Classifications

• • H—ELECTRICITY
  • H04—ELECTRIC COMMUNICATION TECHNIQUE
  • H04W—WIRELESS COMMUNICATION NETWORKS
  • H04W48/00—Access restriction; Network selection; Access point selection
  • H04W48/18—Selecting a network or a communication service
• • H—ELECTRICITY
  • H04—ELECTRIC COMMUNICATION TECHNIQUE
  • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
  • H04L67/00—Network arrangements or protocols for supporting network services or applications
  • H04L67/50—Network services
  • H04L67/56—Provisioning of proxy services
  • H04L67/568—Storing data temporarily at an intermediate stage, e.g. caching
• • H—ELECTRICITY
  • H04—ELECTRIC COMMUNICATION TECHNIQUE
  • H04W—WIRELESS COMMUNICATION NETWORKS
  • H04W88/00—Devices specially adapted for wireless communication networks, e.g. terminals, base stations or access point devices
  • H04W88/02—Terminal devices
  • H04W88/06—Terminal devices adapted for operation in multiple networks or having at least two operational modes, e.g. multi-mode terminals

Definitions

• WiFi network services become more ubiquitous and accessible, in particular, in both indoor and outdoor environments, integration and utilization of WiFi networks by mobile devices are becoming a mechanism through which network operators can alleviate their data traffic load.
• LAN based networks such as WiFi networks and services can also provide a mechanism to enhance mobile device performance when used in conjunction with cellular networks and connections.
• FIG. 1A depicts an example diagram of an environment in which the present embodiments may be implemented, the environment including a mobile device which can access different network connections in communicating with remote entities;
• FIG. IB depicts an example diagram of a system where a host server facilitates management of traffic, content caching, and/or resource conservation between mobile devices (e.g., wireless devices), an application server or content provider, or other servers such as an ad server, promotional content server, or an e-coupon server in a wireless network (or broadband network) for resource conservation;
• mobile devices e.g., wireless devices
• an application server or content provider e.g., an application server or content provider
• other servers such as an ad server, promotional content server, or an e-coupon server in a wireless network (or broadband network) for resource conservation
• FIG. 1C depicts an example diagram of a proxy and cache system distributed between the host server and device which facilitates network traffic management between a device, an application server or content provider, or other servers such as an ad server, promotional content server, or an e-coupon server for resource conservation and content caching;
• FIG. IE depicts an example diagram showing the architecture of client side components in a distributed proxy and cache system
• FIG. IF depicts an example diagram of the example components on the server side of the distributed proxy and cache system
• FIG. 2A depicts a diagram illustrating example resources including a network evaluation and selection engine that is implemented as a component of a local-proxy, which may be a part of a distributed caching system that effects network resource conservation and application performance optimization;
• FIG. 2C depicts another example diagram illustrating the network evaluation and selection engine of FIG. 2A and the radio evaluation and selection engine of FIG. 2B being implemented in some embodiments where the local-proxy can be optional;
• FIG. 3 depicts a functional block diagram illustrating example components of a mobile device including a local proxy having a network evaluation and selection engine;
• FIG. 4 depicts a diagram illustrating a ping mechanism for parameter measurements which can be used in the network evaluation and selection engine
• FIGS. 5A and 5B respectively depict two network specific quality tables which can be adapted in the network evaluation and selection engine in gauging network quality levels
• FIG. 6A depicts a flow chart illustrating an example flow for network evaluation and selection
• FIG. 6B depicts a flow chart illustrating an example flow for radio evaluation and selection
• FIG. 7 depicts a flow chart of illustrating additional or alternative details of the example flows of FIGS. 6A-6B.
• FIG. 8 shows a diagrammatic representation of a machine in the example form of a computer system within which a set of instructions, for causing the machine to perform any one or more of the methodologies discussed herein, may be executed.
• Devices typically have multiple radios to access different networks (e.g., 3G, 4G, LTE, Wi-Fi, Bluetooth, and/or NFC) for data traffic.
• quantification of various network signal metrics can be used to select an optimal network such that quality of experience (QoE) can be enhanced for a given user and/or for a given device.
• QoE quality of experience
• one of the problems solved by the present disclosure is to measure this QoE from Application level (“App").
