WO2015074991A1

WO2015074991A1 - Ranking based prediction of network connection for multimedia event

Info

Publication number: WO2015074991A1
Application number: PCT/EP2014/074749
Authority: WO
Inventors: Parashar SHAH
Original assignee: Alcatel Lucent
Priority date: 2013-11-20
Filing date: 2014-11-17
Publication date: 2015-05-28
Also published as: IN2013DE03397A

Abstract

Method(s) and system(s) for ranking based prediction of network connections for carrying out a multimedia event are disclosed. The method may include receiving network service and device parameters pertaining to a plurality of network connections, subscribed by a user, from one or more data sources. The network service and device parameters are indicative of information relating to the multimedia event and the network connections. Further, the method may include aggregating the network service and device parameters for each network connection based on at least a type of network connection. The method may also include ranking the network connections based on at least one predictive ranking rule on the aggregated network service and device parameters to predict at least one network connection from amongst the plurality of network connections for carrying out the multimedia event. The predictive ranking rule is indicative of criteria for ranking the network connections.

Description

RANKING BASED PREDICTION OF NETWORK CONNECTION FOR MULTIMEDIA

EVENT

FIELD OF INVENTION

[0001] The present subject matter relates to ranking of network connections and, particularly, but not exclusively, to ranking based prediction of network connection for a multimedia event.

BACKGROUND

[0002] Communication devices, such as cellular phones, Smartphones, personal digital assistants (PDAs), tablets, home theatre system, internet protocol televisions (IPTVs), smart televisions (smart TVs), laptops, and desktops have seemingly become a ubiquitous part of today's lifestyle and digital technology has found its way into different aspects of human life, professional as well as personal.

[0003] With recent advances in technology and growing competition, a large number of internet based services are offered by operators that are accessible using these communication devices. An operator may be understood as an internet service provider. The operators are faced with a challenge to meet user demands of high speed data connectivity at all places and all the time across the communication devices. For this, the operators generally provide the internet based services to the users through various network connections, such as Wi-Fi network connections over asymmetric digital subscriber line (ADSL) broadband network connections, third Generation (3G) network connections, Long Term Evolution (LTE) network connections, and ADSL broadband network connections. Examples of internet based services that are utilized by users include video on demand (VOD), music on demand (MOD), video conferencing, web surfing, conference communications, online gaming, and real time social networking.

SUMMARY

[0004] This summary is provided to introduce concepts related to ranking based prediction of network connection for multimedia event. This summary is not intended to identify essential features of the claimed subject matter nor is it directed to use in determining or limiting the scope of the claimed subject matter. [0005] In an aspect, a method for ranking based prediction of network connections for carrying out a multimedia event is disclosed. The method may include receiving network service and device parameters pertaining to a plurality of network connections, subscribed by a user, from one or more data sources. The network service and device parameters are indicative of information relating to the multimedia event and the plurality of network connections. Further, the method may include aggregating the network service and device parameters for each of the plurality of network connections based on at least a type of network connection. The method may also include ranking the plurality of network connections based on at least one predictive ranking rule on the aggregated network service and device parameters to predict at least one network connection from amongst the plurality of network connections for carrying out the multimedia event. The at least one predictive ranking rule is indicative of criteria for ranking the plurality of network connections.

[0006] In another aspect, the present subject matter discloses a predictive ranking system for predicting network connections, based on ranking, for carrying out a multimedia event. The predictive ranking system may include a processor, a determination module coupled to the processor, an aggregation module coupled to the processor, and a ranking module coupled to the processor. The determination module may receive network service and device parameters pertaining to a plurality of network connections, subscribed by a user, from one or more data sources. The network service and device parameters are indicative of information relating to the multimedia event and the plurality of network connections. Further, the aggregation module may aggregate the network service and device parameters for each of the plurality of network connections based on at least a type of network connection. The ranking module may rank the plurality of network connections based on at least one predictive ranking rule on the aggregated network service and device parameters to predict at least one network connection from amongst the plurality of network connections for carrying out the multimedia event. The at least one predictive ranking rule is indicative of criteria for ranking the plurality of network connections.

[0007] In yet another aspect, a computer readable medium having embodied thereon a computer program for executing a method for ranking based prediction of network connections for carrying out a multimedia event is disclosed. The method may include receiving network service and device parameters pertaining to a plurality of network connections, subscribed by a user, from one or more data sources. The network service and device parameters are indicative of information relating to the multimedia event and the plurality of network connections. Further, the method may include aggregating the network service and device parameters for each of the plurality of network connections based on at least a type of network connection. The method may also include ranking the plurality of network connections based on at least one predictive ranking rule on the aggregated network service and device parameters to predict at least one network connection from amongst the plurality of network connections for carrying out the multimedia event. The at least one predictive ranking rule is indicative of criteria for ranking the plurality of network connections.

BRIEF DESCRIPTION OF THE FIGURES

[0008] The detailed description is described with reference to the accompanying figures.

In the figures, the left-most digit(s) of a reference number identifies the figure in which the reference number first appears. The same numbers are used throughout the figures to reference like features and components. Some embodiments of system and/or methods in accordance with embodiments of the present subject matter are now described, by way of example only, and with reference to the accompanying figures, in which:

[0009] Figure 1 illustrates a communication network environment implementing a predictive ranking system, in accordance with an embodiment of the present subject matter; and

[0010] Figure 2 illustrates a method for ranking based prediction of network connections for carrying out a multimedia event, in accordance with an embodiment of the present subject matter.

[0011] It should be appreciated by those skilled in the art that any block diagrams herein represent conceptual views of illustrative systems embodying the principles of the present subject matter. Similarly, it will be appreciated that any flow charts, flow diagrams, state transition diagrams, pseudo code, and the like represent various processes which may be substantially represented in computer readable medium and so executed by a computer or processor, whether or not such computer or processor is explicitly shown.

DESCRIPTION OF EMBODIMENTS [0012] Nowadays, users are becoming increasingly demanding in terms of rate of data transfer, availability of network connections access, numbers and categories of features or services offered by operators. As mentioned earlier, operators may be understood as internet service providers. As a consequence, the operators are faced with a challenge to meet users' demands and expectations of high speed data connectivity at all places and all times. High speed data connectively also enable data intensive internet based services, such as video on demand (VOD), music on demand (MOD), video conferencing, web surfing, online gaming, and real time social networking to cater to the evolving users' needs and provide rich user experiences.

