FIELD OF INVENTION
[0001] The present subject matter relates to communication networks and, particularly,
but not exclusively, to data cormectivity in the communication network.
BACKGROUND
[0002] Communication devices, such as cellular phones, smart phones, and personal
digital assistants (PDAs), provide users with a variety of mobile communications services and networking capabilities. Such communication devices have seemingly become a ubiquitous part of today's lifestyle. The communicating devices allow data exchange between multiple users through network services provided by various service providers. The service providers are faced with a challenge to meet user demands of high speed data connectivity at all places and all the time. For this, the service providers generally provide data cormectivity services to the users through various means, such as wired broadband connections, wireless internet access, connectivity through cellular networks, and other wireless access points.
[0003] Communication network service providers currently operate not only on the
prevalent IP and mobile radio systems using the GSM and CDMA standards for mobile communications, but also on networks, such as IP Multimedia Service (IMS) and telecommunication networks using the new and evolved 3rd generation (3G) Universal Mobile Telecommunications Service (UMTS) and cdma2000 standards. Based on such standards and infrastructure to support high rates of data exchange, the service providers provide enhanced connectivity to the users. Enhanced cormectivity allows the users to utilize data intensive multimedia services like push to talk, video calling, conference calling, high data rate internet connectivity, live media streaming, audio and video downloading/streaming, voice communications, video communications, conference communications, online gaming, and real time social networking.
[0004] The enhanced connectivity with high data rate is generally provided to the users
against a charge that is generally based on various parameters, such as tariff plan selected by the users, type of connection associated with the caller party, i.e., a pre-paid connection or a post paid connection, and the type of service requested by the user. Service providers strive to provide
better services and higher data rates at competitive charges to invite more users and generate more revenue.
SUMMARY
[0005] This summary is provided to introduce concepts related to data cormectivity in a
communication network. This summary is not intended to identify essential features of the claimed subject matter nor is it intended for use in determining or limiting the scope of the claimed subject matter.
[0006] In one implementation, a method to provide data cormectivity in a communication
network with an assured quality of service (QoS) is described. The described method may include identifying one or more of data usage pattern associated with at least one user and pattern of drops in QoS. Further, the method may also include predicting one or more of probable data usage and probable drops in QoS based on one or more of the identified data usage pattern and the pattern of drops in QoS; and reserving resources of the communication network based on the one or more predicted probable data usage and probable drops in QoS to provide assured QoS.
[0007] In another implementation of the present subject matter, a system to provide data
connectivity in a communication network with an assured quality of service (QoS) is described. The system may include a processor and a memory coupled to the processor. The memory of the system may include a pattern analysis module configured to identify one or more of a data usage pattern associated with at least one user and patterns of drops in QoS, wherein the drops in QoS are associated with at least one of communication network congestion and handoffs between cell blocks. The pattern analysis module may also predict probable handoffs based on handoff patterns derived from the data usage pattern of the at least one user. Further, the system may include a handoff optimization module configured to optimize handoffs between different cell blocks, for the at least one user, based on predicted probable handoffs.
[0008] In one implementation, a computer-readable medium having embodied thereon a
computer readable program code for executing a method is described. The method may include identifying one or more of data usage pattern associated with at least one user and patterns of drops in QoS, predicting one or more of probable data usage and probable drops in QoS based on one or more of the identified data usage pattern and the pattern of drops in QoS; and reserving
resources of the communication network based on the one or more predicted probable data usage and probable drops in QoS to provide an assured QoS.
BRIEF DESCRIPTION OF THE FIGURES
[0009] 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:
[0010] Fig. 1 illustrates an exemplary communication network environment, according to
an embodiment of the present subject matter;
[0011] Fig. 2 illustrates a method to provide data connectivity in a communication
network with an assured quality of service (QoS), in accordance with an embodiment of the present subject matter
[0012] 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
[0013] In the present document, the word "exemplary" is used herein to mean "serving as
an example, instance, or illustration." Any embodiment or implementation of the present subject matter described herein as "exemplary" is not necessarily to be construed as preferred or advantageous over other embodiments.
[0014] Systems and methods for providing data connectivity in a communication
network with an assured quality of service (QoS) are described, in accordance with an implementation of the present subject matter. The methods can be implemented in various
communication devices communicating through various networks. Although the description herein is provided with reference to telecommunication networks, the methods and systems may be implemented in other networks providing data connectivity, albeit with a few variations, as will be understood by a person skilled in the art.
[0015] The systems and methods can be implemented in systems capable of exchanging
data in accordance with the Global System for Mobile Communications (GSM) techniques utilizing the different GSM communication standards, such as 2G and 3G. Further, the methods may also be implemented in systems capable of exchanging data in accordance with the Code Division Multiple Access (CDMA) technique utilizing the different CDMA communication standards, such as IS 95 or cdmaOne, and cdma2000; and Internet Protocol (IP) Multimedia Subsystem (IMS).
[0016] The systems and methods can be implemented in a variety of entities, such as
communication devices. The entities that can implement the described method(s) include, but are not limited to, hand-held devices, mobile phones, PDAs, smartphones, and the like. Further, the method may also be implemented by devices capable of exchanging data to provide connectivity to different communicating devices and computing systems. Such devices may include, but are not limited to, Radio Network Controller (RNC), Base Transceiver Station (BTS), Mobile Switching Centre (MSC), Base Station Subsystem (BSS), Home Location Register (HLR), Authentication Center (AuC), data cards, mobile adapters, wireless (WiFiTM) adapters, routers, and the like.
