Network and user behavior based time-shifted mobile data transmission

A system, and computer program product for mobile data transmission are provided in the illustrative embodiments. A request for data is received from a mobile device. A determination is made whether a data transmission over a mobile data communication network in response to the request can be delayed, forming a time-shifting determination. A determination is made, responsive to the time-shifting determination being affirmative, a delayed schedule for the data transmission in response to the request such that the data transmission is completed by a deadline. The data is transmitted over the mobile data communication network according to the delayed schedule.

BACKGROUND

1. Technical Field

The present invention relates generally to a system, and computer program product for mobile communications. More particularly, the present invention relates to a system, and computer program product for network and user behavior based time shifted mobile data transmission.

2. Description of the Related Art

Mobile data communication essentially is data communication using a mobile device at least at one end of the data communication. The data being communicated to or from the mobile device may be voice data, video data, application data, session management data, or many other types of data.

Some mobile data communications are interactive or time-sensitive data communications, in other words, synchronous data communications. For example, voice data is time sensitive in that the data has to be transmitted to and from a mobile device without perceptible delays, otherwise the voice communication becomes unacceptable. As another example, a banking transaction may be synchronous because a transaction has to complete within stipulated time and other transactions cannot proceed until a preceding transaction has completed.

Some other mobile data communications are background communications, or not time sensitive in nature, in other words, asynchronous data communications. For example, a file backup operation may occur in the background, may be interrupted and restarted over a period without affecting the end result of creating a backup to or from a mobile device.

SUMMARY

The illustrative embodiments provide a system, and computer program product for mobile data transmission. One embodiment receives a request for data from a mobile device. The embodiment determines, using a processor and a memory, whether a data transmission over a mobile data communication network in response to the request can be delayed, forming a time-shifting determination. The embodiment further determines, responsive to the time-shifting determination being affirmative, a delayed schedule for the data transmission in response to the request such that the data transmission is completed by a deadline. The embodiment transmits over the mobile data communication network the data according to the delayed schedule.

In another embodiment, determining the delayed schedule further includes determining a probability density function (PDF) of network load in the mobile data communication network over a period, wherein the PDF of network load is determined using historical network load data collected from a set of mobile data communication network infrastructure components. The embodiment further includes determining a pattern of movement (mobility pattern) of the mobile device during the period. The embodiment further includes computing a load threshold using the network load PDF and the mobility pattern, such that transmitting the data only when network load is below the load threshold satisfies the deadline. The embodiment further includes computing a rate of transmission corresponding to the load threshold, wherein the delayed schedule is based on the rate of transmission.

Another embodiment further includes recomputing the load threshold at a set interval, or at an occurrence of an event in the mobile data communication network.

In another embodiment, determining the delayed schedule further includes receiving a plurality of requests from a corresponding plurality of mobile devices, wherein each request in the plurality of requests has a corresponding deadline, and wherein the request is one of the plurality of requests and the deadline is one of the plurality of deadlines. The embodiment further includes arranging the plurality of requests in an order of shortest deadline to longest deadline. The embodiment further includes determining a pattern of movement (mobility pattern) of the mobile device during a period. The embodiment further includes determining a PDF of channel quality in the mobile data communication network over the period, wherein the PDF of channel quality is determined using historical channel quality data collected along the mobility patterns during the period. The embodiment further includes computing a signal threshold using the channel quality PDF and the mobility pattern, such that transmitting the data only when signal quality to the mobile device exceeds the signal threshold satisfies the deadline. The embodiment further includes identifying a time slot when the signal quality to the mobile device exceeds the signal threshold, wherein the delayed schedule is based on the identified time slot, and wherein the data is transmitted using the time slot. The embodiment further includes scheduling to transmit second data in response to a second request in the plurality of requests in a second time slot.

Another embodiment further includes recomputing the signal threshold at one of (i) a set interval, and (ii) at an occurrence of an event in the mobile data communication network.

