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
5 multimedia event.
[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
10 today's lifestyle and digital technology has found its way into different aspects of human life, Q 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
15 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,
20 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 e surfing, conference communications, online gaming, and real time social networking.
[0004] This summary is provided to introduce concepts related to ranking based
25 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.
[OOOS] 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
5 multimedia event. The at least one predictive ranking rule is indicative of criteria for ranking the
plurality of network connections.
[OOOS] 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
10 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
15 predictive ranking system, in accordance with an embodiment of the present subject matter; and
[OO 1 01 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.
[OO 1 11 It should be appreciated by those skilled in the art that any block diagrams herein
20 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
0 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.
[OO 121 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.
[00 131 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.
[OO 1 51 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.
[OO 1 61 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.
[OO 1 71 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.
100 181 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
5 problem to occur. The action may be understood as using the most suitable network connection
I 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
10 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 I @ effort in contacting the operator's helpdesk agent, it leads to an increase in user's satisfaction.
[OO 1 91 In one implementation of the present subject matter, an operator providing
communication network connectivity to a user may provide various internet based services, such
15 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
20 network connection and a 3G network connection services. Similarly, another user 'Y' 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
0 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
25 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
30 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.
[002 11 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 SkypeTM from his home on October 24,201 3 at 7:00 PM.
100231 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
5 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
10 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
15 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.
20 [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
0 on the data quota rule, the quality rule, the connection speed rule, the data speed rule, and the
frame error rate rule.
25 [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.
I003 11 In another implementation, the ranking may be based on multiple predictive
30 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
5 rules, then both the network connections may be assigned a same rank and left to the user to
select.
(00321 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
10 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.
15 [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.
20 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
I the network connections may change with time as the network service and device parameters
vary with time.
I00341 Referring again to the previous example, where a user is subscribed to the 3G
25 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 ~ 30 network connection, and the user devices, i.e., the Smartphone, the tablet, the Wi-Fi router, and
the lPTV 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
5 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
10 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
15 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.
20 [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
0 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
25 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.
100371 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
30 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.
100391 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, andlor configurations, the embodiments are described in the context of the
following exemplary system(s).
[004 11 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.
5 [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
10 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 I @ box, smart televisions (smart V S ) , 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
15 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
20 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,
0 Code Division Multiple Access (CDMA) network, Next Generation Network (NGN), Public
Switched Telephone Network (PSTN), and Integrated Services Digital Network (ISDN).
25 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
30 circuitries, andlor any devices that lnanipulate 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
5 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
10 limitation, digital signal processor (DSP) hardware, network processor, application specific i integrated circuit (ASIC), field programmable gate array (FPGA), read only memory (ROM) for
I @ 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
15 110 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 1 10 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.
20 [0051] In another embodiment of the present subject matter, the predictive ranking
system 102 may also include a memory 112. The memory 112 may be coupled to the processor
108. The memory 112 can include any computer-readable medium known in the art including, 0 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
25 (ROM), erasable programmable ROM, flash memories, hard disks, optical disks, and magnetic
tapes.
lo0521 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.,
30 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.
(00531 Further, the modules 114 can be implemented in hardware, instructions executed
by a processing unit, or by a combination thereof. The processing unit can comprise a computer,
5 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-
10 readable instructions (software) which, when executed by a processor/processing unit, perform
0 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.
I5 [OOSS] In an implementation, the module(s) 1 14 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
20 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 116 is shown internal to the
predictive ranking system 102, it may be understood that the data 1 16 can reside in an external
0 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
25 interface(s) 1 10 to obtain information from the data 1 16.
[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.
I00571 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
5 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
10 network connection.