[0013] With an increasingly large number of users availing various high data rate internet based services provided by the operators, the users can experience poor Quality of Service (QoS), bad Quality of Experience (QoE) etc. Generally, poor QoS issues are faced due to poor network planning, inappropriate scheduling mechanisms utilized by the operators, and problems in core network, access network, last mile, content delivery network and even users' own home networks. Due to poor QoS, better data connectivity may not be available to the users at different time instances and at different geographic locations. It would be understood that QoE amounts to the overall experience received by the user at any given instance or at any particular geographical location.

[0014] Therefore, for an adhoc or even a preplanned schedule, a user may not know what will be his experience at a particular time instance and at a particular location for a multimedia event. The multimedia event may be understood as an internet based service provided to the user by an operator. For illustration, consider a scenario where an operator provides internet based services to its users through various network connections, such as Wi-Fi network connections over asymmetric digital subscriber line (ADSL) broadband network connections, third Generation (3G) network connections, Long Term Evolution (LTE) network connections, and ADSL broadband network connections. For example, a user may be registered with the operator. The user may subscribe to a Wi-Fi network connection over an ADSL broadband network connection, a 3G network connection, and an ADSL broadband network connections provided by the operator. In one example, the user may have to attend a video conference from his home. For this video conference, the user may connect his mobile phone to the Internet through the Wi- Fi network connection and use a video conferencing application installed on his mobile phone. Alternately, the user may establish a video call for the video conference using the 3G network connection or the ADSL broadband network connections. Choosing an option from amongst the several options available to the user is based on the user's preference. At best, the user's preference may be based on his past experience. For example, the user may have experienced faster Wi-Fi connectivity in the past, therefore, the user may decide to use the Wi-Fi network connection instead of the 3G network connection or the ADSL broadband network connections. However, while making such a decision, the user has no visibility into what possible network issues may arise during the video conference when he uses the Wi-Fi network connection. For example, there could be a possibility that on that particular day, the bandwidth may become low, for example, due to unfavorable weather conditions or interference or maintenance scheduled by the operator and hence the user may experience poor QoS.

[0015] Further, there can be situations when a better alternative is available to the user but due to ignorance, he suffers by continuing to use a poor network connection at that particular time. Furthermore, whenever the user faces a problem accessing the internet based service through a network connection, the user can contact the operator to report the problem. The operator's helpdesk agent can try to help the user based on availability of tools and information. However, by the time problem may get resolved, the user may have already suffered a poor QoS and QoE. Moreover, if the user faces problem during a real time event, for example, a video conference, the event may not happen again. It may also be possible that the helpdesk agent may not have the visibility in to various network connections option available to the user, therefore, the helpdesk agent may not be aware of a better alternative for the user.

[0016] Therefore, as described, the reasons for which users may experience a poor QoS may be several, for example, poor network planning and lack of visibility into what possible network issues may arise during a scheduled event. Due to such reasons, the users can experience poor QoE.

[0017] According to an implementation of the present subject matter, systems and methods for ranking based prediction of network connections for a multimedia event are described herein. In one embodiment of the present subject matter, the systems and the methods, for carrying out a multimedia event, rank a plurality of network connections, subscribed by a user, based on predictive ranking rules in near real time. Based on the ranking, the systems and the methods can predict and inform the user which can be the most suitable network connection option from amongst the plurality of network connections for the user's expected QoS and QoE for the upcoming multimedia event. The systems and the methods can also predict a user device from various user devices, that the user may be using, associated with the plurality of network connections for carrying out the upcoming multimedia event in near real time using the predicted network connection.

[0018] Further, assured QoS is provided to the user based on prediction of a possible degradation of QoE and hence actions can be taken before hand rather than waiting for the problem to occur. The action may be understood as using the most suitable network connection for the multimedia event. Further, since the most suitable network connection is predicted for carrying out the multimedia event, it is unlikely that the user will face any problem during the multimedia event. Therefore, the user does not have to contact operator's helpdesk agent to report any problem and as a result, number of calls made by the user to the operator reduces. Due to reduction in the number of calls made to the operator's helpdesk for reporting problems there is cost savings and profitability is improved. Since the user does not have to spend time and effort in contacting the operator's helpdesk agent, it leads to an increase in user's satisfaction.

[0019] In one implementation of the present subject matter, an operator providing communication network connectivity to a user may provide various internet based services, such as VOD, MOD, video conferencing, web surfing, conference communications, online gaming, and real time social networking to the user. It would be understood by those skilled in the art that to obtain connectivity to a communication network, users generally subscribe to an operator through which various internet based services can be availed. For example, a user 'X' may subscribe to an operator 'A' for availing a Wi-Fi network connection over an ADSL broadband network connection and a 3G network connection services. Similarly, another user Ύ' may subscribe to the operator 'A' for obtaining connectivity to a LTE network connection and an ADSL broadband network connection. In yet another example, the user 'Z' may subscribe to the operator 'A' for availing the Wi-Fi network connection, the 3G network connection, the LTE network connection, and the ADSL broadband network connection services. It would be understood by those skilled in the art that an operator may provide connectivity to a user with various network connections to communicate with other users through their user devices.

[0020] According to an implementation, for ranking the network connections, initially, a plurality of network connections, subscribed by a user, may be determined. In one implementation, the plurality of network connections, subscribed by the user, may be determined from an operator providing various internet based services to the user through the network connections. In another implementation, details of the network connections subscribed by the user may be obtained from the user itself. Examples of the network connections may include a Wi-Fi network connection over an ADSL broadband network connection, a 3G network connection, a LTE network connection, and an ADSL broadband network connection. In one example, the user may be subscribed to the 3G network connection, the ADSL broadband network connection and the LTE network connection, provided by the operator. Further, the multimedia event may include VOD, MOD, video conferencing, web surfing, conference communications, online gaming, and real time social networking.

[0021] Although, it has been described that one operator provides the network connections and internet based services to a user to access the internet based services, more than one operator may provide the network connections to the user to access the internet based services. For example, the user 'X' may subscribe to the operator 'A' for availing a Wi-Fi network connection and may subscribe to an operator 'B' for availing a 3G network connection.

[0022] Upon determining the network connections subscribed by the user, network service and device parameters pertaining to the determined network connections may be received from one or more data sources. In one example, the one or more data sources may include the user, the operator, the user devices and the like. Further, the network service and device parameters may be indicative of information relating to the multimedia event and the plurality of network connections. For example, the network service and device parameters may include a calendar data comprising details of the multimedia event. The details of the multimedia event may include day and time when the multimedia event is scheduled, location from where the multimedia event is scheduled to take place, and uniform resource locator (URL) of one or more websites to be used during the multimedia event. In one example, the calender data may be received from the user. The user may provide the calender data through one or more user devices. For example, the calender data provided by the user may depict that the user has to attend a video conference using Skype™ from his home on October 24, 2013 at 7:00 PM.