In another embodiment, determining the delayed schedule further includes determining a pattern of movement (mobility pattern) of the mobile device during a period. The embodiment further includes determining a PDF of channel quality in the mobile data communication network over the period, wherein the PDF of channel quality is determined using historical channel quality data collected along the mobility patterns during the period. The embodiment further includes computing a weight parameter using the channel quality PDF and the mobility pattern. The embodiment further includes computing, at a data transmission time slot, a product of the weight parameter and a signal quality to the mobile device, wherein the delayed schedule uses the data transmission time slot responsive to the product having highest value amongst a plurality of products corresponding to a plurality of requests during the data transmission time slot.

Another embodiment further includes recomputing the weight parameter at a set interval, or at an occurrence of an event in the mobile data communication network.

Another embodiment further includes determining whether the network load exceeds a load threshold, wherein the data transmission in response to the request is not delayed responsive to the time-shifting determination being negative, or the network load not exceeding the load threshold.

Another embodiment further includes sending a set of deadlines and a corresponding set of incentives to the mobile device. The embodiment further includes receiving a selection of the deadline from the set of deadlines, wherein the deadline delivers a corresponding incentive from the set of incentives to the mobile device during the data transmission.

In another embodiment, the corresponding incentive is an improved user experience in consuming data of the data transmission.

In another embodiment, the corresponding incentive is an improved quality of service (QoS) during the data transmission.

DETAILED DESCRIPTION

An explosive growth in mobile data traffic is occurring given the rapid adoption of mobile devices such as smartphones, tablet computers, and embedded mobile computing platforms. The mobile data traffic includes mobile data communications for applications such as audio, video, and gaming applications, that are time-sensitive and require near-real-time quality of service (QoS).

The illustrative embodiments recognize that mobile traffic exhibits a distinct diurnal pattern in aggregate network load. For example, the mobile data traffic volume varies greatly between peak and off-peak times. The illustrative embodiments recognize that at peak load times, the performance of mobile applications degrades uniformly, i.e., when the mobile network is experiencing higher than threshold loads, all types of mobile data communications suffer from the scarcity of bandwidth. For example, mobile services consumers are all too familiar with video lags, choppy voice communications, call drops, slow webpage loads, and transaction timeouts during peak hours designated by the mobile carriers.

Network upgrades, capacity increases, or additional spectrum purchase are cost-prohibitive answers to the explosive demand in mobile data communications. Provisioning for peak usage is expensive and results in poor utilization during off-peak periods. Mobile communication network operators are under pressure the make the most of the available network infrastructure and wireless spectrum to meet the demand in a satisfactory manner. The illustrative embodiments recognize that reducing peak load is key to improving mobile data communication experience without performing expensive network upgrades.

The illustrative embodiments used to describe the invention generally address and solve the above-described problems and other problems related to providing mobile data communications. The illustrative embodiments provide a system, and computer program product for network and user behavior based time shifted mobile data transmission.

Mobility pattern is a record of a mobile device's position over a period. An embodiment uses a mobile data requestor's future positions—a trajectory—using mobility patterns of the mobile device associated with the requestor. A requestor can be a user of the mobile device or an application executing on the mobile device.

Channel quality is a record of an indicator of quality of mobile data communication channel that existed between a base-station and a mobile device over a period. Signal strength is one example indicator of channel quality. Noise to signal ratio is another example of such indicator. Many other indicators will be conceivable from this disclosure by those of ordinary skill in the art and the same are contemplated within the scope of the illustrative embodiments.

The illustrative embodiments recognize that mobile data consumers present predictable mobility patterns with corresponding patterns in channel quality variation. The illustrative embodiments recognize that some requestors are either inherently tolerant to data transmission delay, or can be made to behave as such by providing incentives. For example, requestors requesting predictable traffic like news-videos, podcasts, sync services, Software upgrades, and large file transfers can be incentivized with better QoS for time-shifted transmission of the requested data.

An embodiment selects certain mobile data transmissions to a mobile device for time-shifting. Time-shifting is the process of delaying or shifting a transmission time for a part of a selected data transmission to a mobile device. For example, delay-sensitive mobile data traffic, such as video-on-demand, consumes more resources than an equivalent file transfer of similar size. An embodiment attempts to time-shift resource-expensive traffic to help alleviate network peak load.

