 302 and the QAM demodulator 302 to select data in response to a client's request, decode selected data, decompress decoded data, reassemble decoded data, store decoded data in the local memory 308 or the buffer memory 309, and deliver stored data to the decoder 312. In an exemplary embodiment, the STB controller 310 controls the overall operation of the STB 300 based on data packet headers in the data packets received from the transmission medium 110. In an exemplary embodiment, the local memory 308 comprises nonvolatile memory (e.g., a hard drive) and the buffer memory 309 comprises volatile memory. In one embodiment, the QAM demodulator 302 comprises transmitter and receiver modules and one or more of the following: privacy encryption/decryption module, forward error correction decoder/encoder, tuner control, downstream and upstream processor, CPU and memory interface circuits. The QAM demodulator 302 receives modulated IF signals, samples and demodulates the signals to restore data. The conditional access module 306 permits a decoding process when access is granted after authentication and/or when appropriate fees have been charged. Access condition is determined by the service provider. In an exemplary embodiment, when access is granted, the decoder 312 decodes at least one data block to transform the data block into images displayable on an output screen. The decoder 312 supports commands from a subscribing client, such as play, stop, pause, step, rewind, forward, etc. The graphics overlay module 314 enhances displayed graphics quality by, for example, providing alpha blending or picture-in-picture capabilities. In an exemplary embodiment, the graphics overlay module 314 can be used for graphics acceleration during game playing mode, for example, when the service provider provides games- on-demand services using the system in accordance with the invention. In an exemplary embodiment, although data files are broadcasted to all cable television subscribers, only the DOD subscriber who has a compatible STB 300 will be able to decode and enjoy data-on-demand services. In one exemplary embodiment, permission to obtain data files on demand can be obtained via a smart card system in the conditional access control module 306. A smart card may be rechargeable at a local store or vending machine set up by a service provider. In another exemplary embodiment, a flat fee system provides a subscriber an unlimited access to all available data files. In an exemplary embodiment, data-on-demand interactive features permit a client to select at any time an available data file. The amount of time between when a client presses a select button and the time the selected data file begins playing is referred to as a response time. As more resources are allocated (e.g., bandwidth, server capability) to provide DOD services, the response time gets shorter. In an exemplary embodiment, a response time can be determined based on an evaluation of resource allocation and desired quality of service. In an exemplary embodiment, a selected response time determines the duration of a time slot. The duration of a time slot (TS) is the time interval for playing a data block at normal speed by a client. In an exemplary embodiment, a data file, such as a video file, is divided into a number of data blocks such that each data block can support the playing of the data file for the duration of a time slot. In one embodiment, the number of data blocks (NUM_OF_BLKS) for each data file can be calculated as follows: Estimated_BLK_Size = (DataFile_Size * TS) / DataFileJLength (1) BLK SIZE = (Estimated BLK Size + CLUSTER_SIZE - lByte) / CLUSTER _SIZE (2) BLK_SIZE_BYTES = BLK_SIZE * CLUSTER_SIZE (3) NUM _OF_BLKS =(DataFile_Size + BLK_SIZE_BYTES - lByte) / BLK_SIZE_BYTES (4) In equations (1) to (4), the Estimated_BLK_Size is an estimated block size (in Bytes); the DataFile Size is the data file size (in Bytes); TS represents the duration of a time slot (in seconds); DataFile_Length is the duration of the data file (in seconds); BLK SIZE is the number of clusters needed for each data block; CLUSTER SIZE is the size of a cluster in the local memory 208 for each channel server 104 (e.g., 64KBytes); BLK_SIZE_BYTES is a block size in Bytes. In this embodiment, the number of blocks (NUM_OF_BLKS) is equal to the data file size (in Bytes) plus a data block size in Bytes minus 1 Byte and divided by a data block size in Bytes. Equations (1) to (4) illustrate one specific embodiment. A person of skill in the art would recognize that other methods are available to calculate a number of data blocks for a data file. For example, dividing a data file into a number of data blocks is primarily a function of an estimated block size and the cluster size of the local memory 208 of a channel server 104. Thus, the invention should not be limited to the specific embodiment presented above. Figure 4 illustrates an exemplary process for generating a scheduling matrix for sending a data file in accordance with an embodiment of the invention. In an exemplary embodiment, this invention uses time division multiplexing (TDM) and frequency division multiplexing (FDM) technology to compress and schedule data delivery at the server side. In an exemplary embodiment, a scheduling matrix is generated for each data file. In one embodiment, each data file is divided into a number of data blocks and the scheduling matrix is generated based on the number of data blocks. Typically, a scheduling matrix provides a send order for sending data blocks of a data file from a server to clients, such that the data blocks are accessible in sequential order by any client who wishes to access the data file at a random time. At step 402, a number of data blocks (x) for a data file is received. A first variable, j, is set to zero (step 404). A reference array is cleared (step 406). The reference array keeps track of data blocks for internal management purposes. Next, j is compared to x (step 408). If j is less than x, a second variable, i, is set to zero (step 412). Next, i is compared to x (step 414). If i is less than x, data blocks stored in the column [(i+j) modulo (x)] of a scheduling matrix are written into the reference array (step 418). If the reference array already has such data block(s), do not write a duplicate copy. Initially, since the scheduling matrix does not yet have entries, this step can be skipped. Next, the reference array is checked if it contains data block i (step 420). Initially, since all entries in the reference array has been cleared at step 406, there would be nothing in the reference array. If the reference array does not contain data block i, data block i is added into the scheduling matrix at matrix position [(i+j) modulo (x), j] and the reference array (step 422). After the data block i is added to the scheduling matrix and the reference array, i is incremented