[0058] According to an implementation, the determination module 122 may store the a 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
15 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
Network service and device
parameters
Calendar data
Historical data
Type of information
Details of the multimedia
event, day and time when the
multimedia event is suppose to
happen, location from where
the multimedia event may take
place, and uniform resource
locator (URL) of website that
may be used for the
multimedia event
Historical usage and
Data Source
User
Analytics engine at the
Weather data
Data quota
Connection data
User's home network
performance
Access network data
Device data
Content delivery network
information
performance data about the
user, the network connections,
and the internet based service
corresponding to the
multimedia event at certain
locations, time and day
Weather information in user's
location at time of the
multimedia event
Available data quota and tariff
plan of each of the plurality of
network connections
Performance data, error and
exception data, overall
performance, planned and
unplanned maintenance
information, connection speed,
data speed, frame error rate,
and packet drop rate rule
Upload speed, download
speed, retransmission rate,
packet drop rate, and number
of user devices attached with
the user's home network
Access network associated
with each network connection
User devices that the user is
using, network connections
available in each user device,
model number, and network
statistics
Information like Ping, Trace
route, etc
operator
Web service of Weather
monitoring service
User or the operator
Operator
One or more user devices
Subscriber data system at
the operator
User or the operator
Network monitoring
system at the operator
I QoS of Last mile connection I QoS of Last mile connection I Network monitoring I
I 1 associated with the network I system at the operator I
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 SkypeTM from his home on October 24,2013 at 7:00 PM. It may
5 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,
10 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
15 may be 500 megabytes (MB).
[0061] The network service and device parameters may also include user's home
I
I network performance. The user's home network may be a residential gateway. In one example, l
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
20 (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).
100621 Also, the network service and device parameters may include access network
data. The access network data represents the access network associated with each network
25 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.
I00631 According to an implementation, the aggregation module 124 may aggregate the
network service and device parameters for each of the plurality of network connections.
5 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
10 are grouped for the 3G network connection, the ADSL broadband network connection, and the
0 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
Aggregated Data
Available data quota
Packet drops
Retransmission of dropped packets
Connection speed
Data speed
QoS
QoE
Tariff plan
Frame error
Attached user devices
3G network
connection
I GB
100
20
As per
services
configured
Above data
speed
threshold level
Good
Good
Not expensive
10
Tablet,
LTE network
connection
500 MB
200
100
As per services
configured
Below data speed
threshold level
Degrading
Bad
Expensive
40
Smartphone 'B'
ADSL
broadband
network
connection
2 GB
5 00
300
As per
services
configured
Below data
speed
threshold
level
Degrading
Bad
Not expensive
5
Wi-Fi Router
[0065] Once the network service and device parameters are aggregated, the ranking
Smartphone
'A'
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
and lPTV
rules may be indicative of criteria for ranking the plurality of network connections. In one
5 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.
(00661 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
@ 10 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
15 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
20 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
25 dynamic in nature and change with time and/or geographical location. Based on the same, the
predictive ranking rules may also get updated.
(00671 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
5 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.
1007 11 Consider a scenario where the user has a tablet with a 3G network connection
10 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 lPTV with ADSL broadband network connection having
unlimited data plan subscription. On Monday, October 24, 201 3 at 7 PM, the user has to attend a
video conference from his home. For this video conference, the user may use a video
15 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
20 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
6 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
25 subscription of 3G network connection, IPTV is not turned ON during this time of the day,
sometimes a VolP 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.
100731 Referring again to the previous scenario, on October 24, 2013 around 6:30 PM, a
30 family member of the user is watching IPTV and observing that picture sometimes freezes. The
lPTV 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
5 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
10 conference happens without any glitches. Meanwhile, the operator can troubleshoot the
degrading ADSL broadband network connection and eventually fix the same.
43 [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
15 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
20 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 e 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
25 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
30 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
5 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
10 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
15 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
20 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
0 distributed computing environment where functions are performed by remote processing devices
that are linked through a communications network. In a distributed computing environment,
25 computer executable instructions may be located in both local and remote computer storage
media, including memory storage devices.
[OOSO] 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
30 media, which are machine or computer readable and encode machine-executable or computerexecutable
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.
I00861 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
5 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
10 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
15 ranking based prediction of network connections for multimedia event.

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
5 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
10 ranking the plurality of network connections based on at least one predictive
0 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.
15 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 (1 04) from
2 0 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 (1 04) associated with
2 5 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.
30 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 (1 04).
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 (1 02) for predicting network connections, based on ranking,
for carrying out a multimedia event, the predictive ranking system (102) comprising:
a processor ( I 08);
a determination module (1 22) 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 (1 08) 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 (1 02) as claimed in claim 11, 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 (1 02) 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:
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.