An embodiment provides improved performance as an incentive to accepting time-shifted delivery of requested data. For example, an application may request a video-on-demand during peak load time. If the data communication continues to provide the video-on-demand service at that time, the video experience is likely to suffer from buffering delays and interruptions. On the other hand, if the video-on-demand service is postponed, or time-shifted, for another time, such as an off-peak time, or when the user has traveled into an area of less than peak load, the user has the incentive of a better video experience at the cost of a delaying that experience.

Generally, an embodiment matches time-elastic mobile data demand with varying network resource availability. In other words, an embodiment identifies delay-tolerant data transmission requests or requestors, negotiates a transmission deadline for the request, for example in exchange for some incentive, and time-shifts the data transmission to a later time when network resources are available above a threshold level. If the data transmission is time-sensitive, an embodiment may negotiate a shorter than a threshold deadline to time-shift the transmission. If the data transmission is not time-sensitive, an embodiment may negotiate a deadline that is longer than a threshold to time-shift the transmission. Thus, an embodiment achieves network load reduction by time-shifting data transmissions and delivering the requested data by the negotiated deadline.

The illustrative embodiments recognize that asking users or mobile applications repeatedly and during the data demand is impractical. The illustrative embodiments use statistical analysis of historical requestors' usage behavior, historical network load behavior, and historical conditions of the mobile data communication channel (channel conditions) for the requestors to devise scheduling strategies that meet data delivery deadlines.

When an embodiment negotiates a deadline in exchange for performance incentives, the negotiations can be transparent to the user of the mobile device. For example, the user can pre-configure an application to negotiate a time-shifted deadline for certain type of data transmissions.

The illustrative embodiments are described with respect to certain devices only as examples. Such descriptions are not intended to be limiting on the invention. For example, an illustrative embodiment described with respect to a smartphone mobile device can be implemented with respect to an embedded mobile computing platform in an automobile without limitation.

The illustrative embodiments are described with respect to certain data only as examples. Such descriptions are not intended to be limiting on the invention. For example, an illustrative embodiment described with respect to a smartphone mobile device using video-on-demand can be implemented with respect to an embedded mobile computing platform in an automobile requesting map database update within the scope of the illustrative embodiments.

FIG. 1depicts a pictorial representation of a network of data processing systems in which illustrative embodiments may be implemented. Data processing environment100is a network of data processing systems in which the illustrative embodiments may be implemented. Data processing environment100includes network102. Network102is the medium used to provide communications links between various devices and computers connected together within data processing environment100. Network102may include connections, such as wire, wireless communication links, or fiber optic cables. Server104and server106couple to network102along with storage unit108. Software applications may execute on any data processing system or device in data processing environment100.

Clients110,112, and114also couple to network102. A data processing system, such as server104or106, or client110,112, or114may contain data and may have software applications or software tools executing thereon.

In addition, mobile device120may be any suitable mobile data processing system capable of performing mobile data communication using mobile communications infrastructure, such as, but not limited to base-station122. Base-station122, a wireless access point, a micro cell device, a pico cell device, or a femto cell device, or a wireless antenna are some examples of mobile communication infrastructure that can communicate with backend systems, such as server104, or to another network via network102. Application105in server104implements all or part an embodiment. In cases where an embodiment is implemented in multiple modules or components, such modules or components may be distributed to other data processing systems, such as server106or client112(distributed components not shown) in the form of other applications. Certain features of an embodiment can be implemented in mobile device120, base-station122, server104, or a combination thereof, without limitation, and depending on the particular implementation. Storage108includes policies data123, channel quality data (channel quality index, “CQI”)124, mobility history125, and network load history126for use according to an embodiment. Policies data123, channel quality data (channel quality index, “CQI”)124, mobility history125, and network load history126may each be stored in any suitable form in storage108, such as in the form of a database, file, or any other suitable data structure.