by 1, such that i - i + 1 (step 424), then the process repeats at step 414 until i = x. If the reference array contains data block i, i is incremented by 1, such that i = i + 1 (step 424), then the process repeats at step 414 until i = x. When i = x, j is incremented by 1, such that j = j + 1 (step 416) and the process repeats at step 406 until j = x. The entire process ends when j = x (step 410). In an exemplary embodiment, if a data file is divided into six data blocks (x = 6), the scheduling matrix and the reference arrays are as follows: Scheduling Matrix (SM) Appendix A attached to this application describes a step-by-step process of the exemplary process illustrated in Figure 4 to generate the above scheduling matrix and reference arrays. In this exemplary embodiment, based on the scheduling matrix above, the six data blocks of the data file are sent in the following sequence: TSO => blkO TS1 => blk0, blkl, blk3 TS2 => blkO, blk2 TS3 => blkO, blkl , blk3, blk4 TS4 => blkO, blk4 TS5 => blkO, blkl , blk2, blk5 In another exemplary embodiment, a look-ahead process can be used to calculate a look-ahead scheduling matrix to send a predetermined number of data blocks of a data file prior to a predicted access time. For example, if a predetermined look-ahead time is the duration of one time slot, for any time slot greater than or equal to time slot number four, data block 4 (blk4) of a data file should be received by a STB 300 at a subscribing client at or before TS3, but blk4 would not be played until TS4. The process steps for generating a look-ahead scheduling matrix is substantially similar to the process steps described above for Figure 4 except that the look-ahead scheduling matrix in this embodiment schedules an earlier sending sequence based on a look-ahead time. Assuming a data file is divided into six data blocks, an exemplary sending sequence based on a look-ahead scheduling matrix, having a look-ahead time of the duration of two time slots, can be represented as follows: TSO => blk0 TS1 => blk0, blkl, blk3, blk4 TS2 => blk0, blk2 TS3 => blkO, blkl , blk3, blk4, blk5 TS4 => blkO, blk5 TS5 => blkO, blkl, blk2 A three-dimensional delivery matrix for sending a set of data files is generated based on the scheduling matrices for each data file of the set of data files. In the three- dimensional delivery matrix, a third dimension containing IDs for each data file in the set of data files is generated. The three-dimensional delivery matrix is calculated to efficiently utilize available bandwidth in each channel to deliver multiple data streams. In an exemplary embodiment, a convolution method, which is well known in the art, is used to generate a three-dimensional delivery matrix to schedule an efficient delivery of a set of data files. For example, a convolution method may include the following policies: (1) the total number of data blocks sent in the duration of any time slot (TS) should be kept at a smallest possible number; and (2) if multiple partial solutions are available with respect to policy (1), the preferred solution is the one which has a smallest sum of data blocks by adding the data blocks to be sent during the duration of any reference time slot, data blocks to be sent during the duration of a previous time slot (with respect to the reference time slot), and data blocks to be sent during the duration of a next time slot (with respect to the reference time slot). For example, assuming an exemplary system sending two short data files, M and N, where each data file is divided into six data blocks, the sending sequence based on a scheduling matrix is as follows: TSO => blkO TS1 => blk0, blkl, blk3 TS2 => blk0, blk2 TS3 => blkO, blkl , blk3, blk4 TS4 => blkO, blk4 TS5 => blkO, blkl , blk2, blk5 Applying the exemplary convolution method as described above, possible combinations of delivery matrices are as follows: Option 1 : Send video file N at shift 0 TS Total Data Blocks TSO => M0, N0 TS1 => M0, M1, M3, N0, N1, N3 TS2 => MO, M2, NO, N2 TS3 => M0, M1, M3, M4, N0, N1, N3, N4 TS4 => MO, M4, NO, N4 TS5 => M0, M1, M2, M5, N0, N1, N2, N5 Option 2: Send video file N at shift 1 TS Total Data Blocks TSO =>M0,N0,N1,N3 4 TS1 =>M0,M1,M3,N0,N2 5 TS2 => MO, M2, NO, NI, N3, N4 6 TS3 =>M0,M1,M3,M4,N0,N4 6 TS4 =>M0,M4,N0,N1,N2,N5 6 TS5 =>M0,M1,M2,M5,N0 5 Option 3 : Send video file N at shift 2 TS Total Data Blocks TSO =>M0,N0,N2 3 TS1 =>M0,M1,M3,N0,N1,N3,N4 7 TS2 => MO, M2, NO, N4 4 TS3 =>M0,M1,M3,M4,N0,N1,N2,N5 8 TS4 => MO, M4, NO 3 TS5 =>M0,M1,M2,M5,N0,N1,N3 7 Option 4: Send video file N at shift 3 TS Total Data Blocks TSO =>M0,N0,N1,N3,N4 5 TS1 =>M0,M1,M3,N0,N4 5 TS2 =>M0,M2,N0,N1,N2,N5 6 TS3 => MO, Ml, M3, M4, NO 5 TS4 => MO, M4, NO, NI, N3 5 TS5 =>M0,M1,M2,M5,N0,N2 6 Option 5 : Send video file N at shift 4 TS Total Data Blocks TSO =>M0,N0,N4 3 TS1 =>M0,M1,M3,N0,N1,N2,N5 7 TS2 =>M0,M2,N0 3 TS3 =>M0,M1,M3,M4,N0,N1,N3 7 TS4 => MO, M4, NO, N2 4 TS5 =>M0,M1,M2,M5,N0,N1,N3,N4 8 Option 6: Send video file N at shift 5 TS Total Data Blocks TSO => MO, NO, NI, N2, N5 TS1 => MO, Ml, M3. N0 4 TS2 => MO, M2, NO, N 1 , N3 5 TS3 => MO, Ml, M3, M4, NO, N2 6 TS4 => M0, M4, N0, N1, N3, N4 6 TS5 => M0, M1, M2, M5, N0, N4 6 Applying policy (1), options 2, 4, and 6 have the smallest maximum number of data blocks (i.e., 6 data blocks) sent during any time slot. Applying policy (2), the optimal delivery matrix in this exemplary embodiment is option 4 because option 4 has the smallest sum of data blocks of any reference time slot plus data blocks of neighboring time slots (i.e., 16 data blocks). Thus, optimally for this embodiment, the sending sequence of the data file N should be shifted by three time slots. In an exemplary embodiment, a three-dimensional delivery matrix is generated for each channel server 104. When data blocks for each data file are sent in accordance with a delivery matrix, a large number of subscribing clients can access the data file at a random time and the appropriate data blocks of the data file will be timely available to each subscribing client. In the example provided above, assume the duration of a time slot is equal to 5 seconds, the DOD system 100 sends data blocks for data files M and N in accordance with the optimal delivery matrix (i.e., shift delivery sequence of data file N by three time slots) in the following manner: Time 00:00:00=> M0 NO NI N3 N4 Time 00:00:05 => M0 M1 M3 N0 N4 Time 00:00: 10=> M0 M2 N0 NI N2 N5 Time 00:00:15=> M0 Ml M3 M4 N0 Time 00:00:20=> M0 M4 NO NI N3 Time 00:00:25-> M0 Ml M2 M5 NO N2 Time 00:00:30=> M0 N0N1 N3 N4 Time 00:00:35 -> M0 Ml M3 NO N4 Time 00:00:40=> M0 M2 NO NI N2 N5 Time 00:00:45 => M0 Ml M3 M4 N0 Time 00:00:50=> M0 M4 NO NI N3 Time 00:00:55=> M0 Ml M2 M5 NO N2 If at time 00:00:00 a client A selects movie M, the STB 300 at client A receives, stores, plays, and rejects data blocks as follows: Time 00:00:00 => Receive M0 => play MO, store