[0017] Further, the techniques described herein may be used for various wireless
communication systems, such as Time Division Multiple Access (TDMA), Frequency Division Multiple Access (FDMA), Orthogonal Frequency-Division Multiple Access (OFDMA), Single Carrier Frequency Division Multiple Access (SC-FDMA) and other systems. A CDMA system may implement a radio technology, such as Universal Terrestrial Radio Access (UTRA), cdma2000, etc., where the UTRA includes variants of CDMA. cdma2000 may include various standards, such as IS-2000, IS-95 and IS-856. A TDMA system may implement a radio technology, such as GSM. An OFDMA system may implement a radio technology, such as Evolved UTRA (E-UTRA), Ultra Mobile Broadband (UMB), IEEE 802.20, IEEE 802.16 (WiMAX), 802.11 (WiFi™), Flash-OFDM®. UTRA and E-UTRA are part of Universal Mobile
Telecommunication System (UMTS). 3GPP Long Term Evolution (LTE) is an upcoming release of UMTS that uses E-UTRA. UTRA, E-UTRA, UMTS, LTE and GSM are described in documents from an organization "3rd Generation Partnership Project" (3GPP). cdma2000 and UMB are described in documents from an organization named "3rd Generation Partnership Project 2" (3GPP2). For clarity, certain aspects of the techniques are described below for 3G communication networks.
[0018] Nowadays, users of communication networks are becoming increasingly
demanding in terms of the number of features provided by the service providers. The users welcome services that appeal to their emotional as well as their practical needs. New, exciting services and enhancements to existing services, like video calling enabling face-to-face interactions, have a key role to play in making the communication experience much more realistic. However, to provide such experiences, service providers have to provide communication networks with enhanced connectivity and high data rates.
[0019] Generally, communication networks facilitate enhanced data coimectivity with
high data rates that enables the service providers to offer multimedia services. High data rates also enable data intensive services, such as live video streaming, and video calling to cater to the evolving user needs and provide rich user experiences. Effectively a user utilizing a communication network could, for example, pay for enhanced data coimectivity to download a video clip to a chosen mobile device and subsequently use some of this material to create a multimedia message to share with other devices on many different networks. Therefore, such enhanced data connectivity and services provide for better communication experiences that provide aid to the ever increasing social networking and multimedia usage.
[0020] With an increasingly large number of users availing various high data rate
services provided by the service providers, the commvmication networks are faced with issues related to capacity saturation, inadequate cell edge performance, poor delivery Quality of Service (QoS), bad Quality of Experience (QoE) by users, etc. To determine QoS, generally certain parameters, such as signal strength, minimum data throughput, and average data throughput apart from (peak data throughput) are utilized. In certain situations, QoS may also be determined based on the average data rate or average network data throughput provided to the users by the service provider. For example, if the average data rate provided to the users by the service provider is X
Kbps, any drop in the data rate below X Kbps may amount to poor QoS and consequently a poor QoE.
[0021] Due to such poor QoS, enhanced data connectivity may not be available to the
users at different time instances and at different geographic locations. Further, due to lack of good data connectivity, the user may not be able to use some applications that a user would have used otherwise. Hence, this may lead to under utilization of applications like online video streaming. It would be understood that QoE amounts to the overall experience received by the user at any given instance or at any particular geographical region.
[0022] Generally, poor QoS issues are faced due to poor network planning and
inappropriate scheduling mechanisms utilized by the service providers. Existing mechanisms to inform the communication network about charmel quality utilize parameters like the Channel Quality Indicator (CQI); however, good coimectivity does not guarantee a good QoS. It can happen that the network capacity is unable to provide the necessary QoS even if CQI is very good and hence it can degrade the throughput. For example, at certain times, the density of users utilizing the services provided by the service provider in a particular geographic location may be more than what the communication network is capable of catering to, resulting in the communication network operating at its near peak capacity. When nearing the peak capacity, the communication network may either not be able to provide services to each and every user, or may provide a poor QoS to the users. In such situations, even when the users are connected to the communication network and catered to by the service provider with good connectivity, the data rate received by the users may be very less resulting in a poor QoS. Since services, such as live video streaming and video calling require a higher data rate, low data rate and poor QoS may in turn also result in a poor QoE.
[0023] Further, while a user is travelling and traversing from one cell block to another,
handoffs might happen between different Base Transceiver Stations (BTSs). Cell blocks may be understood as a pre-defined geographical region to which a BTS is assigned, and to which the BTS is configured to provide coimectivity to the users. During handoffs between different BTSs, user may either experience loss of data connectivity or may experience poor QoS even when connectivity to the communication network is available.
[0024] Therefore, as described, the reasons for which users may receive a poor QoS may
be several, for example, poor network planning, un-optimized scheduling, and handoffs between BTSs. Due to such reasons, the communication network resources may also be utilized un-optimally which may ultimately lead to a poor QoE.
[0025] To assure good QoS at all times, service providers may try to improve the QoS by
increasing the capacity of the communication network to not allow such degradation of service even due to congestion or during handoffs. However, this may be an expensive solution for the service provider as the higher network capacity may be underutilized for most of the time.
[0026] Further, to assure good QoS to selected users, for example, users who may be
willing to pay higher fees, generally the service provider assigns a high profile subscription, such as a Gold or Platinum subscription to the selected users. Such subscriptions are given higher priority in the network and thus guarantee high bit rate and QoS all the time. However, the high profile subscriptions are either only provided to the selected users or levy a high fee on a user. In many cases, the user may not even require the high profile subscription at all times. For example, a user utilizing a high profile subscription may pay a fixed fee for a fixed period of time, such as a month. However, during this fixed period of time, the user may only require the assured QoS during particular time instances, such as certain periods in a day. Since such requirements of the user are not accounted for, the user may end up paying the fee for the durations when actually the assured QoS is not required by the user. Hence, the user may not only end up paying an extra amount unnecessarily, but the assured bandwidth reserved for these users may also be wasted during the time periods when it is actually not required and not utilized.