Servers104and106, storage unit108, and clients110,112, and114may couple to network102using wired connections, wireless communication protocols, or other suitable data connectivity. For example, a cluster typically has multiple network types, such as IP networks, direct connections of machines via packets exchange implemented by storage protocols (Fibre Channel, SCSI), serial links, and message exchange via writing and reading packets to shared storage such as a hard disk drive. For performance reasons, in sending client traffic, an IP network is given precedence. Furthermore, a given network type may not connect to all nodes in a cluster. For instance, a cluster may span machines located at two geographically distant sites. For the long distance connection, Ethernet may be the preferred connection, and within a geographical location, a direct connection may be preferable. Additionally, within a geographical location, additional non-IP networks, such as Fibre channel or serial connections may be used within the scope of the illustrative embodiments.

With reference toFIG. 2, this figure depicts a block diagram of a data processing system in which illustrative embodiments may be implemented. Data processing system200is an example of a computer, such as server104, server106, or client112inFIG. 1, or another type of device in which computer usable program code or instructions implementing the processes of the illustrative embodiments may be located for the illustrative embodiments. Data processing system200is also representative of a computing device, such as mobile device120inFIG. 1in which computer usable program code or instructions implementing the processes of the illustrative embodiments may be located for the illustrative embodiments. Data processing system200is also representative of an embedded mobile computing device, such as a data processing system embedded in a vehicle (not shown) in which computer usable program code or instructions implementing the processes of the illustrative embodiments may be located for the illustrative embodiments. Data processing system200is described as a computer only as an example, without being limited thereto. Implementations in the form of mobile device120inFIG. 1may modify data processing system200and even eliminate certain depicted components there from without departing from the general description of the operations and functions of data processing system200described herein.

In the depicted example, data processing system200employs a hub architecture including North Bridge and memory controller hub (NB/MCH)202and south bridge and input/output (I/O) controller hub (SB/ICH)204. Processing unit206, main memory208, and graphics processor210are coupled to north bridge and memory controller hub (NB/MCH)202. Processing unit206may include one or more processors and may be implemented using one or more heterogeneous processor systems. Graphics processor210may be coupled to NB/MCH202through an accelerated graphics port (AGP) in certain implementations.

An operating system runs on processing unit206. The operating system coordinates and provides control of various components within data processing system200inFIG. 2. The operating system may be a commercially available operating system such as Microsoft® Windows® (Microsoft and Windows are trademarks of Microsoft Corporation in the United States, other countries, or both), or Linux® (Linux is a trademark of Linus Torvalds in the United States, other countries, or both). An object oriented programming system, such as the Java™ programming system, may run in conjunction with the operating system and provide calls to the operating system from Java™ programs or applications executing on data processing system200(Java and all Java-based trademarks and logos are trademarks or registered trademarks of Oracle Corporation and/or its affiliates).

Program instructions for the operating system, the object-oriented programming system, the processes of the illustrative embodiments, and applications or programs, including application105, are located on one or more storage devices, such as hard disk drive226or CD-ROM230, and may be loaded into at least one of one or more memories, such as main memory208, read only memory224, or one or more peripheral devices, for execution by processing unit206. Program instructions may also be stored permanently in non-volatile memory and either loaded from there or executed in place. For example, the synthesized program according to an embodiment can be stored in non-volatile memory and loaded from there into DRAM.

With reference toFIG. 3, this figure depicts an example network load probability density function graph that is usable in an illustrative embodiment. Probability density function (PDF) graph300can be constructed using historical data from network load history data126in storage108inFIG. 1. Graph300depicts the load on the X-axis, and the probability of a value of the load occurring on the Y-axis, over a given period.

With reference toFIG. 4, this figure depicts some example cases of time-shifting data transmissions in accordance with an illustrative embodiment. Mobile devices402and404may be an example of mobile device120inFIG. 1at different times. Graphs412and414are constructed for projecting network load over different periods using network load history data126inFIG. 1. Period markings are shown at thirty minutes and one hour only as examples for clarity and not as a limitation on an embodiment.

Assume that mobile device402has to transfer data of size F and has agreed to a deadline of one hour. Assume, as shown in graph412that at time T1, network load is expected to be lower than threshold422for a part of the one-hour negotiated deadline and then exceed threshold422for the remainder of the period. Accordingly, an embodiment determines that the data transmission can be accomplished during time slot432as depicted in graph412A, which is identical to graph412.