MO. Time 00:00:05 => Receive Ml, M3 => play Ml, store MO, Ml, M3. Time 00:00:10 => Receive M2 => play M2, store M0, Ml, M2 M3. Time 00:00: 15 => Receive M4 => play M3, store M0, Ml, M2, M3, M4. Time 00:00:20 => Receive none => play M4, store M0, Ml, M2, M3, M4. Time 00:00:25 => Receive M5 => play M5, store M0, Ml, M2, M3, M4, M5. If at time 00:00:10, a client B selects movie M, the STB 300 at client B receives, stores, plays, and rejects data blocks as follows: Time 00:00:10 => Rcv M0, M2 => play M0, store M0, M2. Time 00:00:15 => Rev Ml, M3, M4 => play Ml, store M0, Ml, M2, M3, M4. Time 00:00:20 => Rev none => play M2, store M0, Ml, M2, M3, M4. Time 00:00:25 => Rev M5 => play M3, store M0, Ml, M2, M3, M4, M5. Time 00:00:30 => Rev none => play M4, store M0, Ml, M2, M3, M4, M5. Time 00:00:35=> Rev none => play M5, store M0, Ml, M2, M3, M4, M5. If at time 00:00:15, a client C selects movie N, the STB 300 of the client C receives, stores, plays, and rejects data blocks as follows: Time 00:00:15 => Rcv N0 => play NO, store NO. Time 00:00:20 => Rcv Nl N3 => play NI, store NO, N1, N3. Time 00:00:25 => Rev N2 => play N2, store NO, NI , N2, N3. Time 00:00:30 => Rcv N4 => play N3, store NO, N1, N2, N3, N4. Time 00:00:35 => Rev none => play N4, store NO, NI, N2, N3, N4. Time 00:00:40 => Rcv N5 => play N5, store NO, N1, N2, N3, N4, N5. If at time 00:00:30, a client D also selects movie N, the STB 300 at the client D receives, stores, plays, and rejects data blocks as follows: Time 00:00:30 => Rev NO, NI , N3, N4 => play NO, store NO, NI , N3, N4. Time 00:00:35 => Rev none => play NI , store NO, NI , N3, N4. Time 00:00:40 => Rev N2, N5 => play N2, store NO, NI, N2, N3, N4, N5. Time 00:00:45 => Rev none => play N3, store NO, NI , N2, N3, N4, N5. Time 00:00:50 => Rev none => play N4, store NO, N1, N2, N3, N4, N5. Time 00:00:55 => Rev none => play N5, store NO, NI , N2, N3, N4, N5. As shown in the above examples, any combination of clients can at a random time independently select and begin playing any data file provided by the service provider. GENERAL OPERATION A service provider can schedule to send a number of data files (e.g., video files) to channel servers 104 prior to broadcasting. The central controlling server 102 calculates and sends to the channel servers 104 three-dimensional delivery matrices (ID, time slot, and data block send order). During broadcasting, channel servers 104 consult the three-dimensional delivery matrices to send appropriate data blocks in an appropriate order. Each data file is divided into data blocks so that a large number of subscribing clients can separately begin viewing a data file continuously and sequentially at a random time. The size of a data block of a data file is dependent on the duration of a selected time slot and the bit rate of the data stream of the data file. For example, in a constant bit rate MPEG data stream, each data block has a fixed size of: Block Size (MBytes) = BitRate (Mb/s) x TS (sec) / 8 (1). In an exemplary embodiment, a data block size is adjusted to a next higher multiple of a memory cluster size in the local memory 208 of a channel server 104. For example, if a calculated data block length is 720Kbytes according to equation (1) above, then the resulting data block length should be 768Kbytes if the cluster size of the local memory 208 is 64Kbytes. In this embodiment, data blocks should be further divided into multiples of sub-blocks each having the same size as the cluster size. In this example, the data block has twelve sub-blocks of 64KBytes. A sub-block can be further broken down into data packets. Each data packet contains a packet header and packet data. The packet data length depends on the maximum transfer unit (MTU) of a physical layer where each channel server's CPU sends data to. In the preferred embodiment, the total size of the packet header and packet data should be less than the MTU. However, for maximum efficiency, the packet data length should be as long as possible. In an exemplary embodiment, data in a packet header contains information that permits the subscriber client's STB 300 to decode any received data and determine if the data packet belongs to a selected data file (e.g., protocol signature, version, ID, or packet type information). The packet header may also contain other information, such as block/sub-block/packet number, packet length, cyclic redundancy check (CRC) and offset in a sub-block, and/or encoding information. Once received by a channel server 104, data packets are sent to the QAM modulator 206 where another header is added to the data packet to generate a QAM- modulated IF output signal. The maximum bit rate output for the QAM modulator 206 is dependent on available bandwidth. For example, for a QAM modulator 206 with 6MHz bandwidth, the maximum bit rate is 5.05 (bit/symbol) x 6 (MHz) = 30.3 Mbit/sec. The QAM-modulated IF signals are sent to the up-converters 106 to be converted to RF signals suitable for a specific channel (e.g., for CATV channel 80, 559.250MHz and 6MHz bandwidth). For example, if a cable network has high bandwidth (or bit rate), each channel can be used to provide more than one data stream, with each data stream occupying a virtual sub-channel. For example, three MPEG1 data streams can fit into a 6MHz channel using QAM modulation. The output of the up-converters 106 is applied to the combiner/amplifier 108, which sends the combined signal to the transmission medium 110. In an exemplary embodiment, the total system bandwidth (BW) for transmitting "N" data streams is BW = N x bw, where bw is the required bandwidth per data stream. For example, three MPEG-1 data streams can be transmitted at the same time by a DOCSIS cable channel having a system bandwidth of 30.3 Mbits/sec because each MPEG-1 data stream occupies 9 Mbits/sec of the system bandwidth. Typically, bandwidth is consumed regardless of the number of subscribing clients actually accessing the DOD service. Thus, even if no subscribing client is using the DOD service, bandwidth is still consumed to ensure the on-demand capability of the system. The STB 300, once turned on, continuously receives and updates a program guide stored in the local memory 308 of a STB 300. In an exemplary embodiment, the STB 300 displays data file information including the latest program guide on a TV screen. Data file information, such as video file information, may include movielD, movie title, description (in multiple languages), category (e.g., action, children), rating (e.g., R, PG13), cable company policy (e.g., price, length of free preview), subscription period, movie poster, and movie preview. In an exemplary embodiment, data file information is sent via a reserved physical channel, such as a channel reserved for firmware update, commercials, and/or emergency information. In another exemplary embodiment, information is sent in a physical