[0027] According to an implementation of the present subject matter, systems and
methods for providing data cormectivity in a communication network with an assured quality of service (QoS) are described. Although the description herein is provided with reference to telecommunication networks, the methods and systems may be implemented in other networks providing data connectivity, albeit with a few variations, as will be understood by a person skilled in the art.
[0028] In one implementation, an assured QoS may be provided to the user based on data
usage patterns of one or more users and patterns of drops in QoS. To provide an assured QoS, based on data usage patterns of one or more users and patterns of drops in QoS, probable time
instances and geographic regions of probable data usage and probable drop in QoS may be predicted. In another implementation, based on such predictions, the subscription of users may be dynamically upgraded in real time to suit their data requirements. The up-gradation in the subscription may either be based on user approval, or may be based on a pre-approval of the user to obtain assured QoS. As described before, the systems and methods can be implemented in a variety of processing and communication devices capable of providing connectivity to the users and form a part of the communication network according to the different standards defined for communication.
[0029] The systems and methods as described herein, on one hand, track and analyze the
data usage patterns of one or more users and patterns of drops in QoS to determine probable data usage and probable drops in QoS, and on the other, provide assured QoS to the users based on dynamic real time assessment. In one implementation of the present subject matter, the assured QoS of service may be provided to all the users of the communication network. However, in another implementation of the present subject matter, users who wish to receive uninterrupted data connectivity, for example, in return of a higher tariff, may be provided with the assured QoS.
[0030] As described before, assured QoS may be provided to the users by assuring a
minimum data rate or a minimum network data throughput. For example, if the average data rate provided to the users by the service provider is X Kbps which drops by 50-80% during times of congestions or handoffs, users can be assured of X Kbps data rate at all times to guarantee an assured QoS and good QoE.
[0031] In one implementation of the present subject matter, for assuring QoS at all times,
the time instances and geographic regions where the user is expected to utilize data services is determined. Similarly, in another implementation, the time instances and geographic regions where QoS is expected to drop may also be determined to provide assured QoS. As described before, such determination may be based on the data usage patterns of one or more users receiving data connectivity from the service provider. Further, in another implementation, the determination may also be based on the patterns of drops in QoS experienced by the users. As described before, the drop in QoS may either be experienced by the users due to congestion in the communication network or due to handoffs between BTSs while the user may be travelling.
[0032] In yet another implementation, the data usage pattern of the user may include
different parameters associated with the user, such as throughput received by the user at different time instances, user's requested throughput based on the request of the applications used by the user, user's throughput at different geographic locations, and user's throughput at different geographic locations at different time instances. Further, the data usage pattern may also include time instances when the user's data usage is high, time instances when user's data usage is low, geographic locations where user's data usage is high, and geographic locations where user's data usage in low.
[0033] Based on the data usage pattern of a user, the user's data requirement at different
time instances and at different geographic locations may be determined. Further, based on patterns of drops in QoS provided by the service provider to the users, the time instances when the communication network is expected to provide a poor QoS may also be determined. In one implementation, the user data requirements and the instances of drop in QoS may be predicted based on statistical and data mining techniques utilized to analyze the data usage patterns and patterns of drops in QoS.
[0034] For example, a user may travel through a highway on a daily basis where he may
utilize the data services provided by the service provider to watch live streaming of videos. Based on the above data usage pattern, the user's data requirement in the specific geographic location may be determined to assure QoS for the user during such determined time instance, i.e., when the user travels through the highway. Similarly, if it is determined from the patterns of drop in QoS that during a particular time period every day, the QoS provided to the users drops due to congestion in a particular geographic region, the time period and the geographic location can be determined and it can be predicted that the user would experience a poor QoS in the particular geographic region during the particular time period in the future as well.
[0035] In one implementation, preemptive measures can be taken to assure QoS to the
users based on the determined data requirements and expected communication network QoS drops from the data usage patterns and pattern of drops in QoS. In said implementation, the assured QoS may be provided to users who opt for uninterrupted data connectivity and assured data rate at all times. As described before, this may be based on the determined user's data requirements and expected communication network QoS drops.
[0036] To this end, the user may be dynamically prompted in real time to accept a
temporary upgrade of their subscription to suite their data requirements and overcome any predicted drop in the data rate and QoS. As described before, the drop in QoS may either be due to data usage pattern of the user or congestion in the network. In another implementation, the users may be upgraded temporarily based on a pre-acceptance of the users. In case of pre-acceptance by a user, the user may request for the QoS upgrade even before the network may prompt the user to upgrade the subscription temporarily. In one example, the pre-acceptance may be based on a subscription of the user where the feature may be provided to all the users opting for such subscription.
[0037] In one example, as described before, if based on the drops in QoS patterns,
congestion in the communication network of the highway through which the user travels is predicted, the user might be prompted to temporarily upgrade his subscription when once identified to be utilizing the communication network of the highway. Similarly, the user may request the service provider to assure the QoS before travelling through the highway. It would be appreciated that the upgradation of the subscription may happen on a temporary basis for a short duration.
[0038] In one implementation, users opting for an assured QoS may be levied an extra
amount of fee for such facility on a dynamic basis. For example, the subscription of a user may be upgraded from normal subscription to a high priority subscription for the time period when drop of QoS is predicted. During such period, the user may be charged either a fixed amount per upgradation or an amount based on the duration for which the subscription was actually upgraded. Further, once such a period is over, the subscription of the user may be downgraded to its normal state.