[0023] The network service and device parameters may further include device data of various user devices that the user may be using. For example, the device data may include a type of each of the user devices, performance statistics of the user devices, and one or more network connections from amongst the network connections available on each user device. The device data may be received from a billing server at the operator or from the user. In one example, the device data may represent that the user is using a tablet with a 3G network connection, a Smartphone with a LTE network connection, and a Wi-Fi router and an IPTV with an ADSL broadband network connection.

[0024] The network service and device parameters may further include historical data comprising historical usage and performance data about the user, network connections, and the internet based service corresponding to the multimedia event at certain locations and/ or time of the day. The historical data may be received from an analytics engine at the operator. The network service and device parameters may also include a connection data comprising performance data, error and exceptions data, planned and unplanned maintenance information, connection speed, a frame error rate, and a packet drop rate of each of the plurality of network connections.

[0025] Although, it has been described the network service and device parameters includes the calendar data, the device data, and the historical data, the network service and device parameters may also include additional data, such as signal strength, quality of service (QoS), quality of experience (QoE), service validity and data plans of the network connections, weather information in user's location, degree of congestion in the network connections, interference level in the network connections, availability of channels, and so on.

[0026] Thereafter, the network service and device parameters may be aggregated for each of the network connections. Aggregation may be understood as grouping the network service and device parameters corresponding to each network connection. In one implementation, the network service and device parameters may be aggregated based on a type of network connection. For example, if the network connections subscribed by the user are the 3G network connection and the LTE network connection, the network service and device parameters are grouped for the 3G network connection and the LTE network connection.

[0027] Once the network service and device parameters are aggregated, the network connections may be ranked based on at least one predictive ranking rule on the aggregated network service and device parameters to predict at least one network connection from amongst the network connections as the most suitable network connection for carrying out the multimedia event along with an appropriate user device. The predictive ranking rule may be indicative of criteria for ranking the network connections. In one implementation, the predictive ranking rules may be defined by the operator.

[0028] The predictive ranking rules may include a data quota rule, a tariff plan rule, a

QoS rule, a QoE rule, a connection speed rule, a data speed rule, a frame error rate rule, and a packet drop rate rule. The data quota rule relates to determining whether data quota of each of the network connections is enough for carrying out a multimedia event. The tariff plan rule relates to determining which of the tariff plans of the network connections is cost effective. The QoS rule relates to determining whether QoS for each of network connections is acceptable or better than a pre-defined QoS threshold. The QoE rule relates to determining whether QoE for each network connection is acceptable or better than a pre-defined QoE threshold. The connection speed rule relates to determining whether connection speed of each network connections is above a connection speed threshold level for using a particular service, for example, IPTV or video conferencing. In one example, the connection speed threshold level may be specified for the user's service level agreement (SLA). The data speed rule relates to determining whether data speed of each network connections is above a data speed threshold level. Further, the frame error rate rule relates to determining whether frame error rate rule of each network connection is below a pre-defined frame error rate threshold. Furthermore, the packet drop rate rule relates to determining whether packet drop rate of each network connections is below a pre-defined packet drop rate threshold.

[0029] As mentioned above, the network connections may be ranked based on at least one predictive ranking rule, therefore, in one example, the network connections may be ranked based on the data quota rule. In another example, the network connections may be ranked based on the data quota rule, the quality rule, the connection speed rule, the data speed rule, and the frame error rate rule.

[0030] In one implementation, the ranking may be based on a single predictive ranking rule. For example, where the ranking is done based on the QoS rule, the network connection from amongst the plurality of network connections whose QoS is acceptable or better than the pre-defined QoS threshold carrying out the multimedia event is assigned a first rank. [0031] In another implementation, the ranking may be based on multiple predictive ranking rules, such as the data quota rule, the QoS rule, the connection speed rule, the data speed rule, and the frame error rate rule. The network connection which satisfies most number of predictive ranking rules may be assigned a first rank, the network connection which satisfies second most number of predictive ranking rules may be assigned a second rank, and so on. Further, in one example, if two network connections satisfy same number of predictive ranking rules, then both the network connections may be assigned a same rank and left to the user to select.

[0032] In an example where the ranking is done based on the data quota rule, the QoS rule, the connection speed rule, the data speed rule, and the frame error rate rule. The network connection whose data quota is enough for carrying out the multimedia event, for which QoS is acceptable or better than the pre-defined QoS threshold, whose connection speed is above the connection speed threshold level, whose data speed is above the data speed threshold level, and for which frame error rate is below the pre-defined frame error rate threshold level at that instance of time, is assigned a first rank. In the present example, a second rank may be assigned to network connection that satisfies second highest number of rules and so on.

[0033] Accordingly, in one example, the predictive ranking rules may define that a video call should be made through the network connection that has enough data quota, for which the frame error rate is below the pre-defined frame error rate threshold level, for which QoS is acceptable or better than the pre-defined threshold, whose connection speed is above the connection speed threshold level, and whose data speed is above the data speed threshold level. As evident, since the predictive ranking rules are based on the network service and device parameters corresponding to the network connections, the result of the rules, i.e., the ranking of the network connections may change with time as the network service and device parameters vary with time.

[0034] Referring again to the previous example, where a user is subscribed to the 3G network connection, the LTE network connection, and the ADSL broadband network connection for using the tablet with the 3G network connection, the Smartphone with the LTE network connection, and the Wi-Fi router and the IPTV with the ADSL broadband network connection. In that case, the network service and device parameters corresponding to the network connections, i.e., the 3G network connection, the LTE network connection, the ADSL broadband network connection, and the user devices, i.e., the Smartphone, the tablet, the Wi-Fi router, and the IPTV are received from various data sources. The network service and device parameters are further aggregated and the network connections are ranked based on applying the predictive ranking rules.

[0035] Consider a scenario where enough data quota is available in the 3G data plan but not in LTE data plan and ADSL data plan for an upcoming video conference. Further, tariff plan for the 3G network connection is more economical in comparison to tariff plan for the LTE network connection and the ADSL broadband network connection. As mentioned earlier, the network service and device parameter may include the device data comprising performance statistics of the user devices that the user may be using. Therefore, based on the device data, it may be observed that picture sometimes freezes while the user is watching IPTV. As a result, it may be found out that using the ADSL broadband network connection could lead to QoE degradation during the upcoming internet based video conference which is done using one of the three services. Therefore, based on this comparison, the 3G network connection may be assigned a first rank, the LTE network connection may be assigned a second rank, and the ADSL broadband network connection may be assigned a third rank. Based on the ranking, a ranked network table may be generated in near real time. The ranked network table may depict ranking of the plurality of network connections, subscribed by the user. Thereafter, based on the ranked network table, the 3G network connection may be predicted as the most suitable network connection for carrying out the upcoming multimedia event.