Similarly, assume that mobile device404has to transfer data of size F and has also agreed to a deadline of one hour. Assume, as shown in graph414that at time T2, network load is expected to exceed threshold424for a part of the one-hour negotiated deadline and then reduce below threshold424for the remainder of the period. Accordingly, an embodiment determines that the data transmission can be accomplished during time slot434as depicted in graph414A, which is identical to graph414.

With reference toFIG. 5, this figure depicts a block diagram of an example configuration for network and user behavior based time shifted mobile data transmission in accordance with an illustrative embodiment. Policy module502, control module504, and controller506can be implemented as application105inFIG. 1. In one embodiment, application105inFIG. 1implements one of policy module502, control module504, and controller506, and the remaining modules are each implemented as separate applications, distributed and executed on data processing systems in the manner of application105on server104inFIG. 1.

Policy module502accepts data requests from any number of mobile devices. For example, policy module502accepts request500from mobile device508, which is i-the requestor amongst n requestors. Mobile device508is analogous to mobile device402or404inFIG. 4.

Policy database510corresponds to policies data123inFIG. 1. Channel quality history database514corresponds to CQI data124inFIG. 1and includes channel quality information collected from mobile devices on the mobile network. Mobility history database516corresponds to mobility history data125inFIG. 1and includes position information, such as location and rate of transition through cells, collected from mobile devices on the mobile network. Network load history database518corresponds to network load history data126inFIG. 1and includes load data collected from network infrastructure components such as base-stations. Policy database510, channel quality history database514, mobility history database516, and network load history database518are example manifestations of their corresponding counterparts inFIG. 1, without implying a limitation of any particular database structure or form.

Policy database510provides to policy module502one or more policies or rules to use in computing a time-shifted deadline and a corresponding incentive. Mobility history database516provides requestor mobile device508's trajectory. Channel quality history database514provides historical channel quality information along requestor mobile device508's trajectory. Network load history database518provides historical network load information along requestor mobile device508's trajectory during previous times similar to the time of request500.

Using the inputs from policy database510, channel quality history database514, mobility history database516, and network load history database518, policy database module502computes one or more sets of deadlines and corresponding incentives to offer to mobile device502.

Using the deadlines and incentives, policy module502negotiates512a deadline for transmitting the requested data. Mobile device508being the i-th requestor, policy module502sends the negotiated deadline Difor the requested data size of Fito control module504. If no deadline can be negotiated, policy module502instructs scheduler530in the mobile network infrastructure to schedule the data transmission of the requested data upon request, i.e., serve-on-demand.

Control module504includes components for modeling PDFs using historical information. For example, mobility modeler522builds patterns of mobility between cells for a single requestor or a single class of requestors at a given time of day using a trajectory learning algorithm on the data furnished by the mobility history database516.

Using channel quality history database514and mobility history database516, CQI modeler520builds statistical models—PDFs—of the wireless channel quality seen at a particular location in a given time window. Operating in conjunction with mobility modeler522, CQI modeler520builds statistical models of the wireless channel quality along a particular trajectory, such as the trajectory of mobile device508.

Load modeler524builds statistical models—PDFs—of the load on a given base-station at a given time of day, using load history database518and mobility database516. Operating in conjunction with mobility modeler522, load modeler524builds statistical models of the load along a given trajectory, such as the trajectory of mobile device508.

Using one or more of the PDFs and mobility patterns thus available, control module504produces one or more thresholds or parameters, collectively referred to as policy parameters. For example, in one embodiment, control module504produces a signal threshold Sifor i-th requestor mobile device508. In another embodiment, control module504produces a load threshold Lifor i-th requestor mobile device508. In another embodiment, control module504produces a weighting parameter Wifor i-th requestor mobile device508. Uses of signal threshold Si, load threshold Li, and weighting parameter Wiare described in greater detail with respect toFIGS. 7,8, and9.

Using one or more policy parameters from control module504, and present load conditions at a base-station, such as base-station122inFIG. 1, that would be transmitting the requested data, controller506produces a rate parameter Rifor i-th requestor mobile device508for request500. Rate parameter Ri is usable by scheduler530in the mobile network infrastructure to schedule the rate of transmission of the requested data from the base-station that would be transmitting the requested data.

