WO2022225952A1 - Quality-of-experience assured networking via application-specific integrated network - Google Patents

Abstract

A method for providing quality of experience (QoE) for an application includes obtaining application specific integrated network (ASIN) information of the application for providing the QoE; configuring a network segment of an end-to end (E2E) ASIN based on the ASIN information to provide the QoE; and communicating data for the application using the network segment.

Description

Quality-of-Experience Assured Networking via Application-Specific Integrated Network

CROSS-REFERENCE TO RELATED APPLICATIONS [0001] This application claims priority to U.S. Provisional Application Ser. No. 63/177,717 filed April 21, 2021.

TECHNICAL FIELD

[0002] The present application relates to network communication, and more specifically to systems and methods for quality-of-experience (QoE) assured networking via an application specific integrated network (ASIN).

BACKGROUND

[0003] The recent pandemic has significantly impacted daily life around the world. Due to social distancing, most people have increasingly relied on online tools such as Zoom® for communication and social activities. To meet the added demand for online conferencing and other virtual interactions, online tools need to provide sufficient bandwidth with low latency and improve the QoE during these interactions. To provide a seamless user experience via video/audio interaction with others, the underlying network needs to meet the requirements on bandwidth, latency, and QoE at multiple levels.

SUMMARY

[0004] A first aspect relates to a method for providing quality of experience (QoE) for an application. The method includes obtaining application specific integrated network (ASIN) information of the application for providing the QoE; configuring a network segment of an end-to end (E2E) ASIN based on the ASIN information to provide the QoE; and communicating data for the application using the network segment.

[0005] A second aspect relates to an apparatus for providing QoE for an application. The apparatus includes memory storing instructions; and a processor in communication with the memory, the processor configured to execute the instructions to cause the apparatus to obtain ASIN information of the application for providing the QoE; configure a network segment of an E2E ASIN based on the ASIN information to provide the QoE; and communicate data for the application using the network segment. [0006] A third aspect relates to an ASIN comprising an E2E Network Slicing Controller and multiple network segments to assure the QoE requested by a given application.

[0007] A fourth aspect relates to computer program product comprising computer-executable instructions that are stored on a non-transitory computer-readable medium and that, when executed by a processor, cause a computing device to: obtain ASIN information of the application for providing the QoE; configure a network segment of an E2E ASIN based on the ASIN information to provide the QoE; and communicate data for the application using the network segment.

[0008] Optionally, in a first implementation according to any of the preceding aspects, the network segment is a Wi-Fi network.

[0009] Optionally, in a second implementation according to any of the preceding aspects or implementation thereof, the network segment is an Internet protocol (IP) network.

[0010] Optionally, in a third implementation according to any of the preceding aspects or implementation thereof, the network segment is an optical transport network (OTN).

[0011] Optionally, in a fourth implementation according to any of the preceding aspects or implementation thereof, the network segment is cloud data center network.

[0012] Optionally, in a fifth implementation according to any of the preceding aspects or implementation thereof, the network segment is an access network.

[0013] Optionally, in a sixth implementation according to any of the preceding aspects or implementation thereof, the access network is a passive optical network (PON).

[0014] Optionally, in a seventh implementation according to any of the preceding aspects or implementation thereof, the IP network is an enhanced IP network.

[0015] Optionally, in an eighth implementation according to any of the preceding aspects or implementation thereof, the enhanced IP network is a New IP network.

[0016] Optionally, in a ninth implementation according to any of the preceding aspects or implementation thereof, the method further includes, or the processor further executes instructions for, performing soft slicing of the IP network in configuring the network segment based on the ASIN information to provide the QoE.

[0017] Optionally, in a tenth implementation according to any of the preceding aspects or implementation thereof, the method further includes, or the processor further executes instructions for, performing hard network slicing of the OTN based on the ASIN information to provide the QoE. [0018] Optionally, in an eleventh implementation according to any of the preceding aspects or implementation thereof, the method further includes, or the processor further executes instructions for, obtaining the based on the ASIN information from an E2E Network Slicing Controller.

[0019] Optionally, in a twelfth implementation according to any of the preceding aspects or implementation thereof, the ASIN information comprises New IP contract and metadata information.

[0020] Optionally, in a thirteenth implementation according to the of the preceding aspects or implementation thereof, the OTN is selected by an E2E Network Slicing Controller for hard network slicing.

[0021] Optionally, in a fourteenth implementation according to any of the preceding aspects or implementation thereof, the QoE is measured based on a set of performance indicators.

[0022] Optionally, in a fifteenth implementation according to any of the preceding aspects or implementation thereof, the set of performance indicators comprises bandwidth, latency, time jitter, and packet loss rate.

[0023] Optionally, in a sixteenth implementation according to any of the preceding aspects or implementation thereof, the method further includes, or the processor further executes instructions for, specifying a cross-layer interface to an adjacent network segment, wherein the cross-layer interface supports network slicing capabilities needed for meeting various levels of QoEs.

[0024] Optionally, in a seventeenth implementation according to any of the preceding aspects or implementation thereof, the Wi-Fi network considers the ASIN information when selecting Physical layer (PHY) transmission parameters scheduled by a Media Access Control (MAC) layer. [0025] Optionally, in an eighteenth implementation according to any of the preceding aspects or implementation thereof, the Wi-Fi network considers the ASIN information when performing link adaptation.

[0026] Optionally, in a nineteenth implementation according to any of the preceding aspects or implementation thereof, the Wi-Fi network considers the ASIN information when performing admission control mechanism.

[0027] Optionally, in a twentieth implementation according to any of the preceding aspects or implementation thereof, the Wi-Fi network communicates the ASIN information to a Wi-Fi air interface. [0028] Optionally, in a twenty-first implementation according to any of the preceding aspects or implementation thereof, the Wi-Fi network is configured to queue and process packets based on the ASIN information.

[0029] Optionally, in a twenty-second implementation according to any of the preceding aspects or implementation thereof, the application is hosted in a local user equipment (UE), and the UE communicates the ASIN information with the E2E Network Slicing Controller.

[0030] Any one of the foregoing embodiments may be combined with any one or more of the other foregoing embodiments to create a new embodiment within the scope of the present disclosure.

[0031] These and other features, and the advantages thereof, will be more clearly understood from the following detailed description taken in conjunction with the accompanying drawings and claims.

BRIEF DESCRIPTION OF THE DRAWINGS [0032] For a more complete understanding of this disclosure, reference is now made to the following brief description, taken in connection with the accompanying drawings and detailed description, wherein like reference numerals represent like parts.

[0033] FIG. 1 is a schematic diagram illustrating a network configuration for an application in accordance with an embodiment of the present disclosure.

[0034] FIG. 2 is a schematic diagram illustrating a first example of network bandwidth requirements for an application in accordance with an embodiment of the present disclosure. [0035] FIG. 3 is a schematic diagram illustrating a second example of network bandwidth requirements for an application in accordance with an embodiment of the present disclosure. [0036] FIG. 4 is a schematic diagram illustrating a third example of network bandwidth requirements for an application in accordance with an embodiment of the present disclosure. [0037] FIG. 5 is a schematic diagram illustrating an ASIN in accordance with an embodiment of the present disclosure.

[0038] FIG. 6 is a block diagram illustrating a network configuration for implementing an E2E ASIN in accordance with some embodiments of the present disclosure.