channel shared by other data streams. A subscribing client can view a list of available data files arranged by categories displayed on a television screen. When the client selects one of the available data files, the STB 300 controls its hardware to tune into a corresponding physical channel and/or a virtual sub-channel to start receiving data packets for that data file. The STB 300 examines every data packet header, decodes data in the data packets, and determines if a received data packet should be retained. If the STB 300 determines that a data packet should not be retained, the data packet is discarded. Otherwise, the packet data is saved in the local memory 308 for later retrieval or is temporarily stored in the buffer memory 309 until it is sent to the decoder 312. To improve performance efficiency by avoiding frequent read/write into the local memory 308, in an exemplary embodiment, the STB 300 uses a "sliding window" anticipation technique to lock anticipated data blocks in the memory buffer 309 whenever possible. Data blocks are transferred to the decoder 312 directly out of the memory buffer 309 if a hit in an anticipation window occurs. If an anticipation miss occurs, data blocks are read from the local memory 308 into the memory buffer 309 before the data blocks are transferred to the decoder 312 from the memory buffer 309. In an exemplary embodiment, the STB 300 responds to subscribing client's commands via infrared (IR) remote control unit buttons, an IR keyboard, or front panel pushbuttons, including buttons to pause, play in slow motion, rewind, zoom and single step. In an exemplary embodiment, if a subscribing client does not input any action for a predetermined period of time (e.g., scrolling program menu, or selecting a category or movie), a scheduled commercial is played automatically. The scheduled commercial is automatically stopped when the subscribing client provides an action (e.g., press a button in a remote control unit). In another exemplary embodiment, the STB 300 can automatically insert commercials while a video is being played. The service provider (e.g., a cable company) can set up a pricing policy that dictates how frequently commercials should interrupt the video being played. If an emergency information bit is found in a data packet header, the STB 300 pauses any data receiving operation and controls its hardware to tune into the channel reserved for receiving data file information to obtain and decode any emergency information to be displayed on an output screen. In an exemplary embodiment, when the STB 300 is idled, it is tuned to the channel reserved for receiving data file information and is always ready to receive and display any emergency information without delay. The foregoing examples illustrate certain exemplary embodiments of the invention from which other embodiments, variations, and modifications will be apparent to those skilled in the art. The invention should therefore not be limited to the particular embodiments discussed above, but rather is defined by the following claims. APPENDIX A SYSTEMS AND METHODS FOR PROVIDING VIDEO-ON-DEMAND SERVICES FOR BROADCASTING SYSTEMS The following is a step-by-step description of the exemplary process illustrated in Figure 4 for generating a scheduling matrix for a data file having six data blocks: START (Step 402) Receive a number of data blocks for a data file (x); assume the number of data blocks is equal to 6 (x = 6). (Step 404) Setj = 0 (Step 406) Clear a Reference Array (RA) (Step 408) Compare j to x. (Step 412) j is less than x (0<6), let i = 0 (Step 414) Compare i to x. (Step 418) i is less than x (0<6). Read matrix positions of column [0] in the SM and write to RA; initially, the SM is empty so nothing is written into RA. (Step 420) Does RA contain data block i or blkO? (Step 422) RA does not contain anything because it is empty. Write blkO into position [0, 0] in SM and the RA. (Step 424) Add 1 to i (i=l) to derive value for position [1, 0]. Go back to Step 414. (Step 414) Compare i to x. (Step 418) i is less than x (1<6). Read matrix positions of column [1] in the SM and write to RA; initially, the SM is empty so nothing is written into RA. (Step 420) Does RA contain data block i or blkl? (Step 422) RA does not contain blkl. Write blkl into position [1, 0] in SM and the RA. (Step 424) Add 1 to i (i=2) to derive value for position [2, 0]. Go back to Step 414. (Step 414) Compare i to x. (Step 418) i is less than x (2<6). Read matrix positions of column [2] in the SM and write to RA; initially, the SM is empty so nothing is written into RA. (Step 420) Does RA contain data block i or blk2? (Step 422) RA does not contain blk2. Write blk2 into position [2, 0] in SM and the RA. (Step 424) Add 1 to i (i=3) to derive value for position [3, 0]. Go back to Step 414. (Step 414) Compare i to x. (Step 418) i is less than x (3<6). Read matrix positions of column [3] in the SM and write to RA; initially, the SM is empty so nothing is written into RA. (Step 420) Does RA contain data block i or blk3? (Step 422) RA does not contain blk3. Write blk3 into position [3, 0] in SM and the RA. (Step 424) Add 1 to i (i=4) to derive value for position [4, 0]. Go back to Step 414. (Step 414) Compare i to x. (Step 418) i is less than x (4<6). Read matrix positions of column [4] of the SM and write to RA; initially, the SM is empty so nothing is written into RA. (Step 420) Does RA contain data block i or blk4? (Step 422) RA does not contain blk4. Write blk4 into position [4, 0] in SM and the RA. (Step 424) Add 1 to i (i=5) to derive value for position [5, 0]. Go back to Step 414. (Step 414) Compare i to x. 22 (Step 418) i is less than x (5<6). Read matrix positions of column [5] of the SM and write to RA; initially, the SM is empty so nothing is written into RA. (Step 420) Does RA contain data block i or blk5? (Step 422) RA does not contain blk5. Write blk5 into position [5, 0]-in SM and the RA. (Step 424) Add 1 to i (i=6). Go back to Step 414. (Step 414) Compare i to x. (Step 416) i is equal to x (6=6). Increment j by 1 (j=l). Go to Step 406. (Step 406) Clear a Reference Array (RA) (Step 408) Compare j to x. (Step 412) j is less than x (1<6), let i = 0. (Step 414) Compare i to x. (Step 418) i is less than x (0<6). Read matrix positions of column [1] in the SM and write to RA. Position [1, 0] contains blk 1 ; thus, blk 1 is written into RA. All other positions are empty. (Step 420) Does RA contain data block i or blkO? (Step 422) RA does not contain blkO. Write blkO into position [1, 1] in the SM and the RA. RA now has blkl and blk 0. (Step 424) Add 1 to i (i=l)to derive value for position [2, 1]. Go back to Step 414. (Step 414) Compare i to x. (Step 418) i is less than x (1<6). Read matrix positions of column [2] in the SM and write to RA. Position [2, 0] contains blk 2. All other positions are empty. RA now has blkl, blk 0, and