[0039] To provide assured QoS to the users, in one implementation of the present subject
matter, certain resources of the communication network may be reserved. Such reserved resources may be utilized for the users who have opted for an upgrade in their subscription. It would be understood by those skilled in the art that the communication network of a cell block has a fixed amount of resources that are shared among the users of that cell block. In said implementation, to provide assured QoS to the upgraded users based on determined probable
data usage and expected drops in QoS, certain resources may be reserved to provide priority data connectivity to the users.
[0040] For example, if based on the patterns of drops in QoS, a cell block is determined
to be providing poor QoS on every 1st day of a week. Therefore, to provide assured QoS, on every 1st day of the week 20% of the resources of that cell block may be reserved for the users desiring an assured data throughput and an assured QoS. Also, the resources may be reserved based on the time of day for which the drop in QoS is expected, i.e., the resource may only be reserved during 1000 hours to 1200 hours on every 1st day of the week. Further, the reserved resources may be utilized for the users opting for an upgrade in the subscription.
[0041] In another implementation of the present subject matter, to provide assured QoS
to travelling users traversing from one cell block to another, thereby causing handoffs, the handoffs between the cell blocks may be optimized. In one example, the handoff threshold parameters may be customized to allow smooth and fast handoffs between two cell blocks. In another example, the handoffs between the cell blocks may be preapproved. In said implementation, the handoffs may be optimized for the users opting for upgradation of subscription. Further, in another implementation, to provide optimized handoffs and better QoS, the optimization of handoffs may be done for all the users.
[0042] The optimization of handoffs for travelling users may also be based on data usage
patterns. The data usage pattern of a user may provide the details of the time instances along with the geographic regions where the user utilizes the data services provided by the service provider. Based on such details, handoff patterns between the cell blocks may be determined for the users. The handoff patterns may describe the time instances and cell blocks between which handoffs generally occur for the user. In one implementation, based on such handoff patterns, possible handoff situations for the user may be predicted. In said implementation, either, for the predicted handoff possibilities, the handoffs between the cell blocks may be pre-approved, or the threshold parameters of the cell blocks may be customized. In another implementation, the handoffs may be optimized dynamically when the user is identified as traversing through such predicted handoff regions.
[0043] The described methods and systems for data connectivity to provide assured QoS
may allow dynamic up gradation of subscription based on data usage pattern and patterns of
drops in QoS. This may allow assured QoS to users opting for consistent data throughput even during times of congestions and probable handoffs. Further, the described methods may allow users to avail better QoE along with ability to consume high data rate applications like streaming videos on the move. Also, the described methods and systems may optimize usage of network resources providing higher average revenue per user and satisfied users to the service provider.
[0044] The above methods and systems are further described in conjunction with the
following figures. It should be noted that the description and figures merely illustrate 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 or shown 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 present subject matter 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 present subject matter, as well as specific examples thereof, are intended to encompass equivalents thereof.
[0045] It will 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" is used throughout for clarity of the description and can include either a direct connection or an indirect cormection. The descriptions and details of well-known components are omitted for the sake of brevity.
[0046] The manner in which the systems and methods for providing assured QoS is
implemented shall be explained in detail with respect to the Figures 1-2. While aspects of described systems and methods for providing assured QoS can be implemented in any number of different computing systems, environments, and/or configurations, the embodiments are described in the context of the following exemplary system(s).
[0047] Fig. 1 illustrates a communication environment 100 for data transfer in
communication networks, in accordance with an embodiment of the present subject matter. In one implementation, the environment 100 includes a system 102 and multiple users utilizing user equipments (UE)s 104-1, 104-2, and 104-N. For the sake of clarity, the multiple UEs 104-1,104-2, 104-3, ..., 104-N are collectively referred to as UEs 104 and individually as UE 104, hereinafter. The UEs 104 may either be stationary at any geographic location or may be a mobile device that may be moved from one geographic location to another, traversing through one cell block to another.
[0048] For example, for the sake of depiction, the user utilizing UE 104-N is depicted to
be travelling and traversing from one cell block 106-1 to another cell block 106-2, collectively referred to as cell block 106 hereinafter. Similarly, various users of the UE 104 may be travelling either within one cell block or may be traversing from one cell block to another. It would be understood by those skilled in the art that the travelling users may be provided data services by any of the cell blocks, such as 106-1 and 106-2, as the case may be.
[0049] The system 102 may be a fixed station that communicates with the cell blocks 106
and the UEs 104; to provide assured QoS to the users based on data usage patterns of the users 104 and the pattern of QoS drops. The system 102 may be implemented in a Node B and may also be referred to as an evolved Node B (eNB), in a base station, an access point, etc. As would be understood by a person skilled in the art, the Node B (NB) provides communication coverage for a particular geographic region. The coverage area of NB 102 may be partitioned into multiple smaller areas. Each smaller area may be served by a respective NB subsystem to cover an area, such as the cell block 106-1 and cell block 106-1. Further, the term "cell block" may refer to the smallest coverage area of any NB and/or a NB subsystem serving a coverage area.
[0050] The UEs 104 may include, 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 UEs 104 may include devices capable of exchanging data to provide cormectivity to different communicating devices and computing systems. Such devices may include, but are not limited to, data cards, mobile adapters, wireless (WiFiTM) adapters, routers, a wireless modem, a wireless communication device, a cordless phone, a wireless local loop (WLL) station, and the like. As UEs 104 may be stationary or mobile and
may also be understood to be a mobile station, a terminal, an access terminal, a subscriber unit, a station, etc.