[0036] In one implementation, the network connection with first rank may be selected automatically for the user, for the video conference. In another implementation, the operator may send an alert to the user before the meeting, i.e., before the video conference, with the ranked network table. For example, the operator may send a message, say an unstructured supplementary services data (USSD) message on a user device. The message may contain the ranked network table. The user may then manually select a network connection with first rank for the video conference so that the video conference happens without any glitches.

[0037] Further, a user device from amongst the user devices associated with the plurality of network connections may be determined or predicted for carrying out the multimedia event using the at least one predicted network connection. In one implementation, the user device may be predicted based on the aggregated network service and device parameters. As mentioned above, the network service and device parameters may include device data comprising information of various user devices that the user may be using. For example, the user may be using two Smartphones, one with High-definition (HD) camera and the other with video graphics array (VGA) camera. Therefore, the user may be given a suggestion, based on the ranking, to use the Smartphone with the VGA camera, since the Smartphone with HD camera may require higher bandwidth as compared to the Smartphone with VGA camera.

[0038] Since, the most suitable network connection is predicted for carrying out the multimedia event, user's expected QoS and QoE is met. Further, since the most suitable network connection is predicted for carrying out the upcoming multimedia event in near real time, it is unlikely that the user will face any problem during the multimedia event. Therefore, the user does not have to contact operator's helpdesk agent to report any problem and as a result number of calls made by the user to the operator reduces. Due to reduction in the number of calls made to the operator's helpdesk for reporting problems there is cost savings and profitability is improved for the operator. Further, due to the predictive service and since the user does not have to spend time and effort in contacting the operator's helpdesk agent, it leads to an increase in user's satisfaction.

[0039] It should be noted that the description merely illustrates the principles of the present subject matter. It will thus be appreciated that those skilled in the art will be able to devise various arrangements that, although not explicitly described herein, embody the principles of the present subject matter and are included within its spirit and scope. Furthermore, all examples recited herein are principally intended expressly to be only for pedagogical purposes to aid the reader in understanding the principles of the invention and the concepts contributed by the inventor(s) to furthering the art, and are to be construed as being without limitation to such specifically recited examples and conditions. Moreover, all statements herein reciting principles, aspects, and embodiments of the invention, as well as specific examples thereof, are intended to encompass equivalents thereof.

[0040] The manner in which the systems and methods shall be implemented has been explained in details with respect to the Figures 1 and 2. While aspects of described systems and methods can be implemented in any number of different computing systems, transmission environments, and/or configurations, the embodiments are described in the context of the following exemplary system(s).

[0041] It will also be appreciated by those skilled in the art that the words during, while, and when as used herein are not exact terms that mean an action takes place instantly upon an initiating action but that there may be some small but reasonable delay, such as a propagation delay, between the initial action and the reaction that is initiated by the initial action. Additionally, the word "connected" and "coupled" is used throughout for clarity of the description and can include either a direct connection or an indirect connection.

[0042] Figure 1 illustrates a network environment 100, implementing a predictive ranking system 102, for ranking network connections for carrying out a multimedia event, in accordance with an embodiment of the present subject matter. The predictive ranking system 102 described herein, can be implemented in any network environment comprising a variety of network devices, including routers, bridges, servers, computing devices, storage devices, etc.

[0043] In one implementation, the predictive ranking system 102 may be deployed at an operator's premise. The operator, such as an internet service provider, may be providing various internet based services, such as VOD, MOD, video conferencing, web surfing, online gaming, and real time social networking to a user, such as a subscriber, through the network connections. In another implementation, the predictive ranking system 102 may be deployed at a third-party provider's premise. The third-party provider may be the one who may provide a ranked list of network connections, for a multimedia event, to the user or to the operator as a paid service. In yet another implementation, the predictive ranking system 102 may be deployed as a residential gateway at the user's home location. At an edge of an access network, a part of network infrastructure is referred to as a residential gateway.

[0044] In one implementation the predictive ranking system 102 is connected to one or more user devices 104-1 , 104-2, 104-3, 104-N, individually and commonly referred to as user device(s) 104 hereinafter, through a network 106. The user devices 104 may include multiple applications that may be running to perform several functions, as required by different users. [0045] The predictive ranking system 102 can be implemented as a variety of servers and communication devices. The communication devices that can implement the described method(s) include, but are not limited to, central directory servers, database server, web server, application server, and the like. The predictive ranking system 102 may also be implemented as a computing device, such as a laptop computer, a desktop computer, a notebook, a workstation, a mainframe computer, a server, and the like.

[0046] The user devices 104 may be implemented as, but are not limited to, desktop computers, hand-held devices, laptops or other portable computers, tablet computers, mobile phones, PDAs, Smartphones, and the like. Further, the user devices 104 may include devices capable of exchanging data to provide connectivity to different communicating devices and computing systems. Such devices may include, but are not limited to, data cards, mobile adapters, wireless (Wi-Fi) routers, a wireless modem, a wireless communication device, a cordless phone, a wireless local loop (WLL) station, internet protocol televisions (IPTVs) set-top box, smart televisions (smart TVs), and the like. In one implementation, the user may avail network connections, from the operator, on more than one user devices 104. The network connections may include a Wi-Fi network connection over an ADSL broadband network connection, a 3G network connection, a LTE network connection, and an ADSL broadband network connection.

[0047] The network 106 may be a wireless or a wired network, or a combination thereof. The network 106 can be a collection of individual networks, interconnected with each other and functioning as a single large network (e.g., the internet or an intranet). Examples of such individual networks include, but are not limited to, Global System for Mobile Communication (GSM) network, Universal Mobile Telecommunications System (UMTS) network, Personal Communications Service (PCS) network, Time Division Multiple Access (TDMA) network, Code Division Multiple Access (CDMA) network, Next Generation Network (NGN), Public Switched Telephone Network (PSTN), and Integrated Services Digital Network (ISDN). Depending on the technology, the network 106 includes various network entities, such as gateways, routers; however, such details have been omitted for ease of understanding.

[0048] In one implementation, the predictive ranking system 102 includes processor(s) 108. The processor 108 may be implemented as one or more microprocessors, microcomputers, microcontrollers, digital signal processors, central processing units, state machines, logic circuitries, and/or any devices that manipulate signals based on operational instructions. Among other capabilities, the processor(s) is configured to fetch and execute computer-readable instructions stored in the memory.