blk 2. (Step 420) Does RA contain data block i or blkl? (Step 424) RA contains blkl. Thus, nothing is written into position [2, 1]. Add 1 to i (i=2) to derive value for position [3, 1]. Go back to Step 414. (Step 414) Compare i to x. (Step 418) i is less than x (2<6). Read matrix positions in column [3] of the SM and write to RA. Position [3, 0] contains blk3. All other positions are empty. RA now has blkl, blkO, blk2, and blk3. (Step 420) Does RA contain data block i or blk2? (Step 424) RA does contain blk2. Thus, nothing is written into position [3, 1]. Add 1 to i (i=3) to derive value for position [4, 1]. Go back to Step 414. (Step 414) Compare i to x. (Step 418) i is less than x (3<6). Read matrix positions of column [4] in the SM and write to RA. Position [4, 0] contains blk4. All other positions are empty. RA now has blkl, blkO, blk2, blk3, and blk4. (Step 420) Does RA contain data block i or blk3? (Step 424) RA does contain blk3. Thus, nothing is written into position [4, 1]. Add 1 to i (i=4) to derive value for position [5, 1]. Go back to Step 414. (Step 414) Compare i to x. (Step 418) i is less than x (4<6). Read matrix positions of column [5] in the SM and write to RA. Position [5, 0] contains blk5. All other positions are empty. RA now has blkl, blkO, blk2, blk3, blk4, and blk5. (Step 420) Does RA contain data block i or blk4? (Step 424) RA does contain blk4. Thus, nothing is written into position [5, 1]. Add 1 to i (i=5) to derive value for position [0, 1]. Go back to Step 414. 23 (Step 414) Compare i to x. (Step 418) i is less than x (5<6). Read matrix positions of column [0] in the SM and write to RA. Position [0, 0] contains blkO. All other positions are empty. RA already contains blkO; thus, blkO is discarded. (Step 420) Does RA contain data block i or blk5? (Step 424) RA does contain blk5. Thus, nothing is written into position [0, 1]. Add 1 to i (i=6). Go back to Step 414. (Step 414) Compare i to x. (Step 416) i is equal to x (6=6). Increment j by 1 ( =2). Go to Step 406. (Step 406) Clear a Reference Array (RA) (Step 408) Compare j to x. (Step 412) j is less than x (2<6), let i = 0. (Step 414) Compare i to x. (Step 418) i is less than x (0<6). Read matrix positions of column [2] in the SM and write to RA. Position [2, 0] contains blk 2. All other positions are empty. RA nowhas blk2. (Step 420) Does RA contain data block i or blkO? (Step 422) RA does not contain blkO. Write blkO into position [2, 2] in the SM and the RA. RA now has blk2 and blk 0. (Step 424) Add 1 to i (i=l) to derive value for position [3, 2]. Go back to Step 414. (Step 414) Compare i to x. (Step 418) i is less than x (1<6). Read matrix positions of column [3] in the SM and write to RA. Position [3, 0] contains blk3. All other positions are empty. RA now has blk2, blk 0, and blk 3. (Step 420) Does RA contain data block i or blkl? (Step 422) RA not contain blkl . Write blkl into position [3, 2] in the SM and the RA. RA now has blk2, blkO, blk3, and blkl. (Step 424) Add 1 to i (i=2) to derive value for position [4, 2]. Go back to Step 414. (Step 414) Compare i to x. (Step 418) i is less than x (2<6). Read matrix positions of column [4] in the SM and write to RA. Position [4, 0] contains blk4. All other positions are empty. RA now has blk2, blkO, blk3, blkl, and blk4. (Step 420) Does RA contain data block i or blk2? (Step 424) RA does contain blk2. Thus, nothing is written into position [4, 2]. Add 1 to i (i=3)to derive value for position [5, 2]. Go back to Step 414. (Step 414) Compare i to x. (Step 418) i is less than x (3<6). Read matrix positions of column [5] in the SM and write to RA. Position [5, 0] contains blk5. All other positions are empty. RA now has blk2, blkO, blk3, blkl, blk4, and blk5. (Step 420) Does RA contain data block i or blk3? (Step 424) RA does contain blk3. Thus, nothing is written into position [5, 2]. Add 1 to i (i=4) to derive value for position [0, 2]. Go back to Step 414. (Step 414) Compare i to x. (Step 418) i is less than x (4<6). Read matrix positions of column [0] in the SM and write to RA. Position [0, 0] contains blkO. All other positions are empty. RA already contain blkO; thus, blkO is discarded. (Step 420) Does RA contain data block i or blk4? 24 (Step 424) RA does contain blk4. Thus, nothing is written into position [0, 2], Add 1 to i (i=5) to derive value for position [1, 2]. Go back to Step 414. (Step 414) Compare i to x. (Step 418) i is less than x (5<6). Read matrix positions of column [1] in the SM and write to RA. Position [1, 0] contains blkl and position [1, 1] contains blkO. RA already contains blkl and blkO; thus, blkl and blkO are discarded. All other positions are empty. (Step 420) Does RA contain data block i or blk5? (Step 424) RA does contain blk5. Thus, nothing is written into position [1, 2]. Add 1 to i (i=6). Go back to Step 414. (Step 414) Compare i to x. (Step 416) i is equal to x (6=6). Increment j by 1 (j = 3). Go to Step 406. (Step 406) Clear a Reference Array (RA) (Step 408) Compare j to x. (Step 412) j is less than x (3<6), let i = 0. (Step 414) Compare i to x. (Step 418) i is less than x (0<6). Read matrix positions of column [3] in the SM and write to RA. Position [3, 0] contains blk3 and position [3, 2] contains blkl. Blk3 and blkl are written into RA. All other positions are empty. (Step 420) Does RA contain data block i or blkO? (Step 422) RA does not contain blkO. Write blkO into position [3, 3] in the SM and the RA. RA now has blk3, blkl, and blkO. (Step 424) Add 1 to i (i=l) to derive value for position [4, 3]. Go back to Step 414. (Step 414) Compare i to x. (Step 418) i is less than x (1<6). Read matrix positions of column [4] in the SM and write to RA. Position [4, 0] contains blk 4. All other positions are empty. RA now has blk3, blk 1, blk 0 and blk 4. (Step 420) Does RA contain data block i or blkl ? (Step 424) RA contains blkl . Thus, nothing is written into position [4, 3]. Add 1 to i (i=2) to derive value for position [5, 3]. Go back to Step 414. (Step 414) Compare i to x. (Step 418) i is less than x (2<6). Read matrix positions of column [5] in the SM and write to RA. Position [5, 0] contains blk5. All other positions are empty. RA now has blk3, blkl, blk0, blk4, and blk5. (Step 420) Does RA contain data block i or blk2? (Step 422) RA does not contain blk2. Write blk2 into position [5, 3] in the SM and the RA. RA now has blk3, blkl, blkO, blk4, blk5, and blk2. (Step 424) Add 1 to i (i=3) to derive value for position [0, 3]. Go back to Step 414. (Step 414) Compare i to x. (Step 418) i is less than x (3<6). Read matrix positions of column [0] in the SM and write to RA. Position [0, 0] contains blkO. All other positions are empty. RA already contains blkO; thus, discard blkO. (Step 420) Does RA contain data block i or blk3? (Step 424) RA does contain blk3. Thus, nothing is written into position [0, 3]. Add 1 to i (i=4) to derive