• App Application level
• the QoE can be determined on an application-by- application basis on each mobile device or for each user.
• the disclosed techniques facilitate measurements, computations, determinations, assessments, evaluations, quantifications or qualification of QoE and/or other suitable measurement of user experience to select the best network or the best radio/protocol (3G, 4G, LTE, Wi-Fi, Bluetooth, NFC) to use for the traffic (e.g., IP traffic) for a given mobile application.
• the best network or the best radio/protocol 3G, 4G, LTE, Wi-Fi, Bluetooth, NFC
• the traffic e.g., IP traffic
• the QoE is measured from the mobile device side(e.g., a local proxy 175 or 275 of the mobile device), and the present techniques can be implemented or measured at the application level on the mobile device.
• the techniques disclosed herein require no or little need for system level changes or measurements.
• One advantage includes reduction of the time it takes to generate or compute a bad or non- representative QoE outcome.
• Additional benefits of the presently disclosed technique include, for example, facilitating decisions in selecting an optimal or a best radio for use (e.g., 3G/4G or Wi-Fi) or an optimal,best network (e.g., WiFi networks offered among different access points (APs)), facilitating operator's ability to use the measured metrics for Wi-Fi off loading, and/or facilitating operator's ability to use the measured metrics for retrieving QoE numbers of their mobile networks at different time/locations.
• an optimal or a best radio for use e.g., 3G/4G or Wi-Fi
• an optimal,best network e.g., WiFi networks offered among different access points (APs)
• APs access points
• the techniques disclosed herein further include for network evaluation and selection, and more specifically for selecting a network from a number of available networks at a mobile device for communication by a mobile application.
• a method comprises measuring a set of parameters for each of the available networks using an application layer protocol (e.g., HTTP).
• parameters can include, for a given network, the Round-Trip Time (RTT) and/or Packet Loss (PL) parameters or other parameters for the applicable servers.
• RTT Round-Trip Time
• PL Packet Loss
• a quality level or an overall quality level for the given networks based on the parameters can be computed or assessed. More specifically, in some embodiments, a statistical parameter of the RTT and/or the PL, for example, a median RTT and an average PL (%) number for each server based on the readings can be calculated.
• median RTT and average PL are example metrics which can be used to assess the quality of experience (QoE) or user experience and the like with an application at a mobile device for a specific network or for a given radio; other suitable mathematical and/or statistical quantifiers can be computed or determined for evaluating quality of experience (QoE) or other types of user experience. Then, with the median RTT and/or the average PL for one or more servers, the quality determination module can assign a specific quality level to the servers, for example, based on a quality table which is specific to the given network or radio.
• the method further comprises determining an overall quality level for each of the available networks based on the parameters, and choosing the network based on the overall quality level.
• the set of parameters are measured by communicating with each of a plurality of predetermined servers within a respective network.
• the application layer protocol is able to establish communication with the servers without requiring an administrative privilege of the mobile device, which may be typically required for other applications that utilize lower-level measurements, thereby reducing the time and effort necessary for deployment.
• embodiments disclosed herein enable a quantified approach to measuring network signals so as to optimize user experience and a quantified approach to application-level Quality of Experience (QoE) measurements, which can serve as bases for selection of radios for the applications.
• QoE Quality of Experience
• FIG. 1A depicts an example diagram of an environment in which the present embodiments may be implemented.
• the depicted environment includes a mobile device 150 which can access different network connections (e.g., network 106 and other networks 108A- N) in communicating with remote entities such as a remote application server or content provider 110 and/or advertisement servers 120A-N.
• the networks 106 e.g., a cellular network
• 108A-N e.g., a WLAN/WiFi network
• a larger network 10 e.g., the Internet
• Functions and techniques disclosed for context aware traffic management for resource conservation in networks (e.g., network 106 and/or 108) and devices 150, can reside in a distributed proxy and cache system.
• the proxy and cache system can be distributed between, and reside on, a given client device 150 in part or in whole and/or host server 100 in part or in whole.
• the distributed proxy and cache system are illustrated with further reference to the example diagram shown in FIG. 1C.
• the present embodiments further recognize that it can be beneficial to measure the QoE from an application level, which can reduce the time to market as well as deployment to existing devices on the market because this approach generally requires no administrator permission (e.g., a root privilege) nor carrier or original equipment
• additional metrics which can be used to evaluate the QoE or user experience may include, for example, the amount of data traffic, quality of signal, power consumption characteristics of a particular network, battery status, network congestion, and so forth.
• the measured QoE can then be used to actively selectively enable one or more radios or radio modules on the mobile device in order to provide the optimal or the best user experience in general, and/oror with respect to a specific conditions, for example, for a given application or most applications at certain times of day or days of week, etc.
• the measured QoE can then be used to select one or more networks.
• the measured QoE can be used to enable radios and/or selection of networks (e.g., the best Wi-Fi network available or accessible, or the best mobile/cellular network within accessible range, or among 3G/4G/LTE and WiFi networks).
• a transmitted packet can be considered “lost” if during an HTTP socket connection either a "Timeout” (e.g., one second for each HTTP socket connection) or an "I/O exception” occurs.
• a percentage or probability of Packet Loss (PL) can be, for example, calculated by the parameter measurement module 232 for each HTTP socket connection.
• the evaluation and selection engine 250 reports the QoE as "0" or "none".
• some embodiments of the parameter measurement module 232 can perform a pseudo or a dummy HTTP Ping prior to the measuring to wake up a radio (e.g., cellular radio 240A) which corresponds to a respective network, and the results from this pseudo or dummy Ping is not measured.
• a radio e.g., cellular radio 240A
• dummy Pings can be sent to servers, and in one embodiment, one dummy Ping can be sent to each server. So, for example, if there are three servers (e.g., Yahoo, Google, CNN), then a total of three dummy Pings are sent.
• a Timeout period for a dummy Ping can be different than a Timeout period for an actual Ping from which RTT and/or PL results are measured.
• a Timeout for each dummy Ping is 20 seconds, and an example of Timeout for each actual Ping is 1 second.
• the parameter measurement module 232 sends out, for example, 5 Pings to each server. If there are, for example, three servers, then a total of 15 actual Pings are sent. Note that any number of servers can be used.
• the HTTP Pings can be sent by the parameter measurement module 232 to each server in a sequential manner (e.g., using a Round-Robin scheduling). Take the embodiment with three servers as an example, a first Ping can be sent to server A, a second Ping to server B, a third Ping to server C, a forth Ping to server A, and so forth.
• median RTT and average PL are example metrics which can be used to assess the quality of experience (QoE) or user experience and the like with an application at a mobile device for a specific network (e.g., to facilitate choosing among different WiFi networks, and/or different Cellular networks) or for a given radio (e.g., to facilitate choosing between WiFi versus Cellular); other suitable mathematical and/or statistical quantifiers can be computed or determined for evaluating quality of experience (QoE) or other types of user expereince.
• the quality determination module 234 can assign a specific quality level to the servers, for example, based on a quality table which is specific to the given network or radio.
• FIGS. 5A and 5B respectively depict two examples of such network specific quality tables: a table for a Cellular network or radio is depicted in FIG. 5A, and a table for a WiFi network or radio is depicted in FIG. 5B.
• the quality determination module 234 can select from the assessed quality levels.
• the quality level (QoE) selected is the highest or near the highest level out of the assessed quality levels.
• the overall QoE is selected based on the best QoE out of the three specific QoEs of the three servers.
• the term "highest" is measured in light of the assigned specific quality levels; for example, a QoE number of 5 is better than a QoE of 4, and a QoE of 4 is better than a QoE of 3, etc.
• the QoE can be determined on an application-by- application basis on each mobile device or for each user.
• the network evaluation and selection engine 230 can employ the switch module 236 to switch network based on the above-said QoE assessment(s).
• the switch can be among different networks under the same radio; in some embodiments, the switch can be among different networks across different radios.
• the engine 230 can switch from a 4G cellular network to a 3G cellular network under the same cellular radio module (even though, depending on the particular implementation of cellular radio chip, circuitry components and/or antennas that respectively in charge of 3G/4G connections may be different or the same).
• the engine 230 can switch from a cellular network offered by base station A to another cellular network offered by base station B under the same cellular radio module.
• the engine 230 can switch from one WiFi network offered by an access point A to another WiFi network offered by an access point B under the same WiFi radio module.
• the engine 230 can switch from a 4G cellular network to a IEEE 802.1 IN WiFi network; and in doing so, the engine 230 can selectively switch from the cellular radio to the WiFi radio.
• the network evaluation and selection engine 230 can continuously monitor the network condition and/or other parameters for network switching (e.g., Wi-Fi offloading) opportunities.
• evaluation and selection can measure the subscriber quality of experience (QoE) for available networks in real time or near real time to ensure a satisfactory subscriber experience.
• QoE subscriber quality of experience
• the best radio e.g., 3G/4G or Wi-Fi
• the best network e.g., WiFi networks offered among different access points
• operators or carriers can further utilize the results from the QoE assessment of their mobile networks of cell towers at various times and/or at different locations.
• the network evaluation and selection engine 230 can include a network monitoring module 238 which can perform the aforementioned measuring (e.g., of RTT and PL parameters) and determining (e.g., of specific and overall QoE numbers) periodically.
• the network monitoring module 238 causes the network switch module 236 to perform the aforementioned choosing when an overall quality level of a previously selected network deteriorates by a level (e.g., below a certain number (such as drop to 2), below a certain degree (from usable to unusable), drops a certain percentage (by 33%), etc.).
• a level e.g., below a certain number (such as drop to 2), below a certain degree (from usable to unusable), drops a certain percentage (by 33%), etc.
• the network monitoring module 238 determines that the overall quality level of a previously selected network has dropped from a usable level to an unusable level, then the aforementioned network evaluation and selection processes can be triggered.
• embodiments disclosed herein enable a quantified approach to user experience estimation and application-level Quality of
• QoE Quality of Experience
• FIG. 2B depicts a diagram illustrating example resources including a radio selection engine that is implemented as a component of a local-proxy, which may be a part of a distributed caching system that effects network resource conservation and application performance optimization.
• the radio evaluation and selection engine 231 includes similar modules as those in the network evaluation and selection engine 230.
• the radio evaluation and selection engine 231 includes a radio switch module 236A and a radio monitoring module 238A for radio selection.
• the radio evaluation and selection engine 231 can use a quantified approach to user experience estimation and application-level Quality of Experience (QoE) measurements, which can serve as bases for selection of radios for the applications.
• QoE Quality of Experience
• FIG. 2C depicts another example diagram illustrating the network evaluation and selection engine 230 of FIG. 2A and the radio evaluation and selection engine 231 of FIG. 2B being implemented in some embodiments where the local-proxy 275 can be optional.
• Applications 210 are example applications of the mobile device 250.
• Applications 102 on mobile device 250 can communicate with the application servers 1 10 (see FIG. 1A) via the networks 106 and 108A-N.
• Some examples of applications 210 include news application, weather services, web browsers with multimedia capabilities, video-sharing applications, online radio and music stations, video-on-demand services, and/or social network applications.
• each application 210 receives a plurality of data (e.g., audio streams or video clips) relevant or necessary to the operations (e.g., foreground and/or background operations) of the application from the application servers 110.
• the embodiments of local proxy 275 can enable carriers with policy-based control of offloading decisions (e.g., performed by the engine 230) by allowing the carriers to control and manage the policies (e.g., quality tables, quality level formulas, etc.) through suitable means.
• suitable means can include communications through the aforementioned proxy servers or other suitable components.
• the aforementioned quality tables and formulas for quality calculations can be defined/downloaded from the proxy server.
• the local proxy 275 identifies and takes advantage of offloading opportunities as they become available, thereby creating more available resources by directing subscribers to local WiFi networks to fulfill their mobile data requirements. As such, carrier costs can be reduced because more traffic is directed to lower-cost WiFi resources, rather than relying on higher- cost cellular network resources.
• network evaluation and selection engine 230 (e.g., in conjunction with the local proxy 275) can further include multiple configurable parameters including security, data usage, application context, battery life, speed/quality of connection, location, and time of day in considering the QoE ratings.
• the local proxy 275 can enhance end-user quality of experience, increase WiFi offload utilization, empower carriers with policy -based control, and deliver insight into mobile client behavior, improve network capacity utilization.
• FIG. 3 depicts a functional block diagram illustrating example components of a mobile device 350 including a local proxy 375 having a network evaluation and selection engine 330.
• the mobile device 350 further includes either accessible or installed thereon mobile application(s) 210 (see FIG. 2B), and a radio interface 340 including a plurality of network modules, each operable to connect to and communicate with networks 106 and 108A-N.
• Examples of the radios in the radio interface 340 include a cellular radio, a Bluetooth radio, and/or a WiFi or WLAN (WiFi) radio.
• the mobile device 350 also includes an RFID based near-field communication chip.
• the local proxy 375 can function as an intermediate stage or interface between the networks 106 and/or 108A-N and the mobile application(s) 210 on the mobile device 350. Overall, the mobile device 350 can communicate with any application server 1 10 for exchanging data (e.g., directly or through host server 100, see FIG. 1A).
• the network evaluation and selection engine 330 includes a parameter measurement module 332, a quality determination module 334, and a server list 336.
• a parameter measurement module 332 For simplicity, other modules such as the aforementioned network switch module and network monitoring module are not depicted in FIG. 3.
• the parameter measurement module 332 in the network evaluation and selection engine 230, 330 measures (610) a set of parameters for each of the available networks using an application layer protocol.
• the set of parameters are measured (612) by communicating with each of a plurality of servers within a respective network.
• the parameter measurement module 332 includes an HTTP Ping module 333 to send out Ping commands (e.g., with handshaking such as illustrated in FIG. 4) to each server on a server list 336.
• the parameter measurement module 332 sends out multiple pings (e.g., 5 Pings) to each server.
• the RTT monitor and PL monitor in the HTTP Ping module 333 can measure Round Trip Time (RTT) times and Packet Loss (PL) percentage numbers based on those multiple (e.g., 5) Pings to each server. Additionally or alternatively, the HTTP Pings module 333 can send the Ping messages to each server using Round-Robin scheduling.
• RTT Round Trip Time
• PL Packet Loss
• the quality determination module 334 determines (620) an overall quality level for each of the available networks based on the parameters. Thereafter, the network switch module 336 chooses (630) one or more networks (e.g., among the network modules 240) based on the overall quality level of each network.
• FIG. 6B depicts a flow chart illustrating an example flow for radio evaluation and selection; depicts a flow chart illustrating an example flow 600A for the radio evaluation and selection techniques disclosed herein. With additional reference to FIGS. 2B and 3, flow 600A is explained.
• the radio evaluation and selection engine 231 is to determine an over quality of experience (QoE) number for each radio of interest.
• QoE quality of experience
• the parameter measurement module in the radio evaluation and selection engine 231 measures (61 OA) a set of parameters for each of the available radios using an application layer protocol.
• the set of parameters are measured (612A) by communicating with each of a plurality of servers within a respective radio.
• the parameter measurement module includes an HTTP Ping module to send out Ping commands (e.g., with handshaking such as illustrated in FIG. 4) to each server on a server list.
• the parameter measurement module sends out multiple pings (e.g., 5 Pings) to each server.
• the RTT monitor and PL monitor in the HTTP Ping module can measure Round Trip Time (RTT) times and Packet Loss (PL) percentage numbers based on those multiple (e.g., 5) Pings to each server. Additionally or alternatively, the HTTP Pings module can send the Ping messages to each server using Round-Robin scheduling.
• RTT Round Trip Time
• PL Packet Loss
• the quality determination module determines (620A) an overall quality level for each of the available radios based on the parameters. Thereafter, the radio switch module 236A chooses (630A) one or more radios (e.g., among the radio modules 240) based on the overall quality level of each radio.
• FIG. 7 depicts a flow chart 700 of illustrating additional or alternative details of the example flow 600 of FIG. 6. With additional reference to FIGS. 2A, 2B and 3, flow chart 700 is explained. Steps 610/610A and 630/630A are the same as what are described above.
• Some embodiments of the parameter measurement module 332 can transmit (710) a pseudo or a dummy HTTP Ping message prior to the measuring to wake up a radio (e.g., cellular radio 240A) which corresponds to a respective network, and the results from this pseudo or dummy Ping is not measured.
• a radio e.g., cellular radio 240A
• one dummy Ping is performed per server.
• the quality determination module 334 can assign (720) a specific quality level to one or more servers within the respective network based on a quality table which is specific to the respective network. For example, a quality calculator module 335 A within the quality determination module 334 can calculate a median RTT and/or an average PL (%) number for one or more servers based on the readings. Then, with the median RTT and the average PL for one or more servers, the quality determination module 334 assigns (720) a specific quality level to each of the servers based on a quality table 335B which is specific to the given network (e.g., as tables illustrated in FIGS. 5A-5B).
• a quality table 335B which is specific to the given network
• the quality determination module 334 selects (725) a quality level from the assessed quality levels.
• the quality level (QoE) selected is the highest or of a higher level out of the assessed quality levels.
• the overall QoE can be converted or computed from the specific QoE numbers based on suitable or efficient formulas.
• the network evaluation and selection engine 230 or the radio evaluation and selection engine 231 can repeat (740) the aforementioned measuring (e.g., of RTT and PL parameters) and determining (e.g., of specific and overall QoE numbers) periodically.
• the network evaluation and selection engine 230 performs (750) the aforementioned network selection when the quality level of a previously selected network deteriorates.
• the radio evaluation and selection engine 231 performs (750) the aforementioned radio selection when the quality level of a previously selected radio deteriorates.
• FIG. 8 shows a diagrammatic representation of a machine in the example form of a computer system within which a set of instructions, for causing the machine to perform any one or more of the methodologies discussed herein, may be executed.
• the machine operates as a standalone device or may be connected (e.g., networked) to other machines.
• the machine may operate in the capacity of a server or a client machine in a client-server network environment, or as a peer machine in a peer-to-peer (or distributed) network environment.
• the machine may be a server computer, a client computer, a personal computer (PC), a user device, a tablet PC, a laptop computer, a set-top box (STB), a personal digital assistant (PDA), a cellular telephone, an iPhone, an iPad, a Blackberry, a processor, a telephone, a web appliance, a network router, switch or bridge, a console, a hand-held console, a (hand-held) gaming device, a music player, any portable, mobile, hand-held device, or any machine capable of executing a set of instructions (sequential or otherwise) that specify actions to be taken by that machine.
• PC personal computer
• PDA personal digital assistant
• machine-readable medium or machine-readable storage medium is shown in an exemplary embodiment to be a single medium, the term “machine-readable medium” and “machine-readable storage medium” should be taken to include a single medium or multiple media (e.g., a centralized or distributed database and/or associated caches and servers) that store the one or more sets of instructions.
• the term “machine- readable medium” and “machine-readable storage medium” shall also be taken to include any medium that is capable of storing, encoding or carrying a set of instructions for execution by the machine and that cause the machine to perform any one or more of the methodologies of the presently disclosed technique and innovation.
• routines executed to implement the embodiments of the disclosure may be implemented as part of an operating system or a specific application, component, program, object, module or sequence of instructions referred to as "computer programs.”
• the computer programs typically comprise one or more instructions set at various times in various memory and storage devices in a computer that, when read and executed by one or more processing units or processors in a computer, cause the computer to perform operations to execute elements involving the various aspects of the disclosure.
• machine-readable storage media machine-readable media, or computer-readable (storage) media
• recordable type media such as volatile and non-volatile memory devices, floppy and other removable disks, hard disk drives, optical disks (e.g., Compact Disk Read-Only Memory (CD ROMS), Digital Versatile Disks, (DVDs), etc.), among others, and transmission type media such as digital and analog communication links.
• CD ROMS Compact Disk Read-Only Memory
• DVDs Digital Versatile Disks
• transmission type media such as digital and analog communication links.
• the terms “connected,” “coupled,” or any variant thereof, means any connection or coupling, either direct or indirect, between two or more elements; the coupling of connection between the elements can be physical, logical, or a combination thereof.
• the words “herein,” “above,” “below,” and words of similar import, when used in this application, shall refer to this application as a whole and not to any particular portions of this application. Where the context permits, words in the above Detailed Description using the singular or plural number may also include the plural or singular number respectively.
• the word “or,” in reference to a list of two or more items covers all of the following interpretations of the word: any of the items in the list, all of the items in the list, and any combination of the items in the list.

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