[0051] In one implementation, the system 102 may communicate with the cell blocks 106
and the UEs 104 through a network, such as network 108, having an uplink and a downlink. The network 108 may be a wireless or a wired network, or a combination thereof. The network 108 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, Internet Protocol Multimedia Subsystem (IMS) network, Personal Communications Service (PCS) network, Time Division Multiple Access (TDMA) network, Code Division Multiple Access (CDMA) network, and Next Generation Network (NGN). The network 108 can in turn be also implemented as one of the different types of networks, such as intranet, telecom network, electrical network, local area network (LAN), wide area network (WAN), Virtual Private Network (VPN), internetwork. Global Area Network (GAN), the Internet. Depending on the technology, the network 108 may includes various network entities, such as gateways, routers; however, such entities have been omitted for ease of understanding. Although the network 108 is described to be any communication network, the described methods and systems have been illustrated with respect to a tele- communication network and may be implemented in other networks providing data connectivity, albeit with a few variations, as will be understood by a person skilled in the art.
[0052] It would be understood by those skilled in the art that the system 102 may be
implemented in a Radio Network Controller (RNC) (not shown) where the RNC is configured to control different NBs by managing resources of the communication network and coordinate data transfer. Further, the system 102 may be implemented as a network server, a server, a workstation, a mainframe computer, and the like.
[0053] In one implementation, the system 102 includes processor(s) 112. The processor
112 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.
[0054] 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.
[0055] Also, the system 102 includes interface(s) 114. The interfaces 114 may include a
variety of software and hardware interfaces that allow the system 102 to interact Avith the entities of the network 108, or with each other. The interfaces 114 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.
[0056] The system 102 may also include a memory 116. The memory 116 may be
coupled to the processor 112. The memory 116 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 mranories, hard disks, optical disks, and magnetic tapes.
[0057] Further, the memory 116 includes module(s) 118 and data 120. The modules 118
include routines, programs, objects, components, data structures, and the like, which perform particular tasks or implement particular abstract data types. The modules 118 further include modules that supplement applications on the system 102, for example, modules of an operating
system. The data 120 serves, amongst other things, as a repository for storing data that may be fetched, processed, received, or generated by one or more of the modules 118.
[0058] In an implementation, the module(s) 118 includes a pattern analysis module 122,
resource management module 124, handoff optimization 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 system 102. In said implementation, the data 120 includes a usage pattern data 130, QoS drop data 132, estimation data 134, and other data 136. The other data 136, 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) 118. Although the data 120 is shovra internal to the system 102, it may be understood that the data 120 can reside in an external repository (not shown in the figure), which may be coupled to the system 102. The system 102 may communicate with the external repository through the interface(s) 114 to obtain information from the data 120.
[0059] As mentioned before, the system 102 is configured to provide assured QoS to the
users in the communication environment 100. In one embodiment, the assured QoS may be provided based on the data usage pattern of one or more users and the patterns of drops in QoS. In one implementation, the assured QoS may be provided to all the users subscribed with a service provider providing data services, on a dynamic notification-acceptance basis. However, in another implementation, the service of assured QoS may be provided to only users who have pre-accepted or notified to receive un-interrupted data cormectivity. The pre-acceptance may either be in the form of a message or request by the user or may be provided to the service provider in the form of a subscription.
[0060] To this end, according to an implementation of the present subject matter, the
pattern analysis module 122 of the system 102 is configured to identify data usage pattern and patterns of drops in QoS. To identify data usage patterns associated with different users, the time instances and the geographic regions where the user utilizes the data services may be monitored. In said implementation, the data services utilized by the user may be monitored based on different parameters, such as throughput received by the user at different time instances, user's requested throughput based on the request of the applications used, user's throughput at different
geographic locations, and user's throughput at different geographic locations at different time instances.
[0061] It would be understood that the user's requested throughput based on applications
used may vary from one time instance to the other. For example, the user may utilize data services provided by the service provider for article reading purpose through a web browsing application. In utilizing the data services for article reading, the web browsing application may only request for low data rates, such as 40-50Kbps. However, if the user is utilizing the data services for live video streaming, the application may request a data rate of 500-700 Kbps for uninterrupted support. Therefore, the requirement of the user may vary from one time instance to another and hence, the user's requested throughput, based on the request of the applications used, may be monitored by the pattern analysis module 122 at different time instances.
[0062] In another implementation, the situations when the data rate requested by user is
greater than the average data rate provided by the service provider are monitored. For example, in situations described above, if the average data rate provided by the communication network is about 450 Kbps, the time instances and geographic locations where the user utilizes applications requesting higher data rate is identified.
[0063] Further, in yet another implementation, the data usage pattern may also be
determined based on time instances when the user utilizes data services, time instances when user's data usage is low, geographic locations where user's data usage occurs, and geographic locations where user's data usage is low.
[0064] Therefore, based on the parameters providing details of the data usage of the user
at different time instances and geographic locations, the data usage pattern associated with the user may be determined. As described before, the pattern analysis module 122 may determine the data usage pattern based on the described parameters.
[0065] The pattern analysis module 122, according to another implementation of the
present subject matter, may also identify the pattern of drops in QoS provided by the communication network. As already described, the drop in QoS may occur due to different reasons, such as poor network planning, congestion in the communication network, and handoffs between cell blocks. The pattern analysis module 122, in said implementation, may monitor, apart from other parameters, the data throughput provided by the service provider to the user at
various time instances and geographic locations. Based on such parameters, the pattern analysis module 122 may determine the patterns of drops in the QoS. Therefore, the time instances when a drop in QoS is observed may be monitored by the pattern analysis module 122.