[0039] FIG. 7 is a schematic diagram illustrating PHY transmission parameter selection in accordance with some embodiments of the present disclosure. [0040] FIG. 8 is a table for modulation coding scheme (MCS) selection in accordance with some embodiments of the present disclosure.

[0041] FIG. 9 is a schematic diagram illustrating a link adaptation process in accordance with some embodiments of the present disclosure.

[0042] FIG. 10 is a schematic diagram illustrating an admission control process in accordance with some embodiments of the present disclosure.

[0043] FIG. 11 is a schematic diagram illustrating an enhanced traffic classification process in accordance with some embodiments of the present disclosure.

[0044] FIG. 12 is a schematic diagram illustrating an enhance traffic classification process in accordance with some embodiments of the present disclosure.

[0045] FIG. 13 is a schematic diagram illustrating cross layer signaling in accordance with some embodiments of the present disclosure.

[0046] FIG. 14 is a schematic diagram illustrating a data packet for providing ASIN information in accordance with some embodiments of the present disclosure.

[0047] FIG. 15 is a flowchart diagram illustrating a method for providing QoE for an application in accordance with some embodiments of the present disclosure.

[0048] FIG. 16 is a schematic diagram of an apparatus configured to implement one or more of the methods disclosed herein according to an embodiment of the disclosure.

DETAILED DESCRIPTION

[0049] It should be understood at the outset that, although illustrative implementations of one or more embodiments are provided below, the disclosed systems and/or methods may be implemented using any number of techniques, whether currently known or in existence. The disclosure should in no way be limited to the illustrative implementations, drawings, and techniques illustrated below, including the exemplary designs and implementations illustrated and described herein, but may be modified within the scope of the appended claims along with their full scope of equivalents.

[0050] To provide a seamless user experience via video/audio interaction with others, the underlying network needs to meet the network requirements. As an example, Zoom® is a video conferencing platform. Zoom® currently uses five different Internet service providers (ISPs) for its servers and supports up to 80 gigabits (G) of bandwidth. US data center racks are provisioned with 40 gigabits per second (Gbps) of connectivity. Zoom® uses a proprietary adaptive codec in the session layer, which optimizes the video frame rate and resolution. Zoom® also uses multiple streams, allowing the application to toggle between streams to ensure that the best quality video gets delivered to end users. In regard to the bandwidth requirements on the customer end, Zoom® has recommended bandwidth for meetings and webinar panelists are as follows:

[0051] For 1:1 video calling: for high-quality video: 600 kilobits per second (kbps) (up/down), for 720p High definition (HD) video: 1.2 megabits per second (Mbps) (up/down), and for 1080p HD video: 3.8 Mbps/3.0M bps (up/down).

[0052] For group video calling: for high-quality video: 1.0 Mbps/600 kbps (up/down), for 720p HD video: 2.6 Mbps/1.8 Mbps (up/down), and for 1080p HD video: 3.8 Mbps/3.0 Mbps (up/down).

[0053] For gallery view receiving: 2.0 Mbps (25 views), 4.0 Mbps (49 views).

[0054] For screen sharing only (no video thumbnail): 50-7 5kbps.

[0055] For screen sharing with video thumbnail: 50-150 kbps.

[0056] For audio Voice over Internet Protocol (VoIP): 60-80 kbps.

[0057] For Zoom Phone: 60-100 kbps.

[0058] The recommended bandwidth for meetings and webinar panelists is as follows:

[0059] For 1:1 video calling: for high-quality video: 600 kbps (up/down), for 720p HD video: 1.2 Mbps (up/down), and for 1080p HD video: 3.8 Mbps/3.0 Mbps (up/down).

[0060] For group video calling: for high-quality video: 1.0 Mbps/600 kbps (up/down), for 720p HD video: 2.6 Mbps/1.8 Mbps (up/down), and for 1080p HD video: 3.8 Mbps/3.0 Mbps (up/down).

[0061] For gallery view receiving: 2.0 Mbps (25 views), 4.0 Mbps (49 views).

[0062] For screen sharing only (no video thumbnail): 50-75 kbps.

[0063] For screen sharing with video thumbnail: 50-150 kbps.

[0064] For audio VoIP: 60-80 kbps.

[0065] For Zoom® Phone: 60-100 kbps.

[0066] The above bandwidth requirements are the application specific requirements of the Zoom® application.

[0067] As another example of an application specific requirement, the free viewpoint video and volumetric video (FV3) application seeks to enable video (e.g., live sports or entertainment) to be interactively controlled and viewed at any angle and any 3D position in space at any moment in time from anywhere in the world. The goal of FV3 is to provide real-time seamless panning and zooming at any viewpoint and enable slow motion and many other special effects. To enable such features, current network bandwidth would have to be increased potentially 10-1000 times. For example, for the best experience (e.g., 8K Ultra HD (UHD); 240 frames per second (fps); 12-bit color), the bandwidth requirements would be -287 Gbps per camera raw, and for the basic experience (e.g., 4k UHD; 30 fps; 8-bit color), the bandwidth requirements would be -6 Gbps per camera raw.

[0068] FIG. 1 illustrates a network configuration for an application that provides media from an array of cameras in accordance with an embodiment of the present disclosure. In the depicted embodiment, an array of cameras (CAMs) 102 are communicatively coupled to a server 104. The server 104 could be either a local server or a cloud server. The server 104 executes an application that provides media (e.g., video or audio/video images) from the array of cameras 102 to one or more user devices 108. The user devices 108 may be mobile or non- mobile devices connected to a communication network via either a wireless link (e.g., cellular, or Wi-Fi) or wired link (e.g., Ethernet). The server 104 communicates the media over the network to a server 106 that is closer to the one or more user devices 108. The server 106 may be an edge server or a cloud server. An edge server is a server that is located on the edge or entry/exit point of a network. A cloud server is a physical or virtual server configured to provide services over a network to one or more client devices. The server 106 then delivers the media to the one or more user devices 108. The network configuration of FIG. 1 and depicted devices are just an example, and various other network configurations and devices may be applicable to the disclosed embodiments (e.g., media downloaded or streaming from a content media server as opposed to the array of cameras 102, or media from one end user device to another end user device).

[0069] FIG. 2 illustrates a first example of an E2E network bandwidth requirement for delivering the media from the array of cameras 102 to the one or more user devices 108 of FIG. 1. In the depicted embodiment, assume the array of cameras 102 are 38 x 4K [3840x2160] red, green, and blue (RGB) cameras that provide motion Joint Photographic Experts Group (M-JPEG or MJPEG) files instead of Moving Picture Experts Group (MPEG) files, where 1 frame (8-bit color) raw data size is 199 megabytes (MB) and M-JPEG without perceivable loss of quality (10:1) 1 frame is -20 Mb. Assuming a server processing and server-side adaptive switching system configuration (i.e., client receiving 1 channel of video normally and multiple when switching), and that each camera 102 provides media at 30 fps and 1 camera data rate is -0.6 Gbps, then the bandwidth required is -6 Gbps at switching (i.e., where the cameras 102 are combined) for RAW files when there is a 10-camera look-ahead. A 10-camera look-ahead means a client-side device needs to buffer 10 additional video streams from 10 cameras that are adjacent to a camera that corresponds to a current viewpoint. When panning, 10-camera look-ahead enables fast switching to not just the adjacent camera or the one next to the adjacent camera, but 10 cameras ahead. [0070] A RAW file is the uncompressed and unprocessed image data captured by a digital camera or scanner’s sensors. The RAW file format stores the largest amount of detail out of any raster file type, which can then be edited, compressed, and converted into other formats. However, the bandwidth requirement for transmitting RAW files is high because the images are so large due to being uncompressed and unprocessed. For 38 cameras, the bandwidth required at the server 104 for RAW files is >20 Gbps. The bandwidth required for RAW files between the server 106 and the one or more user devices 108 will depend on the particular system solution.