[0049] The functions of the various elements shown in the figure, including any functional blocks labeled as "processor(s)", may be provided through the use of dedicated hardware as well as hardware capable of executing software in association with appropriate software. When provided by a processor, the functions may be provided by a single dedicated processor, by a single shared processor, or by a plurality of individual processors, some of which may be shared. Moreover, explicit use of the term "processor" should not be construed to refer exclusively to hardware capable of executing software, and may implicitly include, without limitation, digital signal processor (DSP) hardware, network processor, application specific integrated circuit (ASIC), field programmable gate array (FPGA), read only memory (ROM) for storing software, random access memory (RAM), non-volatile storage. Other hardware, conventional and/or custom, may also be included.

[0050] Also, the predictive ranking system 102 includes interface(s) 1 10. The interfaces

1 10 may include a variety of software and hardware interfaces that allow the system 102 to interact with the entities of the network 106, or with each other. The interfaces 110 may facilitate multiple communications within a wide variety of networks and protocol types, including wire networks, for example, LAN, cable, etc., and wireless networks, for example, WLAN, cellular, satellite -based network, etc.

[0051] In another embodiment of the present subject matter, the predictive ranking system 102 may also include a memory 1 12. The memory 1 12 may be coupled to the processor 108. The memory 1 12 can include any computer-readable medium known in the art including, for example, volatile memory, such as static random access memory (SRAM) and dynamic random access memory (DRAM), and/or non-volatile memory, such as read only memory (ROM), erasable programmable ROM, flash memories, hard disks, optical disks, and magnetic tapes.

[0052] Further, the predictive ranking system 102 may include module(s) 114 and data 1 16. The modules 1 14 and the data 1 16 may be coupled to the processors 108. The modules 1 14, amongst other things, include routines, programs, objects, components, data structures, etc., which perform particular tasks or implement particular abstract data types. The modules 1 14 may also be implemented as, signal processor(s), state machine(s), logic circuitries, and/or any other device or component that manipulate signals based on operational instructions.

[0053] Further, the modules 1 14 can be implemented in hardware, instructions executed by a processing unit, or by a combination thereof. The processing unit can comprise a computer, a processor, a state machine, a logic array or any other suitable devices capable of processing instructions. The processing unit can be a general-purpose processor which executes instructions to cause the general-purpose processor to perform the required tasks or, the processing unit can be dedicated to perform the required functions.

[0054] In another aspect of the present subject matter, the modules 1 14 may be machine- readable instructions (software) which, when executed by a processor/processing unit, perform any of the described functionalities. The machine-readable instructions may be stored on an electronic memory device, hard disk, optical disk or other machine -readable storage medium or non-transitory medium. In one implementation, the machine -readable instructions can be also be downloaded to the storage medium via a network connection.

[0055] In an implementation, the module(s) 114 includes a determination module 122, an aggregation module 124, a ranking module 126, and other module(s) 128. The other module(s) 128 may include programs or coded instructions that supplement applications or functions performed by the predictive ranking system 102. In said implementation, the data 1 16 includes parameter data 130 and other data 132. The other data 132 amongst other things, may serve as a repository for storing data that is processed, received, or generated as a result of the execution of one or more modules in the module(s) 114. Although the data 1 16 is shown internal to the predictive ranking system 102, it may be understood that the data 1 16 can reside in an external repository (not shown in the figure), which may be coupled to the predictive ranking system 102. The predictive ranking system 102 may communicate with the external repository through the interface(s) 110 to obtain information from the data 116.

[0056] According to an implementation, the determination module 122 may determine a plurality of network connections, subscribed by a user. In one implementation, the determination module 122 may determine the plurality of network connections, subscribed by the user, from at least one of the user and the operator.

[0057] Upon determination of the network connections, the determination module 122 receives network service and device parameters pertaining to the network connections from one or more data sources, such as the user, one or more user devices 104, the operator, etc. Further, the network service and device parameters may be indicative of information relating to the multimedia event and the plurality of network connections. Few examples of the network service and device parameters may include a calendar data, a device data of the user devices 104 associated with the network connections, a connection data pertaining to each network connection, a data quota of each network connection, a tariff plan of each network connection, quality of service (QoS) for each network connections, and quality of experience (QoE) for each network connection.

[0058] According to an implementation, the determination module 122 may store the received network service and device parameters within the parameter data 130. The parameter data 130 may be updated, when required. For example, new network service and device parameters may be added into the parameter data 130, existing network service and device parameters may be modified, or non-useful network service and device parameters may be deleted from parameter data 130. Few exemplary network service and device parameters received by the determination module 122 from various data sources are depicted in Table 1 (provided below).

TABLE 1

may be used for the

multimedia event

Historical data Historical usage and Analytics engine at the performance data about the operator

user, the network connections,

and the internet based service

corresponding to the

multimedia event at certain

locations, time and day

Weather data Weather information in user's Web service of Weather location at time of the monitoring service multimedia event

Data quota Available data quota and tariff User or the operator

plan of each of the plurality of

network connections

Connection data Performance data, error and Operator

exception data, overall

performance, planned and

unplanned maintenance

information, connection speed,

data speed, frame error rate,

and packet drop rate rule

User's home network Upload speed, download One or more user devices performance speed, retransmission rate,

packet drop rate, and number

of user devices attached with

the user's home network

Access network data Access network associated Subscriber data system at with each network connection the operator

Device data User devices that the user is User or the operator

using, network connections

available in each user device,

model number, and network

statistics Content delivery network Information like Ping, Trace Network monitoring information route, etc system at the operator

QoS of Last mile connection QoS of Last mile connection Network monitoring associated with the network system at the operator connections

[0059] As shown in the Table 1 above, the network service and device parameters include the calendar data. In one example, the calendar data may depict that the user has to attend a video conference using Skype™ from his home on October 24, 2013 at 7:00 PM. It may be understood from the example that the multimedia event is a video conference. Further, the network service and device parameters include weather data. In an example, the weather data may indicate that there is a mild thunderstorm and temperature is 30° Celsius.

[0060] Further, it is shown that the network service and device parameters include historical data that may include performance of each network connection in past two months, congestion rate of each network connection in past three months, experience of the user with the operator, and the like. Furthermore, the network service and device parameters includes data quota of each of the plurality of network connections. For example, if the user is subscribed to the 3G network connection and the LTE network connection, then available data quota of the 3G network connection may be 1 gigabytes (GB) and data quota of the LTE network connection may be 500 megabytes (MB).

[0061] The network service and device parameters may also include user's home network performance. The user's home network may be a residential gateway. In one example, one or more user devices 104 may provide this data to the determination module 122 via user's devices via technical report (TR) protocols or open mobile alliance (OMA) device management (DM) (OMA-DM) protocol. The user's home network performance may also be received based on a custom application installed on one or more user devices 104. Further, in one example, upload speed may be 1 megabits per second (Mbps).