[0066] For example, in a cell block comprising of several office compounds, generally
workers may arrive in the morning, and may leave by evening. In such a cell block, the workers may utilize the data services through the communication network during their stay in the office compound, and therefore, the communication network may experience a high load during day time, because of which the QoS may drop at various time instances. However, the utilization of the data services by the users may drastically drop during evening and night hours. It may also occur that the utilization of the data services in day time is drastically less on weekends when compared to the utilization of data services at the same time on weekdays. Therefore, the pattern analysis module 122 may determine a pattern of drops in QoS based on the QoS provided to different users at different time instances and at different geographic locations.
[0067] In one implementation, the pattern analysis module 122 analyzes the data usage
pattern of users and the pattern of drops in QoS to predict probable usage by the users and probable drops in QoS. For example, if the pattern analysis module 122 determines a user to be requesting 600-700 Kbps data rate on every weekday between 1000 hours and 1200 hours, based on such data usage pattern, the pattern analysis module 122 may predict the probable usage of data services by user. In said example, the pattern analysis module 122 may predict probable data usage by the user on weekdays between 1000 hours and 1200 hours.
[0068] Similarly, the pattern analysis module 122 may also be configured to predict
probable drops in QoS at different time instances and geographic locations based on the identified pattern of drops in QoS. In the example described earlier, where the cell block includes several office compounds, the pattern analysis module 122 may identify that a poor QoS is provided to the user during day time in weekdays. Therefore, based on the identified pattern of drops in QoS, the pattern analysis module 122 may predict probable drop in QoS in the particular cell block during weekdays. An example of the pseudo code implemented by the pattern analysis module 122 is as follows:
variable array UserLocationProfileHistory; variable array UserTimeofUsageHistory; variable array UserBandwidthDemanciHistory;
variable array CurrentServingNetworkElements;
variable array StateOfCurrentServingNetworkElements;
variable array ExpectedServingNetworkElements;
variable array StateOfExpectedServlngNetworkElements;
variable array TimeOfExpectedServingNetworkElements;
variable array LocationMapBandwIdthRequirements;
variable array LocationMapNetworkResourceUsed;
variable array LocationMapTimeOfPresence;
variable array LocatlonMapCellSites;
variable array CellSitesRadioNetworkController;
variable UserMediaType;
variable UserMediaMinimumBitRate;
ExpectedBitRateAtLocationXTimeT = Function DecideExpectedBitRate
(UserLocationProfileHistory, UserTimeofUsageHistory,
UserBandwidthDemandHistory, CurrentServingNetworkElements,
StateOfCurrentServingNetworkElements, ExpectedServingNetworkElements,
StateOfExpectedServingNetworkElements,
TimeOfExpectedServingNetworkElements,
LocationMapBandwidthRequirements, LocationMapTimeOfPresence,
LocationMapCellSites, CellSitesRadioNetworkController, UserMediaType);
While (DurationOfTravel OR ApplicationUsageTime) {
If (ExpectedBitRateAtLocationXTimeT < UserMediaMinimumBitRate)
{Prompt User for upgrading QoS};}
[0069] It would be understood by those skilled in the art that the frequency of repetition
of data usage may vary from one user to another and may also be erratic for several individuals. Similarly, the pattern of drops in QoS may also vary in time instance and duration from one geographic location to another. The pattern analysis module 122 may implement statistical and data mining techniques to analyze the data usage patterns and predict the probable usage and probable drops in QoS.
[0070] In one implementation, the system 102 may take preemptive measures to provide
assured QoS to the users based on the predicted probable data usage and probable drops in QoS derived from the data usage patterns and pattern of drops in QoS. In said implementation, the preemptive measure may be taken to assure availability of resources for the users wishing to receive uninterrupted data services with good QoS. The users may either provide an approval in advance by various modes, such as through a message or by subscribing to a subscription service to avail assured QoS. In another implementation, the user may be dynamically prompted to opt for service of assured QoS when a probable drop in QoS is predicted.
[0071] In operation, the resource management module 124 may temporarily upgrade the
subscription of the users to a high priority subscription to assure good QoS. In one
implementation, the temporary upgrade may either be based on dynamic approval of the user or may be done by the service provider based on pre-approval by the user. In either condition, the users may be upgraded to the high priority subscription for the duration when either probable data usage is predicted, or a drop in QoS is predicted by the pattern analysis module 122.
[0072] In said implementation, the users may be charged a fee by the service provider for
the temporary upgrade. The fee may either be levied based on the time duration of the upgrade, or may be levied on a per upgrade basis. It would be appreciated that the temporary upgrade of the subscription for the users may be based on the predicted probable data usage and predicted probable drops in QoS.
[0073] For example, the pattern analysis module 122 may predict a probable QoS drop in
a particular cell block during 1400 hours to 1500 hours based on the past pattern of drops in QoS. A user p may incidentally enter the cell block at 1430 hours. To provide assured QoS to this user during the predicted drop in QoS, the subscription of the user may be upgraded to high priority subscription on a temporary basis. Similarly, if it is determined that a user r utilizes data services on Mondays at 2000 hours where the application utilized by the user requires a data rate higher that the average data rate provided by the communication network, the resource management module 124 may upgrade the subscription of the user r to high priority subscription to assure required data rate and hence, a good QoS.
[0074] In situations described above and in similar situations when an assured QoS is to
be provided to the user, the user may be prompted dynamically to allow an upgrade of his subscription temporarily for un-interrupted data services and assured QoS. However, it would be understood that in case the user has provided a pre-approval to obtain assured QoS, he may not be prompted dynamically and would be upgraded automatically.
[0075] To provide assured QoS to the users, in one implementation of the present
subject matter, the resource management module 124 may reserve certain resources of the communication network. Such reserved resources may be utilized for the users who have opted for an upgrade in their subscription. As described before, the communication network of a cell block has a fixed amount of resources, such as 64 Enhanced Dedicated Charmel (E-DCH) resources, that are shared among the users of that cell block. To provide assured QoS to the
upgraded users, based on determined probable data usage and expected drops in QoS, the reserved resources may be utilized to provide data connectivity to the users on priority.