value for position [1, 3]. Go back to Step 414. (Step 414) Compare i to x. 25 (Step 418) i is less than x (4<6). Read matrix positions of column [1] in the SM and write to RA. Position [1, 0] contains blkl and position [1, 1] contains blkO. All other positions are empty. RA already contains blk 1 and blkO; do not write a duplicate copy. (Step 420) Does RA contain data block i or blk4? (Step 424) RA does contain blk4. Thus, nothing is written into position [1, 3]. Add 1 to i (i=5) to derive value for position [2, 3]. Go back to Step 414. (Step 414) Compare i to x. (Step 418) i is less than x (5<6). Read matrix positions of column [2] in the SM and write to RA. Position [2, 0] contains blk2 and position [2, 2] contains blk 0. All other positions are empty. RA already contains blk2 and blkO; do not write a duplicate copy. (Step 420) Does RA contain data block i or blk5? (Step 424) RA does contain blk5. Thus, nothing is written into position [2, 3]. Add 1 to i (i=6). Go back to Step 414. (Step 414) Compare i to x. (Step 416) i is equal to x (6=6). Increment j by 1 Q=4). Go to Step 406. (Step 406) Clear a Reference Array (RA) (Step 408) Compare j to x. (Step 412) j is less than x (4<6), let i = 0. (Step 414) Compare i to x. (Step 418) i is less than x (0<6). Read matrix positions of column [4] in the SM and write to RA. Position [4, 0] contains blk4. Blk4 is written into RA. All other positions are empty. (Step 420) Does RA contain data block i or blkO? (Step 422) RA does not contain blkO. Write blkO into position [4, 4] in the SM and the RA. RA now has blk4 and blkO. (Step 424) Add 1 to i (i=l) to derive value for position [5, 4]. Go back to Step 414. (Step 414) Compare i to x. (Step 418) i is less than x (1<6). Read matrix positions of column [5] in the SM and write to RA. Position [5, 0] contains blk5 and position [5, 3] contains blk2. All other positions are empty. RA now has blk4, blkO, blk 5, and blk2. (Step 420) Does RA contain data block i or blkl ? (Step 422) RA does not contain blkl . Write blkl into position [5, 4] of the SM and the RA. RA now has blk4, blkO, blk5, blk2, and blkl. (Step 424) Add 1 to i (i=2) to derive value for position [0, 4]. Go back to Step 414. (Step 414) Compare i to x. (Step 418) i is less than x (2<6). Read matrix positions of column [0] in the SM and write to RA. Position [0, 0] contains blkO. All other positions are empty. RA already contains blkO; thus, do not write a duplicate copy. (Step 420) Does RA contain data block i or blk2? (Step 424) RA does contain blk2. Add 1 to i (i=3) to derive value for position [1, 4]. Go back to Step 414. (Step 414) Compare i to x. (Step 418) i is less than x (3<6). Read matrix positions of column [1] in the SM and write to RA. Position [1, 0] contains blkl and position [1, 1] contains blkO. All other positions are empty. RA already contains blkl and blkO; do not write a duplicate copy. (Step 420) Does RA contain data block i or blk3? 26 (Step 422) RA does not contain blk3. Write blk3 into position [1, 4] of the SM and the RA. RA now has blk4, blkO, blk5, blk2, blkl, and blk3. (Step 424) Add 1 to i (i=4) to derive value for position [2, 4]. Go back to Step 414. (Step 414) Compare i to x. (Step 418) i is less than x (4<6). Read matrix positions of column [2] in the SM and write to RA. Position [2, 0] contains blk2 and position [2, 2] contains blkO. All other positions are empty. RA already contains blk2 and blkO; do not write a duplicate copy. (Step 420) Does RA contain data block i or blk4? (Step 424) RA does contain blk4. Thus, nothing is written into position [2, 4]. Add 1 to i (i=5) to derive value for position [3, 4]. Go back to Step 414. (Step 414) Compare i to x. (Step 418) i is less than x (5<6). Read matrix positions of column [3] in the SM and write to RA. Position [3, 0] contains blk3, position [3, 2] contains blkl, and position [3, 3] contains blkO. All other positions are empty. RA already contains blk3, blkl, and blkO; do not write a duplicate copy. (Step 420) Does RA contain data block i or blk5? (Step 424) RA does contain blk5. Thus, nothing is written into position [3, 4]. Add 1 to i (i=6). Go back to Step 414. (Step 414) Compare i to x. (Step 416) i is equal to x (6=6). Increment j by 1 (j=5). Go to Step 406. (Step 406) Clear a Reference Array (RA) (Step 408) Compare j to x. (Step 412) j is less than x (5<6), let i = 0. (Step 414) Compare i to x. (Step 418) i is less than x (0<6). Read matrix positions of column [5] in the SM and write to RA. Position [5, 0] contains blk5, position [5, 3] contains blk2, and position [5, 4] contains blkl. Blk5, blk2, and blkl are written into RA. All other positions are empty. (Step 420) Does RA contain data block i or blkO? (Step 422) RA does not contain blkO. Write blkO into position [5, 5] in the SM and the RA. RA now has blk5, blk2, blkl, and blkO. (Step 424) Add 1 to i (i=l) to derive value for position [0, 5]. Go back to Step 414. (Step 414) Compare i to x. (Step 418) i is less than x (1<6). Read matrix positions of column [0] in the SM and write to RA. Position [0, 0] contains blkO and all other positions are empty. RA now has blk5, blk2, blkl, and blkO. (Step 420) Does RA contain data block i or blkl? (Step 424) RA does contain blkl . Add 1 to i (i=2) to derive value for position [1, 5]. Go back to Step 414. (Step 414) Compare i to x. (Step 418) i is less than x (2<6). Read matrix positions of column [1] in the SM and write to RA. Position [1, 0] contains blkl, position [1, 1] contains blkO, and position [1, 4] contains blk3. All other positions are empty. RA already contains blkO and blkl; thus, do not write a duplicate copy. Write blk3 into RA. RA now has blk5, blk2, blk2, blkl, blkO, and blk3. (Step 420) Does RA contain data block i or blk2? 27 (Step 424) RA does contain blk2. Add 1 to i (i=3) to derive value for position [2, 5]. Go back to Step 414. (Step 414) Compare i to x. (Step 418) i is less than x (3<6). Read matrix positions of column [2] in the SM and write to RA. Position [2, 0] contains blk2 and position [2, 2] contains blkO. All other positions are empty. RA already contains blk2 and blkO; do not write a duplicate copy. (Step 420) Does RA contain data block i or blk3? (Step 424) RA does contain blk3. Add 1 to i (i=4) to derive value for position [3, 5]. Go back to Step 414. (Step 414) Compare i to x. (Step 418) i is less than x (4<6). Read matrix positions column [3] in the SM and write to RA. Position [3, 0] contains blk3, position [3, 2] contains blkl, position [3, 3] contains blkO. All other positions are empty. RA already contains blk3, blkl, and blkO; do not write a duplicate copy. (Step 420) Does RA contain data block i or blk4? (Step 422) RA does not contain blk4. Write blk4 into position [3, 5] of the SM and the RA. The RA now has blk5, blk2, blkl, blkO, blk3, and blk4. (Step 424) Add 1 to i (i=5) to derive value for position [4, 5]. Go back to Step 414. (Step 414) Compare i to x. (Step 418) i is less than x (5<6). Read matrix positions of column [4] in the SM and write to RA. Position [4, 0] contains blk4 and position [4, 4] contains blkO. All other positions are empty. RA already contains blk4 and blkO; do not write a duplicate copy. (Step 420) Does RA contain data block i or blk5? (Step 424) RA does contain blk5. Thus, nothing is written into position [3, 4]. (Step 424) Add 1 to i (i=6). Go back to Step 414. (Step 414) Compare i to x. (Step 416) i is equal to x (6=6). Increment j by 1 (j=5). Go to Step 406. (Step 406) Clear a Reference Array (RA) (Step 408) Compare j to x. (Step 410) j is equal to x (6=6); END. 28

Claims: WHAT IS CLAIMED IS: 1. A method for sending data to a client to provide data-on-demand services, comprising the steps of: (a) receiving a data file; (b) specifying a time interval; (c) parsing said data file into a plurality of data blocks based on said time interval such that each data block is displayable during said time interval; (d) determining a required number of time slots to send said data file, wherein each of said time slot has a duration substantially equal to said time interval; (e) allocating to each time slot at least: ( 1 ) a first of said plurality of data blocks; and (2) optionally one or more additional data blocks, such that said plurality of data blocks is available in sequential order to a client accessing said data file during any time slot; and (f) sending said plurality of data blocks based on said allocating step (e). 2. The method of claim 1 , wherein said parsing step includes the steps of: (1) determining an estimated data block size; (2) determining a cluster size of a memory in a channel server; and (3) parsing said data file based on said estimated data block size and said cluster size. 3. The method of claim 1, wherein said determining step includes the step of assessing resource allocation and bandwidth availability. 4. A method for processing data received from a server to provide data-on- demand services, comprising the steps of: (a) receiving a selection of a data file during a first time slot; (b) receiving at least one data block of said data file during a second time 29 slot; and (c) during a next time slot: ( 1 ) receiving any data block not already received; (2) sequentially displaying a data block of said data file; and (3) repeating step (c) until all data blocks of said data file has been received and displayed. 5. A method for generating a scheduling matrix for a data file, said scheduling matrix provides a send order for sending data blocks of a data file, such that said data blocks are available in sequential order to a client receiving said data blocks, said method comprising the steps of: (a) receiving a number of data blocks [x] for a data file; (b) setting a first variable [j] to zero; (c) setting a second variable [i] to zero; (d) clearing all entries in a reference array; (e) writing at least one data block stored in matrix positions of a column [(i+j) modulo x] in a matrix to a reference array, if said reference array does not already contain said data block; (f) writing a data block [i] into said reference array and a matrix position [(i+j) modulo x, j] of said matrix, if said reference array does not contain said data block [i]; (g) incrementing said second variable [i] by one and repeating step (e) until said second variable [i] is equal to said number of data blocks [x]; and (h) incrementing said first variable [j] by one and repeating said step (c) until said first variable [j] is equal to said number of data blocks [x]. 6. The method of claim 5, further comprising the steps of: (i) repeating said steps (a) to (h) to generate a set of scheduling matrices for a set of data files; and (j) applying a convolution method to generate a delivery matrix based on said set of scheduling matrices for sending said set of data files. 30 7. A data-on-demand system, comprising: a first set of channel servers; a central controlling server for controlling said first set of channel servers; a first set of up-converters coupled to said first set of channel servers; and a combiner module coupled to said first set of up-converters, said combiner module adapting to transmit data via a transmission medium; wherein said central controlling server is configured to divide a data file into data blocks and calculate a delivery matrix for sending said data blocks across said transmission medium in a scheduled manner such that said data file is accessible on demand. 8. The data-on-demand system of claim 7, wherein said combiner module includes a combiner and an amplifier. 9. The data-on-demand system of claim 7, wherein said channel server includes a controller, a modulator, and a network interface. 10. The data-on-demand system of claim 7, further comprising: a channel monitoring module for monitoring said system; a switch matrix; a second set of channel servers; and a second set of up-converters; wherein said channel monitoring module is configured to report system status to said central controlling server, said central controlling server, in response to a report from said channel monitoring module, instructing said switch matrix to replace a channel server in said first set of channel servers with a channel server in said second set of channel servers and replace an up-converter in said first set of up-converters with an up-converter in said second set of up-converters. 11. A method for processing data received from a server to provide data-on- demand services, comprising the steps of: (a) receiving a data packet from a server; 31 (b) reading header information in said data packet; (c) organizing said data packet into a data block based at least in part on said header information; (d) authenticating access to said data block; (e) decoding said data block when access is authenticated; and (f) displaying said data block. 12. The method of claim 11 , further comprising the steps of: (g) terminating said receiving step when an emergency bit is detected; (h) receiving emergency data; and (i) displaying said emergency data. 13. The method of claim 11 , further comprising the step of tuning to an emergency channel when no data packet is being received. 14. A method for calculating a delivery matrix, said delivery matrix provides a send order for sending data blocks of a set of data files, said method comprising the steps of: (a) calculating a scheduling matrix for each data file in a set of data files to form a set of scheduling matrices; (b) generating an identification array containing an identification for each of said set of data files; and (c) combining said set of scheduling matrices and said identification array to generate a delivery matrix for said set of data files. 15. The method of claim 14, wherein said calculating step includes the step of: (i) generating an array containing a set of time slots for each data file; and (ii) generating an array containing at least one data block of a data file to be sent during each time slot. 16. The method of claim 14, wherein said combining includes the step of using a convolution method. 32 AMENDED CLAIMS [received by the International Bureau on 15 October 2001 (15.10.01); new claims 17-33 added; remaining claims unchanged (4 pages)] A computer implemented on-demand data broadcast method comprising the act of preparing a delivery matrix defining a data transmission sequence suitable for broadcast, to a plurality of clients, on-demand data in a non client specific manner, whereby transmission of said on-demand data files requires an amount of transmission bandwidth that is independent of the number of said plurality of clients. 18. A computer implemented method as recited in claim 17, wherein the act of generating a delivery matrix comprises the act of: preparing a first scheduling matrix suitable for transmission of a first data file, said first data file being represented by a first plurality of data blocks, said first scheduling matrix providing a first sequence for transmitting said first plurality of data blocks sequentially within time slots in a manner such that any client receiving transmission of said first data file according to said first scheduling matrix may begin accessing said first data file within one time slot. 19. A computer implemented method as recited in claim 18, wherein the act of preparing a delivery matrix further includes the acts of: preparing a second scheduling matrix suitable for transmission of a second data file, said second data file being represented by a second plurality of data blocks, said second scheduling matrix providing a second sequence for transmitting said second plurality of data blocks sequentially within time slots in a manner such that any client receiving transmission of said second data file according to said second scheduling matrix may begin accessing said second data file within one time slot; and generating said delivery matrix through a combination of said first and second scheduling matrices. 20. A computer implemented universal data broadcast method as recited in claim 17 further comprising the act of preparing an electronic program guide (EPG) suitable for broadcast to said plurality of clients. 21. A computer implemented met! recited in claim 17, wherein said on-demand data includes video data. 33 22. A computer implemented method as recited in claim 17, wherein said on-demand data includes game data. 23. A computer implemented method for controlling a set-top-box (STB), said method comprising the acts of: receiving digital data including non client specific on-demand data having at least one data file; and processing said non client specific on-demand data in order to make ready said at least one data file for a user of said STB. 24. A computer implemented method as recited in claim 23, further comprising the acts of: receiving an electronic program guide (EPG) indicating the nature of said received digital data including said non client specific on-demand data having at least one data file; providing said EPG data to said user of said STB; and receiving a demand for said at least one data file from said user of said STB. 25. A computer implemented method as recited in claim 23, wherein said on-demand data includes video data. 26. A computer implemented method as recited in claim 23, wherein said on-demand data includes game data. 27. A computer implemented method as recited in claim 23 wherein said non client specific on-demand data includes a plurality of data files, and said act of processing said non client specific on-demand data includes processing said non client specific on-demand data in order to make at least two data files available to said user. 28. A computer implemented method as recited in claim 27 wherein a first of said at least two data files is provided real-time to said user. 34 29. A computer implemented method as recited in claim 27 wherein a first of said at least two data files is stored to a persistent memory device. 30. A computer implemented method for controlling a set-top-box (STB), said method comprising the acts of: receiving digital data including non client specific on-demand data having at least one data file and an electronic program guide (EPG), said EPG indicating the nature of said received digital data and non client specific on-demand data having at least one data file; providing said EPG data to a user of said STB ; receiving a demand for said at least one data file from said user of said STB; and processing said non client specific on-demand data in order to make ready said at least one data file for said user. 31. A set-top-box (STB) capable of receiving and handling a plurality of digital services such as VOD and digital broadcast, said universal STB comprising: a databus; a first communication device suitable for coupling to a digital broadcast communications medium, said first communication device operable to receive digital broadcast data; memory bi-directionally coupled to said databus; a digital data decoder bi-directionally coupled to said databus; and a central processing unit (CPU) bi-directionally coupled to said databus, said CPU implementing a STB control process controlling said memory, said digital decoder, and said demodulator, said STB control process executing instructions for: processing an electronic program guide (EPG) received via said first communication device, said EPG indicating a nature of data broadcast via a digital broadcast server coupled to said communication device; providing a user of said STB an indication of said broadcast data; receiving a request for desired data received by said STB, wherein said desired data is received in a non client specific data-on demand format as designated by said EPG; 35 processing said desired data received in a non client specific data-on demand format; and providing said desired data to said user of said universal STB. 32. A STB as recited in claim 31, wherein said STB control process is operable to simultaneously tune into two or more of a plurality of channels broadcast by said universal broadcast server, and to simultaneously process data from two or more of said plurality of channels. 33. A STB as recited in claim 31, wherein said STB control process is operable to tune said STB to a first channel in order to select data requested by said user, determine the nature of said selected data, decode said selected data, decompress said selected data, reassemble said decoded data, store said selected data to said memory, and provide said selected data in a properly processed manner to an output device. 36

Inventors: HOANG KHOI, HOANG, KHOI
Applicants: PREDIWAVE CORP, PREDIWAVE CORP.
Application year: 2000
Main classification: G06F15
IPC codes: H04L29, H04N5, H04N7