[0062] Also, the network service and device parameters may include access network data. The access network data represents the access network associated with each network connection. For example, the LTE and the 3G network connection is associated with wireless transmission, and the ADSL broadband connection is on copper. It is to be understood that the network service and device parameters described above are only exemplary network service and device parameters, it should not be construed as a limitation.

[0063] According to an implementation, the aggregation module 124 may aggregate the network service and device parameters for each of the plurality of network connections. Aggregation may be understood as grouping the network service and device parameters corresponding to each of the plurality of network connections. In one implementation, the aggregation is performed based on at least a type of network connection. Consider an example where the user is subscribed to the 3G network connection, the ADSL broadband network connection, and the LTE network connection, then the network service and device parameters are grouped for the 3G network connection, the ADSL broadband network connection, and the LTE network connection.

[0064] According to an example, the aggregated data for the LTE connection, the ADSL broadband network connection, and the 3G connection is depicted in Table 2 (provided below).

TABLE 2

Frame error 10 40 5

Tablet, Wi-Fi Router

Smartphone and IPTV

Attached user devices 'A' Smartphone 'B'

[0065] Once the network service and device parameters are aggregated, the ranking module 126 may rank the plurality of network connections based on at least one predictive ranking rule on the aggregated network service and device parameters. The predictive ranking rules may be indicative of criteria for ranking the plurality of network connections. In one implementation, the predictive ranking rules may be defined by the operator. The ranking module 126 may then predict at least one network connection from amongst the plurality of network connections for carrying out the upcoming multimedia event in near real time.

[0066] In one implementation, the predictive ranking rules may include a data quota rule, a tariff plan rule, a QoS rule, a QoE rule, a connection speed rule, a data speed rule, a frame error rate rule, and a packet drop rate rule. The data quota rule relates to determining whether data quota of each of network connections is enough for carrying out the multimedia event. The tariff plan rule relates to determining whether tariff plan of each network connection is expensive. The QoS rule relates to determining whether QoS for each of network connections is acceptable or better than a pre-defined QoS threshold. The QoE rule relates to determining whether QoE for each network connection is acceptable or better than a pre-defined QoE threshold. The connection speed rule relates to determining whether connection speed of each network connection is above a connection speed threshold level. In one example, the connection speed threshold level may be specified for the user's service level agreement (SLA). The data speed rule relates to determining whether data speed of each network connection is above a data speed threshold level. Further, the frame error rate rule relates to determining whether frame error rate rule of each of network connection is below a pre-defined frame error rate threshold. Furthermore, the packet drop rate rule relates to determining whether packet drop rate of each of the plurality of network connections is below a pre-defined threshold. Further, it should be appreciated by those skilled in the art, that the network service and device parameters are dynamic in nature and change with time and/or geographical location. Based on the same, the predictive ranking rules may also get updated. [0067] In a scenario where three network connections are to be ranked based on multiple predictive ranking rules, the ranking module 126 may assign a first rank to the network connection which satisfies most number of predictive ranking rules. Further, the ranking module 126 may assign a second rank to the network connection which satisfies second most number of predictive ranking rules, and the ranking module 126 may assign a third rank to the network connection which satisfies third most number of predictive ranking rules. Further, the ranking module 126 may assign a same rank to network connections which satisfy same number of predictive ranking rules.

[0068] In one example, if the network connections are to be ranked based on the data quota rule, the tariff plan rule, the QoS rule, and the frame error rate rule, then as a result of these rules, the ranking module 126 may assign first rank, i.e., a highest rank to a network connection from amongst the plurality of network connections whose data quota is enough for carrying out the multimedia event, for which frame error rate is below the pre-defined frame error rate threshold level, and which is most cost effective for a given multimedia event. Similarly, the ranking module 126 ranks each of the plurality of network connections for carrying out the multimedia event. Accordingly, in the above example, the predictive ranking rules may define that a video call should be made through the network connection that has enough data quota, which is cost effective, and for which frame error rate is below the pre-defined frame error rate threshold level, along with good QoS.

[0069] Taking a scenario where available data quota is enough for the video conference for the 3G network connection, however, it is not enough for the LTE network connection. Further, tariff plan for the 3G network connection is more economical in comparison to tariff plan for the LTE network connection. Furthermore, QoS for the 3G network connection is acceptable or better than the pre-defined QoS threshold, and for the LTE network connection, the QoS is degrading. As a result, it may be found out that using the LTE network connection could lead to QoE degradation during the video conference. Therefore, based on this comparison, the ranking module 126 may give first rank to the 3G network connection and second rank to the LTE network connection. Based on the ranking, the ranking module 126 may generate a ranked network table. The ranked network table may depict ranking of the plurality of network connections, subscribed by the user. Thereafter, based on the ranked network table, the ranking module 126 predicts the 3G network connection as the most suitable network connection for carrying out the upcoming multimedia event.

[0070] In one implementation, the ranking module 126 may select the network connection with first rank for the user, for the video conference. In another implementation, the operator may send an alert to the user before the meeting, i.e., before the video conference, with the ranked network table. For example, the operator may send a message, say an unstructured supplementary services data (USSD) message on a user device. The message may contain the ranked network table. The user may then select a network connection based on the ranking, say the user may select the network connection with first rank for the video conference so that the video conference happens without any glitches.

[0071] Consider a scenario where the user has a tablet with a 3G network connection having moderate data plan subscription, a laptop with Ethernet network connection and a Wi-Fi network connection, a Smartphone with LTE network connection having minimal data plan subscription, and a Wi-Fi router and IPTV with ADSL broadband network connection having unlimited data plan subscription. On Monday, October 24, 2013 at 7 PM, the user has to attend a video conference from his home. For this video conference, the user may use a video conferencing application.