With reference toFIG. 6, this figure depicts a block diagram of a process of network and user behavior based time shifted mobile data transmission in accordance with an illustrative embodiment. Process600can be implemented using a combination of policy module502, control module504, controller506, and scheduler530inFIG. 5.

Process600begins by receiving a data transfer request, such as request500inFIG. 5, (step602). Process600determines the present network load at the time of the request is above a threshold level of load (step604). If the network load does not exceed the threshold (“No” path of step604), process600serves the request on demand (step606). As to the request of step602, process600ends thereafter. Processing a request on demand when the network load permits allows for the expected user-experience and QoS and no deadline negotiations are required.

If the network load exceeds the threshold (“Yes” path of step604), process600determines whether the request of step602or a mobile device making the request can be time-shifted (step608). If the request or the requestor cannot be time-shifted (“No” path of step608), process600serves the request on demand at step606, and ends thereafter as to the request of step602.

If the request or the requestor can be time-shifted (“Yes” path of step608), process600publishes one or more sets of time-shifted deadlines and corresponding incentives to the requestor (step610). Process600receives a deadline selection (step612). In one embodiment, an application executing in a mobile device may select a deadline in manner transparent to a user. For example, the application may select a deadline according to a delay tolerance parameter that is preconfigured according to a day, time, type of data, location of the user, or any other factor. In another embodiment, a user may be prompted to select one of the deadlines.

Process600determines the scheduling, i.e., the rate of transmission, for the transfer of the requested data (step614). Process600schedules the data transfer accordingly (step616). Process600ends thereafter for the request of step602. In one embodiment, for example owing to network load change, user mobility, or channel quality change, process600may re-execute for the same request if part of the requested data remains to be transmitted to the requestor mobile device.

With reference toFIG. 7, this figure depicts a flowchart of an example process of load threshold based time-shifting of data transmission in accordance with an illustrative embodiment. Process700can be implemented in control module504ofFIG. 5to produce load threshold Lipolicy parameter.

Process700executes for each requestor i, and begins by receiving a data transfer request for data size Fiby deadline Difrom requestor i (step702). Process700determines a pattern of mobility between cell locations during the period from a present time till deadline Di for requestor i (step704). Process700determines a PDF of network load over a period for requestor i (step706).

Using the load PDF and the mobility pattern, process700computes a load threshold Lisuch that if the data is transmitted to the requestor only when the network load is less than Li, deadline Diis met (step708).

In each slot, process700checks if the load is less than the load threshold Li, and if so, determines a rate of transmission Ri(step710). At step708, process700recomputes the threshold Liat set intervals or upon certain events using all pending data requests (step708A), and adjusts rate Riaccordingly. Process700schedules the data transmission according to rate Ri(step712). Process700ends thereafter.

With reference toFIG. 8, this figure depicts a flowchart of an example process of signal quality threshold based time-shifting of data transmission in accordance with an illustrative embodiment. Process800can be implemented in control module504ofFIG. 5to produce signal threshold Sipolicy parameter.

Process800executes for each requestor i, and begins by receiving a data transfer request for data size Fiby deadline Difrom requestor i (step802). Process800arranges the data transmission requests from all active requestors in the order of earliest to latest deadlines (step804).

Assume that a requestor index i is initialized to value 1 (step806). Process800calculates the expected fraction of slots occupied by requestors1through i−1 (step814). Process800determines a pattern of mobility between cell locations during the period for requestor i (step808). Process800determines a PDF of channel quality in the unoccupied slots in the period between a present time and deadline Difor requestor i (step810).

For requestor i, using the channel quality PDF and the mobility pattern, process800computes a signal threshold Si(a measure of channel quality) such that if the data is transmitted to the requestor only when the signal exceed Si, deadline Diis met (step812).

The requestor index i is incremented if more requestors are pending (step818). If more requestors are pending, process800returns to step814with the incremented index. In another branch of process800, process800also recomputes the signal threshold, such as upon an event or passage of a set period since the last computed threshold (step820). For example, process800may recompute the threshold Liat set intervals or upon certain events using all pending data requests. The branch of process800returns to step804.