[0076] For instance, in the above described example where the pattern analysis module
122 has predicted a probable QoS drop in the particular cell block during 1400 hours to 1500 hours, the resource management module 124, based on such prediction, may reserve some amount of resources, such as 5-15%, of the cell block for the users subscribed to receive assured QoS. The reserved resources may then be utilized for the users subscribed to receive assured QoS. In one implementation, the resource management module 124 may dynamically increase or decrease the amount of resources reserved, based either on the identified number of users utilizing the high priority subscription, or the quantum of drop predicted in the data throughput of the data services provided by the service provider.
[0077] Similarly, for a user's predicted data usage, the resource management module 124
may reserve resource of the communication network to provide assured QoS. For example, if it is predicted by the pattern analysis module 122 that the user would be utilizing data services with increased data throughput request from the utilized application, the resource management module 124 may reserve certain resources of the communication network for the user during the time period and at the predicted geographic region. Further, the resource management module 124 may also release the reserved resources if the reserved resources are identified to be unutilized. Although it has been described that the resources would be reserved and utilized for the users currently utilizing the high priority subscription, it would be appreciated that the resources may also be reserved for all the users to provide better data throughput and assured QoS.
[0078] In another implementation of the present subject matter, the travelling users, such
as the user 104-N, traversing from one cell block 106-1 to another cell block 106-2, may also be provided with assured QoS. As would be understood by those skilled in the art that during handoffs between BTSs of different cell blocks, drop in QoS is observed and an assured data through may not be received by the users. To provide assured QoS to travelling users, the pattern analysis module 122 may identify the data usage pattern of users also based on their data usage during travelling from one geographic location to another. Based on the data usage pattern of the user during travel, the handoff patterns associated with the user may be identified. The handoff
patterns may describe the cell blocks and the BTSs among which the handoffs occur along with the time instances for the user. Further, the handoff patterns may also include the data rate requested by the user during such travels. In said implementation, the pattern analysis module 122 may predict the probable handoffs and the data usage of a user based on the handoff patterns.
[0079] In one implementation, the handoff optimization module 126 may optimize the
handoffs by customizing the threshold parameters. The optimization of the handoffs through customization of the threshold parameters may allow smooth and fast handoff between cell blocks and provide better QoE to the user. Further, the handoff optimization module 126 may modify the threshold timers of the cell blocks where the handoffs for the user are predicted by the pattern analysis module 122. The modification of the threshold timers may allow quicker handoffs and may also reduce the ping-pong effect generated in the communication network.
[0080] In another implementation, based on the predicted handoffs for a user, the handoff
optimization module 126 may pre-approve the handoffs between the cell blocks. The pre-approval may allow a smooth and fast handoff between the cell blocks, ensuring un-interrupted data service to the user. Further, based on the data usage pattern of the travelling users, the resource management module 124 may also reserve the resources of the path traversed by the user. For example, based on the data usage pattern of the user 104-N, it may be determined that the user 104-N travels through a particular highway on every 15th day of a month and utilizes data services provided by the communication network. It may also be determined that during this travel, the user 104-N undergoes 8 handoffs between different cell blocks. Therefore, based on the above described data usage pattern of the user 104-N and the associated handoff pattern, the pattern analysis module 122 may predict probable usage and the handoffs for the user.
[0081] In one implementation, based on such predictions, the handoff optimization
module 126 may either pre-approve the predicted handoffs or customize the threshold parameters to provide un-interrupted data service to the users. Further, in said implementation, the resource management module 124 may also reserve resources of the highway through which the user's travel may be predicted by the pattern analysis module 122 to provide assured QoS to the user.
[0082] Therefore, the described methods and systems for data connectivity to provide
assured QoS may allow dynamic up gradation of subscription of the users based on data usage
pattern and patterns of drops in QoS. This may allow assured QoS to users wishing for consistent data throughput even during times of congestions and probable handoffs. Further, the described methods may allow users to avail better QoE along with ability to utilize high data rate applications like streaming videos on the move. Also, the described methods and systems may optimize usage of network resources providing higher average revenue per user and satisfied users to the service provider.
[0083] Fig. 2 illustrates a method 200 for providing assured QoS to users in a
communication network, according to an embodiment of the present subject matter. The order in which the method 200 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 methods. Additionally, individual blocks may be deleted from the methods without departing from the spirit and scope of the subject matter described herein. Furthermore, the methods can be implemented in any suitable hardware, software, firmware, or combination thereof
[0084] 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, fimctions, etc., that perform particular lunctions or implement particular abstract data types. The method may also be practiced in a distributed computing environment where fimctions 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.
[0085] A person skilled in the art will readily recognize that steps of the methods can be
performed by programmed computers. Herein, some embodiments are also intended to cover program storage devices, 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 configured to perform said steps of the exemplary methods.
[0086] Referring to Fig. 2, the method 200 may be implemented by the system 102.
[0087] At block 202, one or more of data usage pattern associated with at least one user
and patterns of drops in QoS may be identified. The drops in QoS may be associated with one of communication network congestion and handoffs between cell blocks. In one implementation, the data usage pattern of users may be identified by the pattern analysis module 122 of the system 102. Further, in said implementation, the data usage pattern may be based on parameters, such as throughput received by the user at different time instances, user's requested throughput based on the request of the applications used, user's throughput at different geographic locations, and user's throughput at different geographic locations at different time instances. Further, the data usage pattern may also provide details regarding the handoff patterns based on the data usage of users.
[0088] At block 204, one or more of probable data usage and probable drops in QoS may
be predicted based on one or more of the identified data usage pattern and the patterns of drops in QoS. In one implementation, the pattern analysis module 122 may predict the probable data usage of a user based on the data usage pattern of the user. As described before, the data usage pattern of different users may be different and the probable drops in QoS may be predicted based on both, the data usage pattern of users and, the pattern of drops of QoS.
[0089] At block 206, subscription of a user based on one or more of the predicted
probable data usage and probable drops in QoS may be temporarily upgraded. The temporary upgradation may either be based on a pre-approval provided by the user, or may be based on user approval to a prompt of upgrade. In one implementation, the service provider may provide a prompt to the user to confirm the upgradation.
[0090] At block 208, resources of a communication network may be reserved based on
the one or more of the predicted probable data usage and probable drops in QoS to provide assured QoS to users. In one implementation, the resource management module 124 of the system 102 may reserve the resources of different cell blocks to provide assured QoS to the users. For example, the E-DCH resources available with a cell block are limited. In case it is predicted that in a particular block, a user may utilize the data services during a time of day. In
such situations, the resource management module 124 may reserve certain E-DCH resources for the user to receive un-interrupted data services and assured QoS.
[0091] At block 210, handoffs between different cell blocks may be optimized based on
the data usage pattern of the users, to provide assured QoS. In one implementation, the data usage pattern may define the handoff patterns as well, based on the data usage of the users. Based on the handoff patterns of a user, the future handoffs for the user may be predicted. Further, handoffs between cell blocks may either be pre-approved, or optimized to provide smooth and fast handoffs for the user. This may ensure un-interrupted data services to the user and assured QoS.
[0092] Although embodiments for methods and systems for providing data connectivity
in a communication network have been described in a language specific to structural features and/or methods, it is to be understood that the invention is not necessarily limited to the specific features or methods described. Rather, the specific features and methods are disclosed as exemplary embodiments for data connectivity in the communication network.

I/We claim:
1. A method to provide assured quality of service (QoS) in a communication network, the
method comprising:
identifying one or more of a data usage pattern associated with at least one user and patterns of drops in QoS;
predicting one or more of probable data usage and probable drops in QoS based on one or more of the identified data usage pattern and the pattern of drops in QoS; and
reserving resources of the communication network based on the one or more predicted probable data usage and probable drops in QoS to provide assured QoS.
2. The method as claimed in claim 1, wherein identifying is based on statistical and data mining techniques.
3. The method as claimed in any one of the preceding claims, wherein the identifying comprises ascertaining time instances when the at least one user utilizes data services provided by a service provider, and wherein the ascertaining provides the data usage pattern associated with the at least one user.
4. The method as claimed in any one of the preceding claims, wherein the identifying comprises ascertaining geographic locations where the at least one user utilizes data services provided by a service provider, and wherein the ascertaining provides the data usage pattern associated with the at least one user.
5. The method as claimed in any one of the preceding claims, wherein the identifying comprises ascertaining communication network congestion and handoffs between cell blocks, and wherein the ascertaining provides the pattern of drops in QoS.
6. The method as claimed in any one of the preceding claims, further comprising temporarily upgrading subscription of at least one user based on one or more of the predicted probable data usage and probable drops in QoS, wherein the upgrading ensures assured QoS.
7. The method as claimed in any one of the preceding claims, further comprising predicting probable handoffs for the at least one user based on handoff patterns derived from the data usage pattern of the at least one user.
8. The method as claimed in claim 7, further comprising optimizing handoffs between different cell blocks based on predicted probable handoffs.
9. The method as claimed in claim 8, wherein the optimizing comprises one or more of customizing handoff threshold parameters and pre-approval of the predicted probable handoffs.
10. A system (102) to provide assured quality of service (QoS) in a communication network, the system (102) comprising:
a processor (112); and
a memory (116) coupled to the processor (112), the memory (116) comprising:
a pattern analysis module (122) configured to:
identify one or more of data usage pattern associated with at least one user and patterns of drops in QoS, wherein the drops in QoS are associated with at least one of communication network congestion and handoffs between cell blocks; and
predict probable handoffs based on handoff patterns derived from the data usage pattern of the at least one user; and
a handoff optimization module (126) configured to optimize handoffs for the at least one user between different cell blocks based on predicted probable handoffs.
11. The system (102) as claimed in any one of the preceding claims, wherein the optimization comprises one or more of customizing handoff threshold parameters and pre-approval of the predicted probable handoffs.
12. The system (102) as claimed in any one of the preceding claims, wherein the pattern analysis module (122) is further configured to predict one or more of probable data usage and probable drops in QoS based on one or more of the identified data usage pattern and the pattern of drops in QoS.
13. The system (102) as claimed in claim 12, wherein the system 102 further comprises a resource management module (124) configured to reserve resources of the
communication network based on the one or more predicted probable data usage and probable drops in QoS to provide assured QoS.
14. The system (102) as claimed in any one of the preceding claims, wherein the resource management module (124) is further configured to temporarily upgrade subscription of at least one user based on one or more of the predicted probable data usage and probable drops in QoS.
15. The system (102) as claimed in any one of the preceding claims, wherein the data usage pattern comprises time instances and geographic locations where the at least one user utilizes data services provided by a service provider.
16. A computer-readable medium having embodied thereon a computer readable program code for executing a method comprising:
identifying one or more of data usage pattern associated with at least one user and patterns of drops in QoS;
predicting one or more of probable data usage and probable drops in QoS based on one or more of the identified data usage pattern and the pattern of drops in QoS; and
reserving resources of the communication network based on the one or more predicted probable data usage and probable drops in QoS to provide assured QoS.