[0071] In comparison, the bandwidth requirement for MJPEG and H.265 image formats are much lower as shown in FIG. 2. MJPEG is a slow series of individually compressed pictures. Although MJPEG images are compressed, MJPEG images are still 10 times larger than H.265 images. For instance, the bandwidth required is - 600 Mbps at switching for MJPEG when there is a 10-camera look-ahead in comparison to -60 Mbps for H.265. MJPEG is typically only used with cameras when lots of data is not being stored. For example, MJPEG may be used with a doorbell camera because on average only about 3 minutes of video are stored a day. H.265 (H.265 is the successor to H.264) uses what are called "Golden Frames," which are 100% true images, and then uses block-oriented compression to define the differences from Frame A to Frame B. If part of Frame B differs from the Golden Frame, then it is updated; if not, then it just uses the Golden Frame's information. This saves massive amounts of storage space without really losing anything of value. Most surveillance cameras use H.264/H.265, which is considered the industry standard. The bandwidth requirements for the remainder of the E2E network for MJPEG and H.265 are shown in FIG. 2. For client-side adaptive switching system configuration, (i.e., 38 channels of video data need to be streamed to end user/client), not depicted, at 30 fps and 1 camera data rate is -0.6 Gbps, then the total data rate for 38 cameras is ~23Gbps.

[0072] FIG. 3 illustrates a second example of an E2E network bandwidth requirement for delivering the media from the array of cameras 102 to the one or more user devices 108. In the second example, assuming a server processing, server-side adaptive switching system configuration, and that each camera 102 provides media at 240 fps, and 1 camera data rate is ~4.8 Gbps, then the bandwidth required for RAW is ~48 Gbps at switching when there is 10-camera look-ahead. For 38 cameras, the bandwidth required at the server 104 for RAW files is >1 terabytes per second (TB). In comparison, the bandwidth requirements for the E2E network for MJPEG and H.265 for the above cameras are shown in FIG. 3. For client processing and client- side adaptive switching system configuration, at 240 fps and 1 camera data rate is —4.8 Gbps, then the total for 38 cameras is -182 Gbps, which is greater than the bandwidth of fifth generation (5G) wireless.

[0073] FIG. 4 illustrates a third example of an E2E network bandwidth requirement for delivering the media from the array of cameras 102 to the one or more user devices 108. In this example, assume the array of cameras 102 are 38 x 8K [7680x4320] cameras that supports 8K UHD. The array of cameras 102 provides l-2bit color RAW 1 frame at -1.2 Gb and M-JPEG without perceivable loss of quality (10: 1) 1 frame at -0.12 Gb. Assuming a server processing and server-side adaptive switching system configuration, at 30 fps, and 1 camera data rate is -3.6 Gbps, then the bandwidth required for RAW is -36 Gbps at switching when there is 10-camera look ahead, which is greater than 5G wireless bandwidth. For comparison, the bandwidth requirements for the E2E network for MJPEG and H.265 for the above cameras are also shown in FIG. 4. For client processing and client-side adaptive switching system configuration, at 30 fps and 1 camera data rate is -3.6 Gbps; then the total data rate for 38 camera is -137 Gbps, which is also greater than 5G wireless bandwidth.

[0074] As shown in FIGS. 2-4, there is a tradeoff between the bandwidth requirement versus the QoE. Unfortunately, there is no E2E mechanism to give a desired QoE in E2E network slicing fashion in various network segments crossing Level 3 (L3) / Level 2 (L2) / Level 1 (LI) domains for the example requirements laid out above. Existing technology on each network segment provides the best QoE either with an aggregated (traffic) fashion or without having any knowledge of the underlying traffic. In some circumstances, mechanisms like those described above resort to dedicated network infrastructure, which is very difficult and expensive to build.

[0075] Disclosed herein are technical solutions to the above technical problem. The disclosed embodiments provide QoE assured networking via an ASIN. The ASIN accounts for application requirements from E2E. The ASIN may include access networks (e.g., Wi-Fi), passive optical networks (PON)), and X-haul/Core networks (e.g., transport network with following network segments: LI (optical transport network (OTN)), L2 (Ethernet), L3 (Internet Protocol (IP), New IP).

[0076] The technical solutions provided in the present disclosure involve assuring various levels of QoE requirements (e.g., for audio, video, static background, time-sensitive interactions, high- resolution presentation). The techniques in the present disclosure make the underlying network layers (e.g., LI, L2, and L3) work together in an E2E network slicing fashion to assure application- specific QoE requirements, which is referred to herein as ASIN. As an example, ultra-low latency for a certain slice of a data stream can be ensured by prioritized E2E transmission and routing. As another example, ultra-low packet loss for a certain slice of a data stream can be ensured by enhanced E2E protection and decoding.

[0077] FIG. 5 illustrates a non-limiting example of an E2E ASIN 500 for an application executing on a user device 502 in accordance with an embodiment of the present disclosure. The user device 502 may be any type of electronic device that can execute the application and access the network such as, but not limited to, smartphones, tablets, laptops, computers, televisions, Internet of Things (IoT) devices, and connected/smart vehicles. The application can be any type of application that sends and/or receives data over the network. For example, the application may be a video streaming application that receives and displays live streaming video from an edge cloud 512 (e.g., live streaming a sporting event). Various other applications may also be employed with the E2E ASIN 500 including, but not limited to, video conferencing or video chat application, video streaming application of movies or other content, and online gaming application. In an embodiment, the application has a set of network performance requirements for providing a QoE to a user of the user device 502. QoE, also sometimes referred to as quality of service (QoS), is a measure of performance based on both objective and subjective psychological measures of using an information communication technology (ICT) service or product (i.e., any service or product (e.g., a computer, tablet, and mobile phone) used to send or receive information (e.g., send email, browse the Internet, make a video call). In some embodiments, QoE is based on a measure of one or more network performance indicators including, but not limited to, bandwidth, latency, time jitter, and packet loss rate.

[0078] In the depicted embodiment, the E2E ASIN 500, indicated by the dashed line, for the user device 502 includes an access network 506, an aggregation network 508, a core network 510, and an edge/core cloud network 512. In other embodiments, the E2E ASIN 500 may omit one or more of the networks depicted in FIG. 5 or may include one or more other networks not depicted in FIG. 5. As will be further described, each of the segments of the E2E ASIN 500 is configured to meet the QoE performance requirements for data communication of the application to guarantee an E2E QoE (e.g., bandwidth and latency guaranteed session). In some embodiments, the application specific performance requirements information is used in the MAC/L2 and PHY/Ll layers to provide better QoE. The access network 506 is a network that connects subscribers (e.g., user device 502) to a network service provider and, through the carrier network, to other networks such as the Internet. In some embodiments, the access network 506 may include an Ethernet network, a digital subscriber line (DSL), a cellular network (e.g., 5G), a Wi-Fi network, or a passive optical network (PON)). In some embodiments, the user device 502 may connect to an access point (AP) 504. The AP 504 is a networking device that allows wireless-capable devices to connect to a wired network. A PON is a fiber-optic telecommunications network that uses unpowered optical splitters for delivering broadband network access to end-users.

[0079] In some embodiments, the PON is configured to provide network slicing capability, as well as a slice interface with the transport network segment to achieve E2E network slicing. Network slicing overlays multiple virtual networks on top of a shared physical network infrastructure. Network slicing can be performed on both wired and wireless networks. For example, 5G network slicing is a network architecture that enables the multiplexing of virtualized and independent logical networks on the same physical network infrastructure. Each network slice is an isolated end-to-end network tailored to fulfill diverse requirements requested by a particular application. Each slice of the network can have its own logical topology, security rules and performance characteristics within the limits imposed by the underlying physical networks.

[0080] Different slices can be dedicated to different purposes, such as ensuring a specific application or service gets priority access to capacity and delivery or isolating traffic for specific users or device classes. Slicing networks enable the network operator to maximize the use of network resources and service flexibility.

[0081] In some embodiments, one or more segments of the E2E ASIN 500 are provisioned as a hard slice. A hard slice provisions resources in such a way that the services that they carry are fully isolated from other services, short of network failures. As a result, services running over hard slices can be engineered to have an absolute or guaranteed level of performance to meet the QoE performance requirements of the application executing on the user device 502. Non-limiting examples of resources used to build hard slices are time-division multiplexing (TDM) time slots (time isolation) and wavelength-division multiplexing (WDM) optical channels (frequency isolation). In contrast, soft slices provision resources in such a way that, while the services they carry do not, on average, interfere with each other (and one service cannot receive another’s packets), they usually compete for resources, such as their position in a buffer queue, or central processing unit (CPU) cycles.

[0082] In an embodiment, the bandwidth requirement for a given service in the E2E ASIN 500 can be met via an E2E hard slice that guarantees the bandwidth requirement, without contention- induced bandwidth reduction, etc. In some embodiments, the bandwidth requirement of the application is variable (i.e., can vary). In some embodiments, the bandwidth requirement of the application is met by a network slice whose bandwidth closely matches the required bandwidth. [0083] The latency and time jitter requirements for a given service in the E2E ASIN 500 can be met via an E2E hard slice with prioritized latency supports. The packet loss rate or bit error rate (BER) requirement for a given service in the E2E ASIN 500 can be met via an E2E hard slice that has sufficient encoding and decoding capabilities.

[0084] The aggregation network 508 aggregates the traffic from multiple access networks and forwards the data from the access networks to the core network 510. The core network 510, also known as a transport network, interconnects networks to provide a path for the exchange of information between different local area networks (LANs) or subnetworks. The core network 510 can connect diverse networks over wide areas. The core network 510 may include an IP network and an OTN. An OTN is a network of optical elements or devices that communicate using a system of laser pulses for transmission. In some embodiments, the OTN provides low-latency hard slice capabilities via the use of optical service units (OSUs), while the IP network provides low-cost slice capabilities.

[0085] An IP network refers to any group of devices, each with their own unique IP addresses, connected under the same network topology, and utilizes the IP to send and receive messages between one or more computers. In some embodiments, the IP network may be a New IP network. New IP is a data plane technology that defines a new network datagram format, its specification (spec), and corresponding capabilities in the network nodes. The New IP packet includes a header spec, a shipping spec, a contract spec, and a payload spec. The header spec describes the offsets (i.e., indicate the beginning and possibly length) of the shipping spec, the contract spec, and the payload spec. The shipping spec supports a flexible address format scheme, is backward compatible (i.e., existing addressing schemes, e.g., legacy IP, Multiprotocol Label Switching (MPLS) or other well-known packet type support only by use of address type field), and supports hybrid addressing formats. The flexible address format scheme allows different types of address namespaces to be embedded. The contract spec enables a variety of contract services. A New IP contract describes a formal service specification of a service, which includes clauses to describe the type of network service capability, actions, and accounting information. A New IP contract can be understood as a service-specific arrangement between two or more parties. The parties may include an application and network, or inter-network ISPs, application, and end-user. New IP contracts can also provide instructions for monitoring. In comparison to traditional QoS/QoE, contracts operate at a much lower level - per packet, and instruct in high-level abstract commands. The payload spec associates network semantics to the user data while maintaining the payload integrity. New IP is open, highly virtualized, software-centric, vendor agnostic, automated, flexible, and scalable. For example, a New IP network can include programmable network devices to innovate more rapidly at lower cost.

[0086] In the depicted embodiment, the core network 510 communicates data with the edge cloud 512. The edge cloud 512 is a network of devices located on the edge of the operator network closer to the user. The edge cloud enables the service provider to provide better QoE to users because of its proximity to the user. In some embodiments, the edge cloud performs the application processing and streaming. For example, the edge cloud 512 may receive all the data of a live event from a plurality of cameras and process the data for streaming to the user device 502. In some embodiments, the edge cloud 512 may be a cloud data center network. A data center is a facility that centralizes an organization's shared network operations and equipment. A cloud data center network is a data center network managed on the cloud or Internet. A data center network interconnects all the data center resources together. A cloud data center moves a traditional on premises data center off-site. Instead of personally managing their own infrastructure, an organization leases infrastructure managed by a third-party partner and accesses data center resources over the Internet. In some embodiments, the cloud data center can include inter data center interconnections and/or intra data center interconnections. The cloud data center may also include servers that support the application and evaluate its QoE. [0087] FIG. 6 is a block diagram illustrating a network configured to implement an E2E ASIN in accordance with some embodiments of the present disclosure. In the depicted embodiment, an E2E network slicing controller 600 is configured to communicate with a host 606, an access network 608, a transport network 610, a cloud network 612, and a server 614. The host 606 is any device on which an application is executing that is configured to or requests E2E guaranteed QoE. The server 614 may be a device that is providing the data (e.g., streaming video) to the host 606. As described in FIG. 5, communication between the host 606 and the server 614 may pass through the access network 608, the transport network 610, and the cloud network 612. The E2E network slicing controller 600 may be located any place on a service provider network, e.g., on the cloud network 612. In some embodiments, the E2E network slicing controller 600 includes a link or interface to the host 606, the access network 608, the transport network 610, the cloud network 612, and the server 614 for communicating ASIN information of an application to the host 606, the access network 608, the transport network 610, the cloud network 612, and the server 614 for establishing an E2E ASIN. In some embodiments, the ASIN information for an application may include QoE performance requirements, a New IP contract, and various metadata. The QoE performance requirements may specify a bandwidth, response time, end-to-end latency, jitter, bit error rate, packet loss ratio, etc.

[0088] In an embodiment, the host 606 with New IP contract and metadata specifies the ASIN information. In addition, the access network 608 fulfills QoE of ASIN, e.g., with information from New IP (cross layer signaling). The various segments (L1/L2/L3) in the network through cross layer signaling fulfill the desired ASIN QoE. The cloud network 612 fulfills the ASIN QoE and access control as desired. The server 614 is configured to provide local ASIN QoE.

[0089] As described above, the disclosed ASIN aims to provide QoS/QoE to specific applications with integrated support from all the network elements and communication protocol layers. As a commonly used access technology, Wi-Fi plays an important role to support end-to- end QoS/QoE for specific applications. The disclosed embodiments include multiple points of technical innovation for Wi-Fi MAC/PHY layers to support ASIN including the following technical improvements:

[0090] 1) Consider application specific information when selecting PHY transmission parameters scheduled by the MAC layer, i.e., use application specific QoS/QoE requirements information and traffic characteristic information as one of the considerations to select PHY transmission parameter settings. That is, use PHY transmission parameter setting as an additional QoS/QoE provisioning tool.

[0091] 2) Consider application specific information when performing link adaptation, e.g., add application specific information into the consideration of link adaptation procedures in the MAC layer to select and adjust the parameters so that the best possible performance for the specific application can be achieved, and introduce the link adaptation mechanisms to per traffic flow/stream level, in addition to current per link/station (STA) level.

[0092] 3) Consider application specific information in admission control mechanisms.

[0093] 4) Communicate application specific information to a Wi-Fi air interface.

[0094] 5) Queue and process packets with application specific information.

[0095] Each of the above technical improvements are discussed further below.

[0096] In current Institute of Electrical and Electronics Engineers (IEEE) 802.11/ Wi-Fi, the Wi-Fi PHY transmission parameter setting mechanisms are mainly based on channel conditions, e.g., receive signal strength indicator (RSSI), signal-to-noise ratio (SNR), the number of re transmissions, MCS, etc., where application specific information is not considered. Therefore, it is new in Wi-Fi to consider application specific information (e.g., QoS/QoE requirements, traffic characteristics) when selecting PHY transmission parameters.

[0097] The current IEEE 802.11/Wi-Fi QoS/QoE mechanisms are mainly based on providing differentiated channel access opportunities to different STAs based on access category/user priority through MAC timing parameters, e.g., the contention window size, back-off time, inter frame space, etc., where PHY parameter selection is not considered. Therefore, it is new in Wi-Fi to use PHY transmission parameter selection as a QoS/QoE provisioning tool.

[0098] The link adaptation in current IEEE 802.11/Wi-Fi generally refers to the processes/procedures that are used to dynamically adjust the PHY transmission parameters coordinated by a MAC scheduler, mainly modulation / coding schemes, based on the channel condition to achieve a best possible link performance. The link adaptation is used for adjusting some PHY parameter settings, but it is different from PHY parameter setting, as PHY parameter setting does not have to use link adaptation, but can just use static parameter setting.

[0099] The disclosed embodiments use the application specific information in link adaptation. The link adaptation can be either open-loop or closed-loop. Open-loop link adaptation: no message exchanges between transmitter (Tx) and receiver (Rx) specifically for link adaptation purpose; and the link adaptation is conducted by Tx based on the Tx’s understanding of the link condition. Closed-loop link adaptation: there are message exchanges between Tx and Rx specifically for link adaptation purpose; and the link adaptation is conducted by Tx based on the link condition information provided by Rx.

[0100] The current IEEE 802.11/Wi-Fi link adaptation mechanisms are based on link condition, while the present disclosure adds application specific information into the consideration of selecting the proper PHY parameters so that the best possible performance for the specific application can be achieved.

[0101] The current IEEE 802.11/Wi-Fi link adaptation mechanisms are based on channel condition on per link/STA basis, while the disclosed embodiments introduce the link adaptation mechanisms to the traffic slice/flow/ stream level.

[0102] The current IEEE 802.11/Wi-Fi admission control mechanisms use the channel condition information when determining whether a new traffic stream (TS) addition request can be accepted, where the channel condition does not consider the impact from the PHY parameter settings using application specific information. However, the PHY parameter settings do have certain impacts on the channel condition, e.g., the available data rate of the channel depends on the PHY parameter settings for all existing traffic streams and the expected PHY parameter settings for the new traffic stream under admission. Therefore, when considering application specific information in selecting PHY parameter settings, the admission control mechanisms need to be enhanced by assessing the channel condition with PHY parameter settings impacted from the consideration of application specific information.

[0103] In order to enable Wi-Fi to support ASIN as mentioned above, the application specific information needs to be communicated to the Wi-Fi air interface. There could be multiple approaches.

[0104] Basic approach: use the current IEEE 802.11/Wi-Fi MAC SAP, i.e., a user priority (UP) value is passed to MAC for each MAC SDU, then the UP is mapped to 802.11 access category (AC). In turn, the AC will be used as the application specific information in the proposed Wi-Fi ASIN mechanisms. This offers a coarse classification of applications.

[0105] Enhanced approach(s): provide more granular application specific information from an upper layer to MAC/PHY, so that MAC/PHY ASIN mechanisms can be more effective and efficient. Additional details are provided below. [0106] Similarly, in order to enable Wi-Fi to support ASIN, the data packets of a specific application or applications need to be properly queued and processed, so that they can be differentiated from other applications. The disclosed embodiments may include one of multiple approaches for queuing the data packets. One approach is to use the current IEEE 802.11/Wi-Fi queuing mechanisms and packet processing schemes with multiple priority queues for different UPs/ACs. Again, this offers a coarse classification of applications. Another approach is to enhance the packet queuing and processing mechanisms, so that MAC/PHY ASIN mechanisms can be more effective and efficient.

[0107] FIG. 7 is a schematic diagram illustrating PHY transmission parameter selection in accordance with some embodiments of the present disclosure. In the depicted embodiment, a PHY transmission parameter selection module 700 considers application specific information 702, in addition to existing input parameters 704, when selecting PHY transmission parameters 706. A module as referred herein may be software, hardware, or a combination of software and hardware specially configured to perform the disclosed process.

[0108] Application-specific information 702 may include, but is not limited to: (i) application specific QoS/QoE requirements: response time, end-to-end latency, jitter, bit error rate, packet loss ratio, etc.; (ii) application specific traffic characteristics: max packet size, average packet size, mean arrival interval, peak data rate, mean data rate, max burst size, mean burst size, max service duration, mean service duration, packet arrival distribution, etc. (iii) application-special characteristics that may be used to select proper PHY control and transmission parameters setting via MAC layer.

[0109] Existing input parameters 704 may include, but are not limited to channel condition, such as minimum (Min) SNR, RSSI, average number of retransmissions, etc.

[0110] Wi-Fi PHY transmission parameters 706 may include, but are not limited to, MCS, GI (guard interval), channel bandwidth, number of spatial streams, Tx power, spatial reuse parameters, etc. The Wi-Fi PHY transmission parameters 706 can be used to directly determine the data rate, bit error rate, and the probability of Tx success.

[0111] Methods for how to use application specific information in selecting PHY parameters vary with different PHY systems and different applications. Some examples are provided below. [0112] For time-sensitive traffic (e.g., requiring very low latency), one method is to select more robust MCS, guard interval, and/or channel bandwidth, to maximize the packet transmission success, hence minimize the retransmission, so that the latency is reduced. A more detailed explanation is given later. Another method is to select a most robust channel, if a device supports multiple bands, e.g., 2.4 gigahertz (GHz) band, 5 GHz band, and/or 6 GHz band. A third method could be to use a higher transmission power, as long as it is still within the regulatory limit.

[0113] For packet loss-sensitive traffic, e.g., requiring very low packet loss ratio, all the three methods for time-sensitive traffic are still applicable. Plus, if time allows, additional retransmissions can be considered in case of transmission failure. For high data rate traffic, more aggressive MCS, wider channel size, more spatial streams, etc. can be considered.

[0114] FIG. 8 is a table that shows an example of MCS selection based on SNR and RSSI for 802.1 In (Wi-Fi 4) and 802.1 lac (Wi-Fi 6). Typically, a Wi-Fi capable device, i.e., a device with Wi-Fi air interface, uses a table like the table in FIG. 8 to select MCS based on the channel condition, i.e., SNR and RSSI. For example, assume the device operates at 80-megahertz (MHz) channel, 2 spatial streams, the current channel condition SNR 20 decibels (dB), RSSI -65 decibel milliwatts (dBm). Currently, a typical implementation will select the MCS of 16 quadrature amplitude modulation (QAM) and ½ coding, as shown in the encircled portion in the table.

[0115] When considering the application specific information, for time-sensitive traffic, e.g., requiring very low latency, a more robust MCS may be selected to avoid the retransmission, e.g., the MCS of quadrature phase-shift keying (QPSK) modulation, ¾ coding, plus a larger GI could be considered (e.g., use 800 nanoseconds (ns) GI, instead of 400 ns GI). For high data rate traffic, a more aggressive MCS may be selected opportunistically, e.g., the MCS of 16-QAM modulation, ¾ coding, with 400 ns GI, which gives about 390 Mbps PHY data rate.

[0116] In addition to MCS and GI, other PHY parameters, e.g., channel size, number of spatial streams, can also be adjusted in order to provide the needed robustness and/or data rate for a specific application.

[0117] FIG. 9 is a schematic diagram illustrating a link adaptation process in accordance with some embodiments of the present disclosure. As stated above, link adaptation in current IEEE 802.11/Wi-Fi generally refers to the processes/procedures that are used to dynamically adjust the PHY transmission parameters coordinated by MAC scheduler, mainly modulation / coding schemes, based on varying channel conditions and traffic carried on the link to achieve a best possible link performance. In the depicted embodiment, a link adaptation module 900 considers application specific information 902 in addition to existing input parameters 904 when performing link adaptation to select and adjust the PHY parameters 906 so that the best possible performance for the specific application can be achieved. The existing input parameters 904 may include, but are not limited to, channel condition, such as Min SNR, RSSI, average number of retransmissions, previous transmission information, etc.

[0118] The application specific information 902 may include, but is not limited to: (i) application specific QoS/QoE requirements: response time, end-to-end latency, jitter, bit error rate, packet loss ratio, etc.; (ii) application specific traffic characteristics: max packet size, average packet size, mean arrival interval, peak data rate, mean data rate, max burst size, mean burst size, max service duration, mean service duration, packet arrival distribution, etc. (iii) application- special characteristics that may be used to select proper PHY control and transmission parameters setting via MAC layer.

[0119] The adjusted PHY parameters 906 may include, but are not limited to, MCS, GI, channel bandwidth, number of spatial streams, Tx power, spatial reuse parameters, etc.

[0120] In some embodiments, the link adaptation module 900 is configured to consider (i) application specific information when a link adaptation scheme selects the initial PHY parameter settings to transmit the packet of the application traffic stream; and (ii) application specific information when a link adaptation scheme adjusts the PHY parameter settings based on channel condition and packet transmission performance. In some embodiments, the process by which the link adaptation module 900 considers the application specific information in selecting or adjusting PHY parameters can vary based on the PHY details and application characteristics.

[0121] Currently, link adaptation is applied per link (i.e., PHY parameters are adjusted on a per link basis). However, a Wi-Fi link typically carries multiple traffic flows/streams. Thus, in some embodiments, the disclosed link adaptation mechanism is applied to per traffic flow/stream level (i.e., per-flow adaptation), in addition to current per link/STA level (i.e., per-link adaptation). This includes, but is not limited to, the link adaptation scheme identifies, tracks, adjusts, and maintains for the proper PHY parameter settings for the traffic streams corresponding to the specific application(s), in addition to per link/per STA PHY parameter settings. The per traffic stream link adaptation can be used for a set of selected traffic streams as needed. The default could be set as per-link adaptation, i.e., if a traffic stream is not chosen to use per-flow adaptation, then it uses per-link adaptation. In some embodiments, in dynamic aggregation mode, link adaptation considers specific application information for multiple links in adjusting QoS/QoE traffic. For example, the per traffic stream PHY parameter settings can be selected and adjusted by the link adaptation scheme (either open-loop or closed-loop) with the consideration of the application specific information of the traffic stream, in addition to channel condition.

[0122] FIG. 10 is a schematic diagram illustrating an admission control process in accordance with some embodiments of the present disclosure. In the depicted embodiment, an admission control module 1000 is configured to consider application specific information 1002 along with existing input parameters 1004 in determining whether a new traffic stream (TS) addition request can be accommodated that meets the new request QoS/QoE requirements 1006. The existing input parameters 1004 may include, but are not limited to, channel condition, such as Min SNR, RSSI, existing traffic load, the QoS/QoE requirements and traffic descriptors of the newly request traffic stream, etc. The application specific information 1002 may include, but is not limited to, additional information regarding the QoS/QoE requirements, and traffic characteristics for the newly requested traffic stream, e.g., upper layer traffic contract information.

[0123] In some embodiments, the admission control module 1000 is configured to assess the channel condition with PHY parameter settings impacted from the consideration of application specific information to determine whether the new traffic stream addition request can be accommodated based on its QoS/QoE requirements. For example, when assessing the available channel capacity, the PHY parameter settings for all existing traffic streams are considered to evaluate the used channel capacity, i.e., all the per traffic stream PHY parameter settings, not just per link/STA settings. In addition, the expected PHY parameter settings for the new traffic stream under admission are considered to evaluate the required channel capacity for the new traffic stream.

[0124] FIG. 11 is a schematic diagram illustrating an enhanced traffic classification process in accordance with some embodiments of the present disclosure. To implement the one or more embodiments of the present disclosure, the application specific information is communicated to the Wi-Fi air interface to enable Wi-Fi to support ASIN. The disclosed embodiments can use either a basic approach or an enhanced approach to communicate the application specific information to the Wi-Fi air interface. The basic approach is using the current IEEE 802.11/Wi- Fi MAC service access point (SAP) as previously discussed. The enhanced approach is to provide more granular application specific information from upper layer to MAC/PHY, so that MAC/PHY ASIN mechanisms can be more effective and efficient. [0125] Both in-band classification and an out-of-band classification can be used to provide the more granular application specific information from an upper layer to MAC/PHY layers. The in- band classification introduces a new MAC function module (e.g., enhanced traffic classification module 1100 in FIG. 11) to inspect the MAC service data units (MSDUs) and user priority (UP) received from the upper layer 1102 to classify the MAC SDUs into application specific traffic streams, and/or enable new MAC SDU formats. An SDU is a unit of data that has been passed down from a layer or sublayer in the ISO/OSI 7-layer reference model to a lower layer. The above approach depends on the inspectable / decodable information fields in the MAC SDU, e.g., if the MAC SDU encapsulates Ethernet / IP / Transmission Control Protocol (TCP) packet, then all the inspectable header fields in the Ethernet header, IP header, TCP header can be used to classify the MAC SDU. In contrast, the out-of-band classification introduces a function module outside of a MAC data plane, either above the MAC or in the MAC management entity, to classify the MAC SDU into application specific traffic streams and to provide such classification information to a MAC layer. This is similar to the <MAC SDU, UP> tuple in the current IEEE 802.11 MAC SAP, where UP is an out-of-band signal communicated along with the MAC SDU to the MAC layer from an upper layer. The disclosed embodiments introduce an enhanced interface 1104 to the current MAC SAP to provide additional signals to support ASIN. The additional signals may include, but are not limited to, a pre-defmed access category identifier, QoS/QoE indicator, traffic type descriptor identifier, etc.

[0126] In the depicted embodiment in FIG. 11, the enhanced traffic classification module 1100 classifies the data based on the information from the existing interface 1102 and the enhanced interface 1104. The enhanced traffic classification module 1100 uses the current IEEE 802.11/Wi- Fi queuing mechanisms and packet processing schemes with multiple priority queues for different UPs/ACs (e.g., voice (VO), video (VI), best effort (BE), background (BK)) for further processing. This provides a coarse classification of applications.

[0127] Alternatively, the disclosed embodiments may include a packet queueing system with multiple queues, each corresponding to different access categories (ag AC-1, AC-2, ... AC-n) as depicted in FIG. 12. In an embodiment, upon receiving a MAC SDU from an upper layer, the enhanced traffic classification module 1100 is configured to place the MAC SDU in the queue corresponding to its access category, where the MAC SDU’s access category information can be provided either by the in-band classification or by the out-of-band classification as described above. The packets are transmitted in the order based on the priorities of the access category. When transmitting a packet, the access category of the packet is considered when selecting the PHY transmitting parameter settings.

[0128] FIG. 13 is a schematic diagram illustrating cross layer signaling in accordance with some embodiments of the present disclosure. In the depicted embodiment, the ASIN information in the New IP contract can be signaled across layers LI and L2. ASIN information can also be signaled in the Wi-Fi, access network, and the OTN. ASIN information may comprise detailed information on bandwidth, latency, time jitter, and package loss rate or bit error rate (BER), etc. In some embodiments, when the detailed new IP contract comprises ASIN information, in band signaling can be used to dynamically provides the service in L3 nodes.

[0129] FIG. 14 is a schematic diagram illustrating a data packet for providing an ASIN in accordance with some embodiments of the present disclosure. In some embodiments, a management device and network control system on each end host application (e.g., E2E network slicing controller 600 in FIG. 6) generates an ASIN identifier (ASIN-ID) 1402. In some embodiments, the ASIN-ID 1402 and ASIN QoE parameters 1404 are encoded in the L3 New IP contract/metadata. There could be additional parameters in the New IP contract such as, but not limited to, flow level, aggregate latency parameter, or drop thresholds specific to ASID-ID. Along the packet traversal path, the ASIN-ID 1402 and ASIN QoE parameters 1404 can be cross signaled (in both directions) to various network segments (e.g., access and L1/L2/L2.5/L3 segments). The respective controllers in various network forwarding elements along the packet traversal path provision resources for the ASIN-ID.

[0130] As previously described, the bandwidth (BW) requirement for a given service in the ASIN can be met via an E2E hard slice that guarantees the BW requirement, without contention- induced bandwidth reduction etc. The latency and time jitter requirements for a given service in the ASIN can be met via an E2E hard slice with prioritized latency supports. The packet loss rate or bit error rate (BER) requirement for a given service in the ASIN can be met via an E2E hard slice that has sufficient encoding and decoding capabilities. The access network segment may comprise a passive optical network (PON) that provides network slicing capability, as well as a slice interface with the transport network segment to achieve E2E network slicing. The transport network segment may comprise an IP network and an OTN, wherein the OTN provides low- latency hard slice capabilities via the use of optical service units (OSUs), while the IP network provides low-cost soft-slice capabilities. The E2E Network Slicing Controller may choose the appropriate transport network for transporting a given service to meet the QoE with the lowest cost. The E2E Network Slicing Controller conducts the QoE analysis to continuously improve the QoE of the services carried by the E2E network.

[0131] FIG. 15 is a flowchart diagram illustrating a method 1500 for providing QoE for an application in accordance with some embodiments of the present disclosure. The method 1500 may be performed by various devices including, but not limited, a host device, a user device, a server, a router, a network management device, and a network slicing controller. The device, at step 1502, obtains ASIN information of the application for providing the QoE. At step 1504, the device configures a network segment of an E2E ASIN based on the ASIN information to provide the QoE. The device, at step 1506, communicates data for the application using the network segment.

[0132] FIG. 16 is a schematic diagram of an apparatus 1600 configured to implement one or more of the methods disclosed herein according to an embodiment of the disclosure. For example, the apparatus 1600 may represent the sending device 100, the receiving device 102, a client- system, and/or a server as described herein. The apparatus 1600 comprises ingress ports 1610 and receiver units (Rx) 1620 for receiving messages, a processor, logic unit, or central processing unit (CPU) 1630 to process the messages, transmitter units (TX) 1620 and egress ports 1640 for transmitting the messages, and a memory 1650.

[0133] The processor 1630 is implemented by any suitable combination of hardware, middleware, and firmware. The processor 1630 may be implemented as one or more CPU chips, cores (e.g., as a multi-core processor), field-programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), or digital signal processors (DSPs). The processor 1630 is in communication with the ingress ports 1610, receiver units 1620, transmitter units 1620, egress ports 1640, and memory 1650.

[0134] The memory 1650 comprises one or more disks, tape drives, or solid-state drives and may be used as an over-flow data storage device, to store programs when such programs are selected for execution, or to store instructions and data that are read during program execution. The memory 1650 may be volatile and/or non-volatile and may be read-only memory (ROM), random-access memory (RAM), ternary content-addressable memory (TCAM), or static random- access memory (SRAM). In one embodiment, the memory 1650 comprises an E2E ASIN module 1660. The E2E ASIN module 1660 comprises executable instructions and data configurations that when executed by the processor 1630 implements the disclosed embodiments as described herein. [0135] The present disclosure may be a system, a method, and/or a computer program product at any possible technical detail level of integration. The computer program product may include a computer readable storage medium (or media) having computer readable program instructions thereon for causing a processor to carry out aspects of the present disclosure.

[0136] The computer readable storage medium can be a tangible device that can retain and store instructions for use by an instruction execution device. The computer readable storage medium may be, for example, but is not limited to, an electronic storage device, a magnetic storage device, an optical storage device, an electromagnetic storage device, a semiconductor storage device, or any suitable combination of the foregoing. A non-exhaustive list of more specific examples of the computer readable storage medium includes the following: a portable computer diskette, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or Flash memory), a static random access memory (SRAM), a portable compact disc read-only memory (CD-ROM), a digital versatile disk (DVD), a memory stick, a floppy disk, a mechanically encoded device such as punch-cards or raised structures in a groove having instructions recorded thereon, and any suitable combination of the foregoing. A computer readable storage medium, as used herein, is not to be construed as being transitory signals per se, such as radio waves or other freely propagating electromagnetic waves, electromagnetic waves propagating through a waveguide or other transmission media (e.g., light pulses passing through a fiber-optic cable), or electrical signals transmitted through a wire.

[0137] Computer readable program instructions described herein can be downloaded to respective computing/processing devices from a computer readable storage medium or to an external computer or external storage device via a network, for example, the Internet, a local area network, a wide area network and/or a wireless network. The network may comprise copper transmission cables, optical transmission fibers, wireless transmission, routers, firewalls, switches, gateway computers and/or edge servers. A network adapter card or network interface in each computing/processing device receives computer readable program instructions from the network and forwards the computer readable program instructions for storage in a computer readable storage medium within the respective computing/processing device. [0138] Computer readable program instructions for carrying out operations of the present disclosure may be assembler instructions, instruction-set-architecture (ISA) instructions, machine instructions, machine dependent instructions, microcode, firmware instructions, state-setting data, configuration data for integrated circuitry, or either source code or object code written in any combination of one or more programming languages, including an object oriented programming language such as Smalltalk, C++, or the like, and procedural programming languages, such as the "C" programming language or similar programming languages. The computer readable program instructions may execute entirely on the user's computer, partly on the user's computer, as a stand alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the latter scenario, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or the connection may be made to an external computer (for example, through the Internet using an Internet Service Provider). In some embodiments, electronic circuitry including, for example, programmable logic circuitry, field-programmable gate arrays (FPGA), or programmable logic arrays (PLA) may execute the computer readable program instructions by utilizing state information of the computer readable program instructions to personalize the electronic circuitry, in order to perform aspects of the present disclosure.

[0139] Aspects of the present disclosure are described herein with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the disclosure. It will be understood that each block of the flowchart illustrations and/or block diagrams, and combinations of blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer readable program instructions.

[0140] These computer readable program instructions may be provided to a processor of a general-purpose computer, special purpose computer, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions/acts specified in the flowchart and/or block diagram block or blocks. These computer readable program instructions may also be stored in a computer readable storage medium that can direct a computer, a programmable data processing apparatus, and/or other devices to function in a particular manner, such that the computer readable storage medium having instructions stored therein comprises an article of manufacture including instructions which implement aspects of the function/act specified in the flowchart and/or block diagram block or blocks.

[0141] The computer readable program instructions may also be loaded onto a computer, other programmable data processing apparatus, or other device to cause a series of operational steps to be performed on the computer, other programmable apparatus or other device to produce a computer implemented process, such that the instructions which execute on the computer, other programmable apparatus, or other device implement the functions/acts specified in the flowchart and/or block diagram block or blocks.

[0142] The flowchart and block diagrams in the Figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of the present disclosure. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of instructions, which comprises one or more executable instructions for implementing the specified logical function(s). In some alternative implementations, the functions noted in the blocks may occur out of the order noted in the Figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems that perform the specified functions or acts or carry out combinations of special purpose hardware and computer instructions.

[0143] While several embodiments have been provided in the present disclosure, it may be understood that the disclosed systems and methods might be embodied in many other specific forms without departing from the spirit or scope of the present disclosure. The present examples are to be considered as illustrative and not restrictive, and the disclosure is not to be limited to the details given herein. For example, the various elements or components may be combined or integrated in another system or certain features may be omitted, or not implemented.

[0144] In addition, techniques, systems, subsystems, and methods described and illustrated in the various embodiments as discrete or separate may be combined or integrated with other systems, modules, techniques, or methods without departing from the scope of the present disclosure. Other items shown or discussed as coupled or directly coupled or communicating with each other may be indirectly coupled or communicating through some interface, device, or intermediate component whether electrically, mechanically, or otherwise. Other examples of changes, substitutions, and alterations are ascertainable by one skilled in the art and may be made without departing from the spirit and scope disclosed herein.

Claims

1. A method for providing quality of experience (QoE) for an application, the method comprising: obtaining application specific integrated network (ASIN) information of the application for providing the QoE; configuring a network segment of an end-to end (E2E) ASIN based on the ASIN information to provide the QoE; and communicating data for the application using the network segment.

2. The method according to claim 1, wherein the network segment is a Wi-Fi network.

3. The method according to claim 1, wherein the network segment is an Internet Protocol (IP) network.

4. The method according to claim 3, further comprising performing soft slicing of the IP network in configuring the network segment based on the ASIN information to provide the QoE.

5. The method according to claim 3, wherein the IP network is an enhanced IP network.

6. The method according to claim 5, wherein the enhanced IP network is a New IP network.

7. The method according to claim 1, wherein the network segment is an optical transport network (OTN).

8. The method according to claim 7, further comprising performing hard network slicing of the OTN based on the ASIN information to provide the QoE.

9. The method according to claim 7, wherein the OTN is selected by an E2E network slicing controller for hard network slicing.

9. The method according to claim 1, wherein the network segment is a cloud data center network.

10. The method according to claim 1, wherein the network segment is an access network.

11. The method according to claim 10, wherein the access network is a passive optical network (PON).

12. The method according to any of claims 1-11, further comprising obtaining the ASIN information from an E2E network slicing controller.

13. The method according to any of claims 1-12, wherein the ASIN information comprises New IP contract and metadata information.

15. The method according to any of claims 1-14, wherein the QoE is based on a set of performance indicators.

16. The method according to claim 15, wherein the set of performance indicators comprises bandwidth, latency, time jitter, and packet loss rate.

17. The method according to any of claims 1-16, further comprising specifying a cross-layer interface to an adjacent network segment, wherein the cross-layer interface supports network slicing capabilities needed for meeting various levels of QoEs.

18. The method according to any of claims 1-17, further comprising instructing the Wi-Fi network to consider the ASIN information when selecting physical layer (PHY) transmission parameters scheduled by a media access control (MAC) layer.

19. The method according to any of claims 1-18, wherein the Wi-Fi network considers the ASIN information when performing link adaptation.

20. The method according to any of claims 1-19, wherein the Wi-Fi network considers the ASIN information when performing admission control mechanism.

21. The method according to any of claims 1-20, wherein the Wi-Fi network communicates the ASIN information to a Wi-Fi air interface.

22. The method according to any of claims 1-21, wherein the Wi-Fi network is configured to queue and process packets based on the ASIN information.

23. An apparatus comprising: a memory configured to store instructions; a processor coupled to the memory, the processor configured to execute the instructions to cause the apparatus to perform the method of any of claims 1-22.

24. A computer program product comprising computer-executable instructions that are stored on a non-transitory computer-readable medium and that, when executed by a processor, cause a computing device to perform the method of any of claims 1-22.

25. An application specific integrated network (ASIN) comprising an end-to end (E2E) Network Slicing Controller and a plurality of network segments configured to provide a quality of experience (QoE) requested by a given application.

26. The ASIN of claim 25, wherein the plurality of network segments comprises a Wi-Fi network.

27. The ASIN according to any of claims 25-26, wherein the plurality of network segments comprises an access network.

28. The ASIN according to any of claims 25-27, wherein the plurality of network segments comprises an Internet Protocol (IP) network.

29. The ASIN according to any of claims 25-28, wherein the plurality of network segments comprises an optical transport network (OTN).

30. The ASIN according to any of claims 25-29, wherein the plurality of network segments comprises a cloud data center network.

31. The ASIN according to any of claims 25-30, further comprising a host device executing the given application.

32. The ASIN according to any of claims 25-31, further comprising a server configured to provide data to the given application.

33. The ASIN according to any of claims 25-32, wherein the QoE is based on a set of performance indicators.

34. The ASIN according to any of claims 25-33, wherein the set of performance indicators comprises bandwidth, latency, time jitter, and packet loss rate.

35. The ASIN according to any of claims 25-34, further comprising a cross-layer interface to an adjacent network segment, wherein the cross-layer interface supports network slicing capabilities needed for meeting various levels of QoEs.

36. The ASIN according to any of claims 25-35, wherein two or more network segments in the plurality of network segments each comprise at least one device configured to use a same ASIN information of the given application to configure the respective network segment.