If no more requestors are pending, process800checks if the load is less than the load threshold Li, and if so, determines a rate of transmission Ri(step830). Process800schedules the data transmission according to rate Ri(step832). Process800ends thereafter.

With reference toFIG. 9, this figure depicts a flowchart of an example process of weight parameter based time-shifting of data transmission in accordance with an illustrative embodiment. Process900can be implemented in control module504ofFIG. 5to produce signal threshold Sipolicy parameter.

Process900executes for each requestor i. Process900receives a data transfer request for data size Fiby deadline Difrom requestor i (step902). Process900determines a pattern of mobility between cell locations during the period for requestor i (step904). Process900determines a PDF of channel quality over a period from a present time till deadline Di for requestor i (step906).

For requestor i, using the PDF and the mobility pattern, process900computes a weight parameter Wi(step910). At step910, process900recomputes the weight parameter Wiat set intervals or upon certain events using all pending data requests (step910A).

For each transmission slot, process900schedules to transmit data for such requestor whose product of weight parameter and signal quality is the highest at the time of the time slot (step912). Process900ends thereafter.

Thus, a system, and computer program product are provided in the illustrative embodiments for network and user behavior based time shifted mobile data transmission. Using an embodiment, resource-heavy requests and requests for predictable data traffic, such as newscasts, can be time-shifted to improve the peak load behavior of a mobile network. An embodiment not only improves the network performance of the mobile network during greater than threshold load times, the embodiment also improves QoS and user-experience during the data transmission, although the experience is delayed.

An embodiment can be implemented to operate in conjunction with a radio network controller component of mobile network's infrastructure. An embodiment receives the requests for data transmissions and analyzes the requests to determine whether and how they can be time-shifted. The time-shifting of an embodiment operates in conjunction with a base-station scheduler at a coarse-grain time scale of a few seconds to a few minutes.

An embodiment leverages statistical information about channel quality and network load to devise a schedule that serves each request before its specified deadline. An embodiment also minimizes the network footprint by varying the rate of feeding the base-station queues so as to opportunistically transmit in periods of low load and high channel quality. An embodiment corrects any errors between prediction based on the models and real experience during transmission to a mobile device by bootstrapping and re-computing the policy parameters at set intervals or upon certain events.

Any combination of one or more computer readable storage device(s) or computer readable media may be utilized. The computer readable medium may be a computer readable signal medium or a computer readable storage medium. A computer readable storage device may be an electronic, magnetic, optical, electromagnetic, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. More specific examples (a non-exhaustive list) of the computer readable storage device would include the following: a portable computer diskette, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or Flash memory), a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the context of this document, a computer readable storage device may be any tangible device that can store a program for use by or in connection with an instruction execution system, apparatus, or device. The terms “computer usable storage device” and “storage device” do not encompass a signal propagation medium such as a copper cable, optical fiber, or wireless transmission medium, any description in this disclosure to the contrary notwithstanding.

Program code embodied on a computer readable storage device or computer readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.

Aspects of the present invention are described herein with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and/or block diagrams, and combinations of blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to one or more processors of one or more general purpose computers, special purpose computers, or other programmable data processing apparatuses to produce a machine, such that the instructions, which execute via the one or more processors of the computers or other programmable data processing apparatuses, create means for implementing the functions/acts specified in the flowchart and/or block diagram block or blocks.

These computer program instructions may also be stored in one or more computer readable storage devices or computer readable media that can direct one or more computers, one or more other programmable data processing apparatuses, or one or more other devices to function in a particular manner, such that the instructions stored in the one or more computer readable storage devices or computer readable medium produce an article of manufacture including instructions which implement the function/act specified in the flowchart and/or block diagram block or blocks.

The computer program instructions may also be loaded onto one or more computers, one or more other programmable data processing apparatuses, or one or more other devices to cause a series of operational steps to be performed on the one or more computers, one or more other programmable data processing apparatuses, or one or more other devices to produce a computer implemented process such that the instructions which execute on the one or more computers, one or more other programmable data processing apparatuses, or one or more other devices provide processes for implementing the functions/acts specified in the flowchart and/or block diagram block or blocks.