[0072] Further, the network service and device parameters may depict that the user has used his laptop with high-definition (HD) camera for similar video conferences in the past, the video conferences normally lasts for 2 hours, it requires around 500 kilobits per second (KBps) bandwidth to support good video and voice on the laptop. Further, the network service and device parameters may indicate that average Wi-Fi network connection throughput is 1 megabits per second (MBps) during this time on any given day and has moderate network congestion, the LTE and 3G network connections are capable of delivering throughput similar to Wi-Fi network connection during this time of the day. The network service and device parameters may also indicate that subscription of LTE network connection is 1.5 times expensive as compared to subscription of 3G network connection, IPTV is not turned ON during this time of the day, sometimes a VoIP call is made during this time, QoS of the ADSL broadband network connection has degraded in user's area in past couple of days, core network does not report any abnormalities, and there is no planned maintenance in operator's wireless and wireline network. [0073] Referring again to the previous scenario, on October 24, 2013 around 6:30 PM, a family member of the user is watching IPTV and observing that picture sometimes freezes. The IPTV set-top-box (STB) periodically, for example, after every 15 minutes sends performance stats back to the operator. Based on the predictive ranking rules on the network service and device parameters, it may be determined that using the ADSL broadband network connection could lead to QoE degradation during the video conference. To avoid any problems during the video conference, the operator may send an alert to the user at 6:45 PM with a ranked network table. The ranked network table may depict that the 3G network connection is given first rank, the LTE network connection is given second rank, and the ADSL broadband network connection is given third rank. Based on the ranked network table, the user may decide to use the 3G network connection instead of the ADSL broadband network connection. Therefore, the video conference happens without any glitches. Meanwhile, the operator can troubleshoot the degrading ADSL broadband network connection and eventually fix the same.

[0074] Further, the ranking module 126 may determine or predict a user device 104 from amongst the user devices 104 for carrying out the multimedia event using the predicted network connection. In one implementation, the ranking module 126 may determine the user device 104 based on the aggregated network service and device parameters. As mentioned above, the network service and device parameters may include device data comprising information of user devices which the user may be using. For example, the user may be using two Smartphones. One with HD camera and the other with VGA camera. Therefore, the user may be given a suggestion to use the Smartphone with VGA camera, since the Smartphone with HD camera may require higher bandwidth as compared to the Smartphone with VGA camera.

[0075] Although the foregoing description has been described with reference to one operator providing the network connection and internet based services to its user, it is well appreciated that multiple operators may provide the network connections to the user to access different internet based services. For example, the user may subscribe to an operator 'A' for availing a Wi-Fi network connection and the user may subscribe to an operator 'B' for availing a 3G network connection.

[0076] According to the present subject matter, the predictive ranking system 102 can predict and inform the user or the operator which can be the most suitable network connection option from amongst the plurality of network connections for the user's expected QoS and QoE for the multimedia event when accessed from a particular user device.

[0077] Further, assured QoS is provided to the user based on prediction of a possible degradation of QoE and hence actions can be taken before hand rather than waiting for the problem to occur. The action may be understood as using the most suitable network connection for the multimedia event. Further, since the most suitable network connection is predicted for carrying out the multimedia event, it is unlikely that the user will face any problem during the multimedia event. Therefore, the user does not have to contact operator's helpdesk agent to report any problem and as a result, number of calls made by the user to the operator reduces. Due to reduction in the number of calls there is cost savings and profitability is improved. This also increases user's satisfaction. Furthermore, the operator can troubleshoot the degrading network connections and fix the same proactively.

[0078] Figure 2 illustrates a method 200 for ranking based prediction of network connections for carrying out a multimedia event, in accordance with an embodiment of the present subject matter. The order in which the method is described is not intended to be construed as a limitation, and any number of the described method blocks can be combined in any order to implement the method 200 or any alternative method. Additionally, individual blocks may be deleted from the method without departing from the spirit and scope of the subject matter described herein. Furthermore, the method can be implemented in any suitable hardware, software, firmware, or combination thereof.

[0079] The method(s) may be described in the general context of computer executable instructions. Generally, computer executable instructions can include routines, programs, objects, components, data structures, procedures, modules, functions, etc., that perform particular functions or implement particular abstract data types. The methods may also be practiced in a distributed computing environment where functions are performed by remote processing devices that are linked through a communications network. In a distributed computing environment, computer executable instructions may be located in both local and remote computer storage media, including memory storage devices.

[0080] A person skilled in the art will readily recognize that steps of the method(s) 200 can be performed by programmed computers. Herein, some embodiments are also intended to cover program storage devices or computer readable medium, for example, digital data storage media, which are machine or computer readable and encode machine-executable or computer- executable programs of instructions, where said instructions perform some or all of the steps of the described method. The program storage devices may be, for example, digital memories, magnetic storage media, such as a magnetic disks and magnetic tapes, hard drives, or optically readable digital data storage media. The embodiments are also intended to cover both communication network and communication devices to perform said steps of the method(s).

[0081] At block 202, the method 200 may include determining a plurality of network connections, subscribed by a user, for carrying out a multimedia event. The multimedia event may be one of internet based services, which includes VOD, MOD, video conferencing, web surfing, online gaming, and real time social networking. The network connections may include a Wi-Fi network connection over an ADSL broadband network connection, a 3G network connection, a LTE network connection, and an ADSL broadband network connection. In one example, the user may subscribe to the network connections provided by an operator. In one implementation, the network connections, subscribed by the user, may be determined from at least one of the user and the operator. In one implementation, the determination module 122 of the predictive ranking system 102 may determine the network connections, subscribed by the user, for carrying out the multimedia event.

[0082] At block 204, the method 200 may include receiving network service and device parameters pertaining to the plurality of network connections from one or more data sources. In one example, the one or more data sources may include the user, one or more user devices, the operator, etc. The network service and device parameters may include a calendar data, a device data of a plurality of user devices 104 associated with the plurality of network connections, a calendar data of the plurality of user devices 104, a connection data pertaining to each network connection, a data quota of each network connection, a tariff plan of each network connection, quality of service (QoS) for each network connection, and quality of experience (QoE) for each network connection. In one implementation, the determination module 122 may receive the network service and device parameters pertaining to the network connections from one or more data sources. [0083] At block 206, the method 200 may include aggregating the network service and device parameters for each of the plurality of network connections. In one example, the network service and device parameters may be aggregated based on a type of network connection. Aggregation may be understood as grouping the network service and device parameters corresponding to each network connection. Consider an example where the network connections subscribed by the user are the 3G network connection and the ADSL broadband network connection, then the network service and device parameters are grouped for the 3G network connection and the ADSL broadband network connection. According to an implementation, the aggregation module 124 may aggregate the network service and device parameters for each of the plurality of network connections.

[0084] At block 208, the method 200 may include ranking the plurality of network connections based on at least one predictive ranking rule on the aggregated network service and device parameters. The predictive ranking rules may be indicative of criteria for ranking the network connections. In one implementation, the predictive ranking rules may be defined by the operator. The predictive ranking rules may include a data quota rule, a tariff plan rule, a QoS rule, QoE rule, a connection speed rule, a data speed rule, a frame error rate rule, and a packet drop rate rule. In one implementation, the ranking module 126 may rank the network connections based on at least one predictive ranking rule on the aggregated network service and device parameters.

[0085] At block 210, the method 200 may include predicting at least one network connection from amongst the plurality of network connections for carrying out the multimedia event. Once the ranking of the plurality of network connections is done, a most suitable network connection from amongst the plurality of network connections is predicted for the upcoming event. For example, if first rank is assigned to the 3G network connection and second rank to the ADSL broadband network connection, then the 3G network connection may be predicted as the most suitable network connection for carrying out the upcoming multimedia event. In one implementation, the ranking module 126 may predict at least one network connection from amongst the network connections for carrying out the multimedia event.

[0086] At block 212, the method 200 may include identifying, based on the aggregated network service and device parameters, a user device from amongst a plurality of user devices for carrying out the multimedia event with the at least one network connection. The plurality of user devices may be associated with the network connections. Further, the network service and device parameters may include device data comprising information of user devices which the user may be using. For example, the user may be using two Smartphones. One with a LTE network connection and other with a 3G network connection. Further, the Smartphone with the LTE network connection may be having a HD camera and the other Smartphone with 3G network connection may be having a VGA camera. Furthermore, based on ranking, if first rank is assigned to the 3G network connection and second rank is assigned to the LTE network connection, then the user may be given a suggestion to use the Smartphone having VGA camera with the 3G network connection for carrying out the upcoming multimedia event, since the Smartphone with HD camera may require higher bandwidth as compared to the Smartphone with VGA camera. In one implementation, the ranking module 126 may determine the user device based on the aggregated network service and device parameters.

[0087] Although embodiments for ranking based prediction of network connections for multimedia event have been described in a language specific to structural features or method(s), it is to be understood that the invention is not necessarily limited to the specific features or method(s) described. Rather, the specific features and methods are disclosed as embodiments for ranking based prediction of network connections for multimedia event.

Claims

I/We claim:

1. A method for ranking based prediction of network connections for carrying out a multimedia event, the method comprising:

receiving network service and device parameters pertaining to a plurality of network connections, subscribed by a user, from one or more data sources, wherein the network service and device parameters are indicative of information relating to the multimedia event and the plurality of network connections;

aggregating the network service and device parameters for each of the plurality of network connections based on at least a type of network connection; and

ranking the plurality of network connections based on at least one predictive ranking rule on the aggregated network service and device parameters to predict at least one network connection from amongst the plurality of network connections for carrying out the multimedia event, wherein the at least one predictive ranking rule is indicative of criteria for ranking the plurality of network connections.

2. The method as claimed in claim 1 further comprising determining the plurality of network connections, subscribed by the user, for carrying out the multimedia event from at least one of the user and an operator.

3. The method as claimed in claim 1 , wherein the method further comprises predicting, based on the aggregated network service and device parameters, a user device (104) from amongst a plurality of user devices (104) associated with the plurality of network connections for carrying out the multimedia event using the at least one predicted network connection.

4. The method as claimed in claim 1 , wherein network service and device parameters includes a calendar data, a device data of a plurality of user devices (104) associated with the plurality of network connections, a connection data pertaining to each of the plurality of network connections, a data quota of each of the plurality of network connections, a tariff plan of each of the plurality of network connections, quality of service (QoS) for each of the plurality of network connections, and quality of experience (QoE) for each of the plurality of network connections.

5. The method as claimed in claim 4, wherein the calendar data includes details of the multimedia event, wherein the details of the multimedia event comprises day and time when the multimedia event is scheduled, location from where the multimedia event is scheduled to take place, and uniform resource locator (URL) of one or more websites to be used during the multimedia event.

6. The method as claimed in claim 4, wherein the device data of the plurality of user devices (104) includes a type of each of the plurality of user devices (104) and one or more network connections from amongst the plurality of network connections available on each of the plurality of user devices (104).

7. The method as claimed in claim 4, wherein the connection data includes performance data of each of the plurality of network connections, error and exceptions data related to each of the plurality of network connections, planned and unplanned maintenance information of each of the plurality of network connections, connection speed of each of the plurality of network connections, a frame error rate of each of the plurality of network connections, and a packet drop rate of each of the plurality of network connections.

8. The method as claimed in claim 1, wherein the ranking based on predictive ranking rules comprises one or more of:

determining an available data quota of each of the plurality of network connections;

determining a connection speed of each of the plurality of network connections; determining a data speed of each of the plurality of network connections; determining a frame error rate rule of each of the plurality of network connections;

determining a packet drop rate of each of the plurality of network connections; and

determining a quality of experience (QoE) for each of the plurality of network connections.

9. The method as claimed in claim 1 , wherein the ranking based on predictive ranking rules comprises determining a tariff plan associated with each of the plurality of network connections.

10. The method as claimed in claim 1 , wherein the ranking based on predictive ranking rules comprises determining a quality of service (QoS) of each of the plurality of network connections.

1 1. A predictive ranking system (102) for predicting network connections, based on ranking, for carrying out a multimedia event, the predictive ranking system (102) comprising: a processor (108);

a determination module (122) coupled to the processor (108) to:

receive network service and device parameters pertaining to a plurality of network connections, subscribed by a user, from one or more data sources, wherein the network service and device parameters are indicative of information relating to the multimedia event and the plurality of network connections;

an aggregation module (124) coupled to the processor (108) to:

aggregate the network service and device parameters for each of the plurality of network connections based on at least a type of network connection; and

a ranking module (126) coupled to the processor (108) to:

rank the plurality of network connections based on at least one predictive ranking rule on the aggregated network service and device parameters to predict at least one network connection from amongst the plurality of network connections for carrying out the multimedia event, wherein the at least one predictive ranking rule is indicative of criteria for ranking the plurality of network connections.

12. The predictive ranking system (102) as claimed in claim 1 1 , wherein the ranking module (126) further predicts, based on the aggregated network service and device parameters, a user device (104) from amongst a plurality of user devices (104) associated with the plurality of network connections for carrying out the multimedia event using the at least one predicted network connection.

13. The predictive ranking system (102) as claimed in claim 11 , wherein the ranking based on predictive ranking rules comprises one or more of:

determine an available data quota of each of the plurality of network connections; determine a connection speed of each of the plurality of network connections; determine a data speed of each of the plurality of network connections; determine a frame error rate rule of each of the plurality of network connections; determine a tariff plan associated with each of the plurality of network connections; determine a packet drop rate of each of the plurality of network connections; and determine a quality of experience (QoE) for each of the plurality of network connections.

14. The predictive ranking system (102) as claimed in claim 11 , wherein the ranking based on predictive ranking rules comprises determining a quality of service (QoS) of each of the plurality of network connections.

15. A non-transitory computer-readable medium having embodied thereon a computer program for executing a method for ranking based prediction of network connections for carrying out a multimedia event, the method comprising: