Adaptive resource management for multi-screen video applications over cable wi-fi networks.
Abstract
The combination of client-based and network-based adaptive streaming approaches enables a distributed and adaptive resource management system to perform carrier-grade video transmission over Cable Wi-Fi systems. Adaptive resource management over heterogeneous Cable Wi-Fi networks includes a network-based approach using client-based feedback. Management of the resources of a video stream is carried out in a service provider's network, for example in a cable modem termination system, by evaluating a margin and a fairness index. In modalities, the speed of a video stream is adjusted to a requesting client, and in modalities, the speed of a video sequence is adjusted for non-requesting clients. Modalities include adaptive streaming and call admission control based on adjustable resource margins and fairness ratios for DOCSIS and HetNet Wi-Fi systems.

Term
7.5 yearsleft in the term
Expires 13 March 2034.
- Priority
- Filed
- Granted
- Today
- Expires
14 claims: 2 independent, 12 dependent
- 1NOVEDAD DE LA INVENCIÓN ΙΝΤΠΤυΤ· MUUCANO MLAFMOFMBiA* fNBUlTUAL Habiendo descrito la presente invención como antecede, se considera como una novedad y, por lo tanto, se reclama como propiedad lo contenido en las siguientes:REIVINDICACIONES 1. Un método basado en red para la gestión adaptable de recursos de streaming en una red de Cable Wi-Fi HetNet, caracterizado porque comprende: determinar un índice de equidad de aplicación que define un uso medio para cada flujo en un grupo de flujo, en donde el índice de equidad de aplicación para cada flujo es una función del uso medio de otros flujos en el grupo de flujo en una misma sesión;determinar un margen de recursos para un área de servicio asociada con la sesión, en donde un área de servicio incluye una pluralidad de clientes, y en donde el margen de recursos es una medida determinada para el área de servicio basada en el ancho de banda tanto en una ubicación de red y al menos un componente Wi-Fi en una trayectoria de sesión correspondiente a la sesión;recibir una solicitud de streaming de velocidad de bits adaptable de un cliente en el área de servicio, en donde la IMPI ΙΝΪΤΓΠ Π» MUUCANU DELAHWfWAB INDUSTRIAL solicitud es indicativa de un cliente que solicita calidad del enlace;determinar si aceptar la solicitud de streaming de velocidad de bits adaptable con base en el índice de equidad de aplicación si el margen es inferior a un umbral de margen, en donde en respuesta a una aceptación de la solicitud de streaming de velocidad de bits adaptable en algunos casos, el ajuste de una velocidad para al menos un flujo en el grupo de flujo, y, con base en la velocidad ajustada, actualizar el índice de equidad de aplicación para cada flujo en el grupo de flujo y actualizar el margen para el área de servicio;y en donde el índice de equidad de aplicación está ajustado con base en el umbral de margen en otros casos, pero el ajuste a la velocidad de bits no es realizado con base de la aceptación de la solicitud de streaming de velocidad de bits adaptable;y en respuesta a un rechazo de la solicitud de streaming de velocidad de bits adaptable, mantener el índice de equidad de aplicaciones y márgenes para el grupo de flujo.
- 2El método de conformidad con la reivindicación 1, caracterizado porque la solicitud de streaming de velocidad de bits adaptable desde el cliente es una solicitud para reducir o disminuir la velocidad de bits de una transmisión de flujo al cliente, y en donde adicionalmente el margen de IMPI IMTTTUT· MUUCAN· DC LA PWOnftQA* INDUSTRIAL recursos tiene un incremento o decremento de ancho de banda para la totalidad de área de servicio para mantener el ancho de banda constantemente disponible, aún cuando la velocidad de bits de flujo individual está reducida en aquella área de servicio.
- 3El método de conformidad con la reivindicación 1, caracterizado porque dicho al menos un flujo en el grupo de flujo para el que se ajusta la velocidad es de al menos uno de:el flujo al cliente solicitante;uno de los otros flujos en el grupo de flujo;un flujo seleccionado con base en un respectivo índice de equidad de aplicación;o un flujo seleccionado en los requisitos de velocidad de un operador de servicios múltiples.
- 4El método de conformidad con la reivindicación 1, caracterizado el ajuste a la velocidad para dicho al menos un flujo en el grupo de flujo es una reducción en la velocidad de dicho al menos un flujo.
- 5El método de conformidad con la reivindicación 1, caracterizado porque el cliente en el área de servicio asociada con la sesión es al menos uno de:un cliente con un flujo activo que solicita una modificación al flujo, o IMPI^ 59 ίΝτπτυτο muucan· KLAIMHUA» INBUS-HUAL -SJ un nuevo cliente en el área de servicios que solicita un nuevo flujo a ser entregado.
- 6El método de conformidad con la reivindicación 1, caracterizado porque además comprende comparar el margen determinado con un umbral de margen.
- 7El método de conformidad con la reivindicación 1, caracterizado porque el índice de equidad de aplicación diferencia la calidad del enlace a lugares específicos del cliente y es indicativo de problemas de dispositivos de clientes específicos.
- 8El método de conformidad con la reivindicación 1, caracterizado porque además comprende comparar el margen actualizado con el umbral de margen y, en respuesta a la determinación de que el margen actualizado es menor que el umbral, reducir las velocidades de los flujos seleccionados y actualizar el índice de equidad basado en las velocidades reducidas.
- 9El método de conformidad con la reivindicación 1, caracterizado porque cada flujo para el que se determina un índice de equidad de aplicación corresponde a un cliente, el índice de equidad de aplicación en función de una solicitud de velocidad de bits adaptable de cliente que se origina con el cliente. 60 60 iwrnui»mukano Jl ot LA FWnilWi Y^IMTXTrWAL * ί!^
- 10El método de conformidad con la reivindicación 1, caracterizado porque el grupo de flujo en la misma sesión para el cual el índice de equidad de aplicación es una función, es un grupo de flujos agrupados basado en el uso de una misma trayectoria de red.
- 11El método de conformidad con la reivindicación 1, caracterizado porque un grupo está definido por el flujo de todos los flujos que comparten un punto de acceso, y el ajuste de una velocidad para al menos un flujo en el grupo de flujo comprende ajustar una velocidad para todos los flujos que comparten el mismo punto de acceso.
- 12El método de conformidad con la reivindicación 1, caracterizado porque el margen de recursos está determinado con base en un límite de retardo, en donde la solicitud de streaming de velocidad de bits del cliente es aceptada si las probabilidades para cada flujo de exceder un límite de retardo está dentro de un rango aceptable.
- 13Un sistema de terminación de módem de cable (CMTS) en una red de un proveedor de servicios para la gestión de recursos adaptables de streaming en una red de Cable Wi-Fi HetNet, el CMTS está caracterizado porque comprende:un dispositivo de almacenamiento un procesador configurado para: IMPI »κτπντο muucah· MUHIORItMP INDUmiAL determinar un índice de equidad de aplicación que define un uso medio para cada flujo en un grupo de flujo, en donde el índice de equidad de aplicación para cada flujo es una función del uso medio de otros flujos en el grupo de flujo en una misma sesión;determinar un margen de recursos para un área de servicio asociada con la sesión, en donde un área de servicio incluye una pluralidad de clientes, y en donde el margen de recursos es una medida determinada para el área de servicio basado en el ancho de banda tanto en una ubicación de red y al menos un componente Wi-Fi en una trayectoria de sesión correspondiente a la sesión;al menos un receptor para recibir una solicitud de streaming de velocidad de bits adaptable de un cliente en el área de servicio, en donde la solicitud es indicativa de la calidad del enlace de un cliente solicitante;el procesador está configurado además para determinar si acepta la solicitud de streaming de velocidad de bits adaptable basado en el índice de equidad de aplicación si el margen es inferior a un umbral de margen, en donde en respuesta a una aceptación de la solicitud de streaming de velocidad de bits adaptable en algunos casos, ajustar una velocidad para al menos un flujo en el grupo de flujo, y, con base en la velocidad ajustada, actualizar el indice de equidad de aplicación IMPI ΜΤΠυΤΟ MNUeAN· mlahiorum· para cada flujo de flujo y actualizar el margen para el área de servicio, en donde el índice de equidad de aplicaciones está ajustado con base en el umbral de margen en otros casos, pero el ajuste a la velocidad de bits no realizada con base en la aceptación de la solicitud de streaming de velocidad de bits adaptable, y en donde en respuesta a un rechazo de la solicitud de streaming de velocidad de bits adaptable, mantener el índice de equidad de aplicaciones y márgenes para el grupo de flujo.
- 14El sistema de terminación de módem de cable de conformidad con la reivindicación 13, caracterizado porque la solicitud de streaming de velocidad de bits adaptable del clientes una solicitud para reducir o disminuir la velocidad de bits de una transmisión de flujo al cliente, y en donde adicionalmente el margen de recursos tiene un incremento o decremento de ancho de banda para la totalidad del área de servicio para mantener el ancho de banda constante disponible, aún cuando la velocidad de bits de flujo individual está reducida en aquella área de servicio. IMPI
Independent claims14
292 paragraphs in 41 sections, as filed
(54) Title: ADAPTABLE RESOURCE MANAGEMENT FOR MULTI-SCREEN VIDEO APPLICATIONS OVER WI-FI CABLE NETWORKS.
(54) Title: ADAPTIVE RESOURCE MANAGEMENT FOR MULTI-SCREEN VIDEO APPLICATIONS OVER CABLE WI-FI NETWORKS.
(57) Summary
The combination of client-based and network-based adaptive streaming approaches enables an adaptive, distributed resource management system to perform carrier-grade video transmission over Cable WI-FI systems. Cable WI-FI's adaptive resource management over heterogeneous networks includes a network-based approach using customer-based feedback. Management of the resources of a video stream is carried out in a service provider's network, for example in a cable modem termination system, by evaluating a margin and a fairness index. In modalities, the speed of a video stream is adjusted to a requesting client, and in modalities, the speed of a video sequence is adjusted for non-requesting clients. Modalities include adaptive streaming and call admission control based on adjustable resource margins and fairness ratios for DOCSIS and Wi-Fi, HetNet systems.
(57) Abstract
Combining network and Client based adaptive streaming approaches enable a distributed and adaptive resource management system for carrier quality video transmission over cable WI-FI systems. The adaptive resource management over cable WI-FI heterogeneous networks includes a network based approach using Client based feedback. The resource management of a video stream is performed on a Service providers network, for example in a cable modem termination system, by evaluating a margin and a fairness Index. In embodiments, the rafe of a video stream to a requesting Client is adjusted and, in embodiments, the rafe of a video stream for non-requesting clients is adjusted. Embodiments include mechanisms for cali admission control and adaptive streaming based on adjustable resource margins and fairness Indices for DOCSIS and WI-FI hetnet systems.
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Mexican Institute of Industrial Property
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PATENT TITLE NO. 347339
Headlines):
ARRIS TECHNOLOGY, INC.
Home:
3871 Lakefield Drive, Suwanee, Georgia, 30024, USA
Denomination:
ADAPTABLE RESOURCE MANAGEMENT FOR MULTI-SCREEN VIDEO APPLICATIONS OVER WI-FI CABLE NETWORKS.
Classification lnt.CI.8: H04L12 / 825; H04L29 / 06
Inventor (s):
SEBNEM ZORLU-OZER; ROBERT L. HOWALD
REQUEST
Numeral
International filing date!
MX / a / 2015/012150 of March 2014
PRIORITY
Country;
Date:
Number!
US
US March 2013 March 2014
61/800,311
14/210,338
Validity: Twenty years
Expiration Date: March 13, 2034
The reference patent is granted based on articles 1, 2, section V, 6, section III, and 59 of the Industrial Property Law.
In accordance with article 23 of the Industrial Property Law, this patent is valid for twenty years, non-extendable, counted from the filing date of the international application and will be subject to the payment of the fee to keep the rights in force. . ,
Whoever signs this title -does it based on the provisions of articles 6 * sections III and 7 bis 2 of the Industrial Property Law (Official Gazette of the Federation (DOF) 06/27/1991, amended on 02 / 08/1994, 10/25/1996, 12/26/1997, 05/17/1999, 01/26/2004, 06/16/2005, 01/25/2006, 05/06/2009, 06/01 / 2010, 06/18/2010, 0/28 / 2010, 01/27/2012 and 04/09/2012); Articles 1, 3<sup>or</sup> fraction V subsection a), 4th and 12th sections l and III of the Regulations of the Mexican Institute of Industrial Property (DOF 12/14/1989, amended on 07/01/2002, 07/15/2004, 07/28/2004 and 9/7/2007); Articles 1, 3, 4, 5 section V subsection a), 16 sections I and III and 30 of the Organic Statute of the Mexican Institute of Industrial Property (DOF 12/27/1999, amended on 10/10/2002, 07/29/2004, 08/04/2004 and 09/13/2007); 1, 3 and 5 subsection a) of the Agreement that delegates powers to the Deputy General Directors, Coordinator, Divisional Directors, Heads of Regional Offices, Divisional Deputy Directors, Departmental Coordinators and other subordinates of the Mexican Institute of Industrial Property. (DOF 12/15/1999, amended on 02/04/2000, 07/29/2004, 08/04/2004 and 09/13/2007).
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TO
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Issue Date: April 21, 2017
THE DIVISIONAL DIRECTOR OF PATENTS
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NAHANNY CANAL REYES
550 Pisol.
M if a CP 16C2C-,
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MX / 2017/34348
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ADAPTIVE RESOURCE MANAGEMENT FOR VIDEO APPLICATIONS
MULTI-SCREEN OVER WI-FI CABLE NETWORKS
CROSS REFERENCE TO RELATED REQUESTS
The present application claims priority from the United States patent application to the United States provisional patent application with serial number. 61 / 800,311 filed March 15, 2013, entitled Adaptive Resource Management for Multi-Screen Video Applications over Wi-Fi Cable Networks which is incorporated herein by reference in its entirety.
BACKGROUND OF THE INVENTION
Existing solutions for streaming (referred to as streaming in the art and throughout this document) over Cable Data Services Interface Specification (DOCSIS) networks include adaptive variable bit rate (VBR) video streaming. network-based. However, network-based monitoring cannot always track performance-related changes effectively when the system is composed of highly variable links and distributed architecture, such as Cable Wi-Fi systems (which is a consortium of providers of this service). The controller
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INBUSTUAL network may not be able to detect an end-user experience effectively or in a timely manner, which can lead to inequality, instability, and low network utilization. Current indoor and outdoor deployments of Cable Wi-Fi offer mostly better data efforts as a free service to subscribers or at fixed plan speeds to non-subscribers, while carrier-grade video is targeted for the next generation. of residential, commercial and public / community Wi-Fi Cable networks.
BRIEF DESCRIPTION OF THE DRAWINGS
For the purpose of illustrating the embodiments described below, exemplary constructions of the embodiments are shown in the drawings; however, the modalities are not limited to the specific methods and instrumentations described. In the drawings: -
Figure 1 shows exemplary Cable Wi-Fi systems.
Figure 2 shows exemplary Wi-Fi Cable systems with integrated video management and control;
Figure 3 represents a flow chart for intake control that includes the possibility of reducing selected flow rates based on a marqen calculation.
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Figure 4 represents an exemplary flow diagram
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Figure 5 represents a flow chart for an end of session algorithm.
Figure 6 shows details of an exemplary architecture of a system configured to implement the techniques described.
Figure 7 shows details of another exemplary architecture of a system configured to implement the techniques described.
Figure 8 represents a graphical derivation of a delay limit for a modified Round Robin Deficit scheduling algorithm.
Figure 9 illustrates queue behavior, including a queue size corresponding to the maximum delay.
Figure 10A represents simulation results of time (x-axis) versus cumulative values (y-axis) for a DOCSIS 3.0 example.
Figure 10B represents another simulation result of time (x-axis) vs. cumulative values (y-axis) for a DOCSIS 3.0 Example.
Figure 11 shows a graph showing the service speed of a flow.
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Figure 12 represents a simulation model for admission control.
Figure 13 represents different actions related to transmission times for packets in queue to optimize rate adaptation.
Figure 14 is a block diagram of an example CMTS device that may include admission control functionality as disclosed.
It should be noted that, although the accompanying figures serve to illustrate modalities of concepts that include the claimed invention, and explain various principles and advantages of the embodiments, the claimed invention is not limited to the concepts shown, as additional modalities would be readily apparent to those of ordinary skill in the art having the benefit of the description herein so that explanation of certain concepts is not necessary to understand such modalities.
DETAILED DESCRIPTION OF THE INVENTION
This document describes techniques to increase network utilization and video quality over heterogeneous Cable Wi-Fi networks by proposing an adaptive resource management system with control based
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in network software that uses client-based feedback, where available. In addition, it addresses the transmission of video traffic through Cable networks
Wifi. Cable operators, using the techniques
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FROM THE FRDUtDAC INPVSTE1AI described, they will be able to apply hybrid network and client-based control to offer carrier-grade video services.
In embodiments, approaches are described that combine client-based adaptive streaming and network approaches to enable a distributed and adaptive resource management system for carrier-grade video transmission over Cable Wi-Fi systems. In addition, modalities include adaptive streaming and call admission control modalities based on adjustable resource margins and fairness ratios for DOCSIS and HetNet Wi-Fi systems.
Cable operators around the world are trying to expand their Wi-Fi services, as a result of the latest successes and the proliferation of new Wi-Fi devices and applications. Wi-Fi began to shift revenue generation from a traditional way of charging end users for voice and text to make money from access charges and sale of services to third parties, depending on local regulations, carrier market and the state
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IMPI rwrrrruTe Mexican KLAnons · * · INDUSTRIAL competition. To this end, points of origin and hotspots / hotzones were unified under operator control and management to offer uninterrupted services while end-user control is not lost in heterogeneous network segments. Roaming partnerships and wholesale models are also expanding to offer integrated services for end users. One of the applications that operators are exploring is carrier-grade video to multiple screens in the home and beyond through indoor and outdoor hotspots / hotzones, such as use cases, such as hospitality, special events, location-based applications, etc.
In existing Cable Wi-Fi systems, cable and Wi-Fi segments are independent in terms of network and resource management, providing end-to-end control for video. Figure 1 and Figure 2 represent exemplary Cable Wi-Fi systems.
Figures 1 and 2 show a service provider core network 101 communicating using various components to deliver content to a network element 114. A service and subscriber management server 102 and gatekeeper 103 can be used both for subscribers and non-subscribers to provide, IMPI®
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INDUSTRIAL - services, authorization, billing and access control. A wireless controller 106 provides and manages the access points and wireless links. Network elements 102, 103 and 106 can be implemented as software appliances or entities and can be combined into the same entity. The Cable Wi-Fi 115 network management system is used for fault management, configuration, provisioning and business intelligence.
In the CMTS path 107, the service provider can use a communications network for processing and transmission of content to the provider's subscribers, such as a hybrid fiber coaxial network (HFC), or a passive optical network (PON). . Although the system is described for the CMTS architecture, the functionality can be integrated into next-generation architectures such as converged edge routers as a home appliance or virtual entity. In the example of the HFC network shown in Figure 1, the CMTS 107 offers content to an optical broadband transmission platform 108. Through a fiber 109, the optical broadband transmission platform 108 offers content to a node 110. The node may allow operators to independently and progressively segment the downstream and upstream paths through coaxial lines lll. The
ΙΝΤΠΤυΤΟ MCXtCAN · Μ THE FRORltDAB INDUSTRIAL coaxial line can lead to a 112 terminal. Subscriber terminals are tapped at various places in the cable network to provide drop lines to subscribers and offer a return path for subscribers' messages . A terminal is typically inserted into the coaxial cable at locations along a length of cable, where the transmitted signal can be provided to one or more subscribers through subscriber lines. Often the terminal provides the final distribution of CATV / RF signals for 114 subscribers, typically over 111 coaxial cables. The service can be for a commercial / residential building or outdoor service areas.
The Cable Wi-Fi 115 network management system is used for fault management, configuration, provisioning and business intelligence. The Cable Wi-Fi system can have its own Cable Wi-Fi network management system separate from the HFC network, for example, and deliver content on a management plane to a Cable Wi-Fi access point. A Wi-Fi access point is a device that allows wireless devices to connect to a wired network using WiFi or related standards. Access points can serve as a central transmitter / receiver of wireless radio signals,
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ΓΜΠΤΠΙΤΟ MkXlCAN · re LA FKAHIBAr IH »urnUAl including Wi-Fi. The access points can support public Internet access points and extend the range of the Wi-Fi signal for private networks. The access point 113 can connect to a router over a wired network as a standalone device or integrated into the router itself.
As shown in Figure 2, a video headend 118 is integrated into the Cable Wi-Fi network management and control system. While current implementations are based on the architecture shown in Figure 1, where cable, Wi-Fi, and video management and control systems are separated, integrating management and video transport control with HetNet systems from Wi-Fi cable will allow higher video quality for Wi-Fi users. Video management and control can be regional / localized or can be integrated into the subscriber management system and the main network as a device or software entity.
Services such as carrier grade video require end-to-end control across heterogeneous networks that can be very different in nature in terms of resource dynamics. Therefore, end-to-end management of resources is challenging in terms of supporting high-quality user experience while maximizing network utilization. The
IMPIAS, <sub>n</sub> MSTnUT · MUICAN · r * LAn ** HDA »Co ^ U l * l» UrHUAL complexity is another issue since managing the ideal resources for Cable Wi-Fi systems would require real-time analysis and link monitoring Wi-Fi, which is not feasible.
This document describes techniques that combine both network and client-based approaches to enable a scalable, distributed resource management system for carrier-grade video transmission over Cable Wi-Fi systems. Adaptive streaming and call admission control modalities based on adjustable resource margins and fairness ratios are released for DOCSIS and HetNet Wi-Fi systems. Development frameworks developed for network-based adaptive streaming for VBR over DOCSIS traffic cannot always track performance-related changes effectively when the system consists of highly variable links and distributed architecture. The techniques described combine a network-based adaptive streaming algorithm with wired and wireless information and take customer device requests into account since the above network-based control techniques do not have the best overview. In Cable Wi-Fi systems, for example, there are more dynamics involved due to changes in width of
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As of today, unmanaged video over Cable Wi-Fi networks is controlled solely by client-based algorithms. Client-based adaptive bit rate video applications are widely used, including HTTP Live Streaming (Apple - HLS), Internet Information Services - Smooth Streaming (Microsoft - HSS), and HTTP Dynamic Streaming (Adobe - HDS) as streaming standards. the industry de-facto, and MPEG Dynamic Adaptive Streaming over HTTP (MPEG-DASH) as the standardized adaptive streaming specification. Although these protocols work best in specialized media, they can create inequity and misdiagnosis of the cause of a link problem (eg, congestion vs. channel errors or channel access problems due to greedy users / applications). On shared media, end user devices 114 cannot have the full network view, making problem differentiation much more difficult. On the other hand, client-based adaptive bit rate video applications are a good indicator when the end user is experiencing problems, which cannot always be detected over time by a network-based controller.
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For example, with a Cable Wi-Fi component, a single user may have link issues (eg fading. Cable Wi-Fi may be a hotspot scenario with many users on the same medium, where a user has connection problems because there is not enough space in the channel due to congestion This is the tension between the individual link and the congestion. The techniques described consider not only network-based control, but also the determination of the type and requests of users based on adaptive control algorithms. Instead of reducing the multiple speeds of a single flow, for example, the network can recognize congestion based on customer requests and make different adjustments, such as reducing the flow for many users at a lower speed, or the adjusting video quality for all streams sharing the same access point.
One issue is that DOCSIS-based wired networks and Wi-Fi-based wireless networks are very different in nature, both in the PHY and MAC domains. Existing technologies that use bandwidth estimation (such as the use of packet pairs) between client and server do not address the fairness issue addressed by the described modalities. This would create problems from the impact of a change in the flow of the other flows of the same category<sub>13</sub> ΙΜΡΪ ^
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AP) is not taken into account. Disclosed our techniques that can be governed by the interaction of stream transmissions.
In the middle of the unlicensed shared spectrum of a Wi-Fi domain, users can have drastically different link qualities based on their location and devices. Fairness algorithms have been developed to allow users to share airtime in an equitable manner. However, these algorithms are based on low-layer information, which is not adapted to the requirements of users' video applications (for example, the bit rate per screen of a specific video), backhaul conditions. ) (as a DOCSIS network segment), the user and device policy of specific applications (such as client-based adaptive rate streaming). These algorithms can create even more inequity for users as some users can go back further, while greedy users can use an aggressively preceded channel. The result is a wide range of end-user video quality for different devices and algorithms running on these devices.
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For example, a first user with a certain client-based adaptive speed algorithm can lower their video speed, while a second user with a different client-based adaptive speed algorithm or a legacy device cannot. Differentiating the cause of the problem is not straightforward, as any user may be on the edge of the access point's coverage area or may be subject to a hidden node or other interference case. In another scenario, however, a first user may be subject to the same link conditions as other devices connected to the same wireless access point, but the user's first adaptive rate algorithm may be more proactive. Reducing the video speed of the first user without further action can increase the access speeds and wireless video channels of other users, resulting in further degradation and inequity to the first user requesting the decrease.
In another example, a first user may request an increase in speed, but this can cause degradation and inequity for other users in the path of shared heterogeneous networks. Therefore, client-based speed adaptation algorithms can create inequity, instability, and low
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Network Utilization for Cable Wi-Fi Networks. On the other hand, as stated before, client-based rate adaptation algorithms are a good indicator of when an end user is experiencing problems. End-user problems may not always be detectable by the central system because it is feasible for a central system to have every bi-directional link state at any point in time for a Wi-Fi system.
The problems described above are compounded if the video is VBR. While constant bit rate (CBR) type video streaming increases network utilization, CBR is not flexible in providing quality for video dynamics. On the other hand, VBR-type video streams can support high quality video with high peak to average bit rates, but with less network utilization. If an adaptive rate algorithm can use the general information of the network, the adaptive rate algorithm can allow video transmission over DOCSIS VBR networks, ensuring a minimum of quality and maximizing network utilization. However, in heterogeneous networks such as Cable Wi-Fi networks, the challenge is to have an accurate view of the network in a timely manner and to differentiate between location and specific issues.
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INDUSTRIAL - r device. Although the 802.llk-type standards are intended to provide access points with more metering capabilities with station-assisted polling, getting device-specific, mobility, and link issues into a central resource manager is not always feasible.
This document describes the techniques that use a distributed and adaptive resource management system that was assisted with client-based adaptive speed algorithms for the transmission of operator quality video over Cable Wi-Fi systems.
Native VBR and layered VBR streams and their effect on the Internet Protocol (IP) last mile link have been evaluated. CBR services can be statically multiplexed with precise bandwidth allocation and therefore can easily direct traffic to any DOCSIS IP channel, whether joined or unjoined. VBR services, on the other hand, must be evaluated for their statistical properties so that services can be mathematically analyzed before bundling them into a specific IP channel, without additional MPEG processing. Due to the impact of network and traffic parameters on system performance for VBR multiplexing, a soft admission control algorithm with adaptation of
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I * LA noNIBAt INBUSTRUi network-based speed. The proposed system can be implemented over DOCSIS transport networks based on
IP as well as IP-based gateway systems.
Network-based control systems only for high dynamic networks, such as wireless networks, have been found to be unsuitable due to the fact that bi-directional links vary as a function of time, link location and direction, and precise measurements of these. Links are not feasible for all time. Furthermore, access points on a shared medium cannot measure interference outside their range, but only within the range of their service stations.
Recent advances in Wi-Fi systems (for example, high-performance systems (802.11η, 802.llac-ad), Alliance Wi-Fi connection admission control specification, 802.llk type metering and reporting protocols , 802.11a for Video over Wi-Fi, etc. allow better performance for video services It should be noted that these frames are complementary to the techniques described. For example, an admission control specification specifies an interoperable way to implement admission control, but does not specify the way in which accept / reject decisions were made or how allocated resources are changed.
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Conventional bandwidth methods that address thinning scale to adapt to user requests performing bandwidth estimation to evaluate network conditions through known methods, such as the Packet-Pair concept or protocol RTP control. In these techniques, the weight loss is done based on the estimate. However, conventional methods do not work well for heterogeneous networks such as wired Wi-Fi systems.
Techniques for an adaptive distributed resource management system that is aided by client-based adaptive rate algorithms for carrier-grade video transmission over Cable Wi-Fi systems are described. As will be described later, our techniques for combining network-based adaptive streaming with client-based adaptive streaming algorithms are disclosed. In modalities, one goal is to make sure the video is streamed at acceptable levels of performance (e.g. speed) which may depend on video complexity, device / display type, user profile, etc. Higher performance is targeted while acceptable levels and lower percentages of time<sub>19</sub> IMPI ^
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Figures 3-5 show exemplary algorithms for the disclosed adaptive resource management system. System components or a device can be configured to carry out the algorithms defined in Figures 3-5. In modalities, call admission control is integrated with adaptive resource management. If a new managed video stream service is requested, the call admission control algorithm will evaluate the resources and the new video requirements to decide whether the stream should be accepted or rejected. The decision is based on margins (resource margins) and an equity index of the application. The decision can be made after restoring the resources (for example, reducing the speeds of other existing flows).
The fairness index is based on the ratio of the quality received over a history window of a single stream to the quality received over a history window of all flows that share the same network resources. The received quality can be an index based on the actual metric and the required quality. This metric can be based on performance, delay, and delay variation (j itter) values.
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Margin is a function of network resources that can be expressed in terms of bandwidth, speed, or delay. An estimated network resource is assumed to be the conditions of the network for a given time interval. Margin thresholds are limits calculated based on traffic and network conditions and needs. For example, if the video requirements of all existing streams (or maximum number of streams) change between [Rl, R2] and the network resources fluctuate between [NI, N2] than the threshold can be calculated based on the difference of R2 and NI to take into account the worst case. An additional margin can be added for estimated fluctuations in the near future of the network. As explained below, customer-based feedback can update both margin and margin thresholds.
Figure 3 depicts a flow chart for admission control (CA) including the possibility of reducing the speeds of selected flows based on a margin calculation, with the beginning of the flow chart represented by 302. At 304, a Margin is calculated for the trajectory of the session. A margin is calculated based on the
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At 306, the calculated margin is compared to a margin threshold. Different margin thresholds can be set for AC and ABR requests. Due to fluctuations in network conditions, resources can change over time. Also, if linear VBR IP video is transmitted, the video requirements may change throughout different sections of the stream depending on the content. Therefore, margin thresholds mu st take into account these fluctuations. For example, if the system bandwidth is determined as BW_S and fluctuations are expected as 10%, then the margin threshold must be more than 10% of BW_S.
While a margin is a calculation for all network usage, an application fairness index is identified for a particular video stream that is also affected by other streams in the group. In modalities, the index of
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<sub>22</sub> IMPI iwrmrru muicam dílawohuu »industrial application fairness is normalized by the corresponding speed requirement based on a video quality requirement index (VQ). The application equity index can be based on the assumption that the VQ index includes an end-user policy and device / display requirements. The application equity index can be updated based on usage history. It is noted that airtime fairness is a term related to IEEE 802.11 mean time / supported time definitions in the Wi-Fi Alliance specification, while application fairness defines a ratio of mean usage and VQ requirement ratio . For example, application fairness may take into account the normalization of the VQ indices obtained against those requested by the flow groups.
In modalities, the application equity index is calculated based on the cooperative game theory approach. For example, in case of congestion within an AP zone, reducing the speed of multiple flows to the next speed level may be better than reducing the speed of the flows one or a bit to the lower speed level. This increases the video quality as there is no sharp change and also the stability. The application equity index corresponds to the same margin group.
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If in 306 the margin is less than a margin threshold,
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at 308 the session is accepted and margin and an application equity index are updated. If at 306 it is determined that the calculated margin is greater than the margin threshold, the algorithm identifies if there is any flow with reduced speed. If there is not, the session is rejected at 312. If there are one or more flows with reducible rate, the margin index and equity are updated at 314. Therefore, the margin can be updated based on ABR requests based on on client. Updating based on client-based ABR requests helps react to device and / or link end-user issues that are not detected by the central session manager.
At 316, the determination is made again if the margin, updated at 314, is less than a margin threshold. If it is not less than the threshold, the session is rejected at 312. If not, at 318, the selected flow rates are reduced and at 308 the session is accepted and the fairness index is updated.
In modalities, the flow selection for speed adjustment varies depending on the speed requirements of the Multiple Service Attendant (MSO), per user and per device. In modalities, each flow has an updated application equity index based on history.
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Flow selection can be based on maximum and minimum limits (for traffic and VQ index). Additionally, stream selection can determine unicast to multicast transitions. For example, slow links can result in a longer mean time, which can affect both the user and others in the AP range.
Figure 4 depicts an exemplary flow chart for network-based control of an adaptive bit rate request, with the beginning of the flow chart represented by 402. At 404, the algorithm determines an adaptive bit rate request that includes a request to reduce or decrease the bit rate of a particular stream, now the stream under analysis. If the adaptive bit rate request includes a request to lower or lower the bit rate, at 406 the analysis is whether the margin is less than a first threshold, eg Thresh2. The margin can be calculated, as described with respect to Figure 3. If the margin is less than the margin threshold value, then at 410 the margin index and equity are updated and the rate for the flow under analysis . If the margin is not less than the margin threshold value, at 408 the margin and equity index are updated and the speed of the selected flows is reduced. The selected flows may or may not include the flow under analysis. For example, if a flow problem results due to congestion, and if the network controller decides that the problem is due to congestion, the system may choose to lower the speeds of other flows that have the highest fairness ratios.
If it is determined at 404 that the adaptive bit rate request does not include a request to reduce or decrease the bit rate, at 412 the determination is whether the margin is less than a second threshold value, eg, Thresh3. It is observed that the THRES2 and THRESH3 values can be identical in such a way that the system can increase the speeds in a conservative way. If the margin is less than the threshold value, then at 416 the margin and the equity index are updated and the speed of the selected flows is increased. The flows can be ordered based on their equity index that takes into account your needs and your history of service speeds compared to other streams in the system. Speeds are then increased to achieve optimal overall fairness. User requests for speed increases that were not met can also be taken into account based on moving average values of network resources and individual flow conditions.
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If the margin is not less than the threshold at 412, no change is made to the margin or equity index, represented by 414.
Figure 5 depicts a flow chart for a session end algorithm, with the beginning of the flow chart represented by 502. At 504, the margin is updated for a session path. For example, in Figure 3 the margin can be updated to 308 or 314 and in Figure 4 the margin can be updated to 408, 410, and 416, for example. If the updated margin is less than a threshold value, for example, Thresh3, then the margin index and equity are updated by 508 and the speeds of the selected flows are increased. Flows can be selected based on their equity index order as discussed in the previous section. If the margin is not less than the threshold value at 506, then there is no change in the margin index and equity, as represented by 510.
Modalities whereby a client-based ABR request is used to correct network-based bandwidth estimates were described above. In contrast, conventional individual bandwidth estimation is carried out between a client and network controller (such as using the Packet Pair concept or other bandwidth estimation methods), and cannot
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The techniques described are based on the fact that shared air spectrum fairness is affected by many factors, including the interaction of algorithms in different layers (for example, congestion control mechanisms at 802.11 MAC, TCP and 802.11 streaming algorithm levels. HTTP). In modalities, an application-level fairness index is used based on grouping users sharing the same network path and user actions (for example, ABR requests). Based on the decision and application fairness index margins, a user's request may change not only their estimate of bandwidth or other conditions, but it may change those of other users in the same group as well.
The use of the application fairness index helps in distinguishing individual link problems (such as signal drop or hidden node problems) vs. congestion (high traffic usage) in the WiFi hotspot. For example, if the network controller begins to receive slowdown requests from multiple users associated with the same AP, by correlation to the estimate of network bandwidth (margins), the<sub>2β</sub> IMPI ^
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In addition to the techniques described, they address stability and network utilization problems. For example, if a user has individual link problems (for example, the user asks for speed decrease, while the corresponding margin is high and other users who share the same AP do not request speed decrease), The fairness index and margins can be updated not to slow down any other user but also to ensure that the user with individual link problems can get more bandwidth quota once their conditions improve. Margins help keep greedy users to get full width
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It is noted that while Figures 3-5 illustrate embodiments of the described techniques, the algorithms may vary or include options other than those shown. For example, in Figure 4, a customer ABR request to decrease the flow rate may result in the decrease of the rates of other flows based on margin. There may be multiple decrease requests from different users in a specific time window (showing general increased / interference congestion in the AP region).
As described in more detail below, various information from the network (s) can influence the adaptive resource management of flows, such as traffic information, resource information, or other metrics. Information about video traffic in on-demand applications, for example, may include peak video-on-demand speeds as a function of time (eg, game cheats). For live play, the traffic information may include maximum speeds for every x seconds ahead of the live broadcast being played.
Resource information can include margins of a CMTS or
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Although the above examples are described with respect to wired Wi-Fi networks, it should be understood by one of ordinary skill in the art that the techniques described can be applied to other network architectures, as well as fiber, cellular, WiMax networks.
Figures 6 and 7 illustrate details of system architectures configured to implement the techniques described. As shown, the traffic control modules include admission control blocks 610, 708 and rate adaptation blocks 608, 705. In these examples, each new video is defined as a stream.
In Figure 6, video input 603 to coding block 606 may originate with video source and processing module 601. Video input 603 may be encoded in coding block 604. One-speed stream bit rate is provided to a rate adaptation module 608, which provides a
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As shown in Figure 7, a different architecture is shown where the encoded video file processing module 701 outputs an encoded stream 703, provides a stream with a certain bit rate 704 to the rate matching module 705, and provides flow characteristics information 702 (traffic, content, target QoS information, network path, etc.) for admission control module 708. The admission control module 708 provides a status 709 to the encoded video file processing module 701 and can also <sub>32</sub> STOP rwrmrro mwucang
FROM PROHSIM · INBUSTUAL to provide 707 video information specific to the 705 rate matching module. The output of the 701 encoded video file processing module can be adjusted based on the 706 target file information (rate or QP) of the module. speed adaptation 705 and the status information 70 9 of the admission control module 708.
The intake control modules 610, 708 estimate the probability for each flow to exceed a delay limit. A new flow or bandwidth / resource change can change the delay probabilities of existing flows. If the final probabilities for each flow are within the acceptable range, the new flow is accepted, otherwise the flow is rejected as explained by the algorithm in Figure 3. A renegotiation with new traffic and quality of service (QoS) information may be acceptable for some use cases.
Rate adaptation modules 608, 705 receive a priori traffic information for a predetermined time interval (eg, the next 2 seconds) and calculate delay limits for each flow. If a delay limit is exceeded for a flow, a new leveling speed is requested (see Figure 8) or a new file chunk (see Figure 9). The functionalities of the modules
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Note that the function blocks shown in Figures 6 and 7 can be implemented within video processing components, such as session and resource managers, packers, and edge streaming servers.
Various modalities for the implementation of the techniques described are described below. Although the embodiments describe a round robin scheduler, it should be understood by one of ordinary skill in the art that other schedulers, such as weighted fair queuing, may also be used.
A CMTS can include a downstream scheduler. Rate adaptation and admission control modules, such as 610, 708, 608, and 705 in Figures 6 and 7, can be based on a delay limit calculation from a downstream DOCSIS scheduler. In modalities, the downstream scheduler is based on the Prioritized Hierarchical Round Robin (HPRR) scheduler. Each packet is assigned a service flow based on its traffic specifications. Each flow is considered to be a member of a single service class, which describes a set of data forwarding services provided to the flows. For purposes of<sub>34</sub> IMPI ^
Mnmrro MUUCANC μ the nonuM »0 * ^ 30 industrial exemplification, suppose classes of services of voice, video, high-speed data (HSD) with high priority and HSD with best effort traffic. Management packets are sent immediately when the channel is ready to transmit.
Packets are first subject to a token bucket limiter (named after the algorithm of the same name) defined by Maximum Sustained Traffic Rate (MSTR) and Maximum Traffic Burst (MTB) of their flows. If the new packet exceeds the allowed burst rate, it is delayed until enough token is accumulated or released if overflow occurs and time to live (TTL) is exceeded. Packets that pass their maximum token bucket limiter rate are sent in one of two classes: the configured class of the stream if they pass another token bucket limiter defined by the Minimum Reserved Rate (MRR) of the stream, or the default class otherwise. Therefore, the HPRR method allows a packet in a stream to be forwarded either as part of the bandwidth allocated to its class of service or as part of the best effort bandwidth allocated to the default class. This feature allows flows of an overbooked class to continue to be serviced through the default class.
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Streams in the same class are virtual per-class by using
Round Robin deficit, where the quanta forwards to the planning queue by are based on your MRR or MSR if your MRR is zero. When the channel is available for transmission, the virtual queues by class are served in the order of scheduling priority, using another Round Robin Deficit algorithm, where the highest priority class is served until its quantum runs out. A quantum class is based on a maximum allocated bandwidth (MAB) that determines the amount of channel bandwidth reserved for the class. The class quantum ratio is proportional to the MABs ratio, adding to a total quantum value (for example 50k bytes).
Configured Active Percentage (CAP) parameters define the percentage of flows that are expected to be active simultaneously. The flows are admitted such that the CAP percentages times the sum of the MRRS admitted flows is less than the MAB percentage of the capacity allocated for the class on the channel. If at some point more than the expected number of active flows is actually active, the class becomes excess. In this case, flows in this class may receive less than their minimum reservation speed, but also be serviced through the default class. Guaranteed services like voice se
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The techniques described can be used on a DOCSIS network.
For example, margin estimates can be made by lag limit calculations that are validated through simulations. MSTR, MTB, MRR, and traffic priorities are DOCSIS service flow parameters, while MAB, CAP, scheduling priority can be proprietary parameters. DOCSIS service flow parameters are assigned from RSVP FLOWSPEC parameters with the recommendations given or by using parameters such as DSCP codes when flows are first activated. A flow reservation is deactivated if there is no activity within the expected time activity value.
Packets that exceed the transmission buffer flow capacity in the CMTS are released. Service packets such as voice and video are received by the CMs in the receive buffers modeled with buffer delays to eliminate packets with higher delays.
A delay limit calculation is made based on a priori information on traffic and resource estimates.
Resource estimation is determined by network resources (for example, available bandwidth) and components of
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Latency speed servers are introduced when delay limit calculations are explained for DRR planners. Error correction can be done with the calculations that have the same origin in the DRR delay limit based on the server definition of latency speed.
Improving on conventional techniques, the described application of an adjusted DRR scheduler for encoded MPEG frames is done in terms of a smaller entity that can be served in one transmission attempt. In the described modes, for example, IP packets (encapsulated MPEG-2 TS packets) are smaller entities, while a burst is defined as the sum of the IP packets within the same round time. The implementation assumes frame boundaries within a burst are known to ensure that complexity does not increase. Therefore the maximum deficit after one round can be (IP packet size -1).
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If the flows have service proportional to their
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The following parameters define the DRR planning system:
• wi = Weight for flow i (Swi = W) • Qi = quantum for flow i = wi * Qmin • DCi = deficit for flow i • mi = maximum burst size for flow i • mmi = maximum packet size for flow i • Fn = DRR round size in round n
The modified DRR system has the following definitions:
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Figure 8 represents a graphical derivation of a delay limit to a modified DRR, where the x-axis represents time and the y-axis represents the service speed for a flow (i). The derivation by the maximum delay for the flow (i) is represented graphically in Figure 8. By using the derivation of the max_delay it can be shown as:
• Felt (ti, tik) max {0, pi (ti-tik -1 / r ((F-Qi) + Ej
Ψ i (mmj-1) + (F / Qi-1) * (mi-1)))} • max_delay = 1 / r ((F-Qi) + Ej / i (mmj-1) + (F / Qi -1) * (mi-1), where max_delay is the delay to the modified DRR.
The derivation shown in Figure 8 shows an example of the described techniques used in a BSR CMTS scheduler to estimate delay limits, which can be used for margin estimates. Note that the latency of a guaranteed rate scheduler is the cumulative measure of time a stream has to wait until it begins to receive service at its guaranteed rate. By using similar triangles (where the service speeds are of the initial type and the guaranteed speed), it can be shown that max_delay = di + d2 is the same as derived above.
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Please note that this derivation is also valid
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If the traffic characteristics are known in a more precise way, the utilization can be increased (at the expense of having a more complex implementation of admission control). For example, if frame sizes are known for given time intervals, a deterministic traffic model can be used. The maximum utilization still depends on the scheduler timing and the interval of the traffic restriction functions. Additionally, stunt mode replay can change traffic time intervals, hence overlapping peak areas. Therefore, it is shown below that statistical admission control with rate adaptation can cover more use cases where delay limits can be guaranteed by conditions of given type. For example, a user may require 90% of the time of a premium speed, while 9% of the time of a lower speed and 1% of the time of a lower speed can provide
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In modalities, a statistical admission control with speed adaptation based on our planner is considered. As explained above, the trade-off between video synchronization flows with the traffic control module and the complexity of the implementation defines network utilization and user QoE. As described, the algorithms can be adjusted based on the synchronization of traffic information and the system. Ά A calculation example is described below where it is assumed that traffic information is known as video frame sizes with a corresponding video frame interval, and a delay variation (jitter) is assumed between the control module of the traffic and video source.
Based on queuing theory, if Aj [s, x] is the size of the arrival of flow j in the time interval [s, i] and Sj [s, t] is the service it received during this time ( S is the muzzle velocity shown in figure 8), the queue size is:
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Suppose that traffic information A is known for all flows j in a given time interval. The service time of each flow j during that time depends on the scheduler. The characteristics of our planner considered in the example can be summarized as:
• Flows are regulated through Max speed and traffic limitations.
• A flux quantum size is predetermined.
• A single class case is assumed (no dependency on inter-class parameters) (Note that multiple classes can be incorporated based on the priorities and values of the quantum class).
• Minimum reserved speeds may be exceeded.
• A round trip time is determined by the total number of bytes of active flows (queued from previous rounds + ne w arrival).
• Multiple packets can arrive for a flow between round visits (bytes in queue + new arrival can exceed quantum size) - (Note that this is related to the characterization and frame statistics of D-bind traffic within the GOP structure) • The maximum delay for a flow arrival is determined by the size of the corresponding flow queue and the
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• Packets that exceed the flow quantum size for the corresponding priority class can be transmitted through a default queue. The delay is then determined by the same c alculation for the delay parameters applied to the default queue. Note that this helps to reduce the delays for bursts that exceed the quantum size of the stream, while increasing the delays for the traffic with fewer bursts (set by the flow parameters).
Figure 9 illustrates the resulting queuing behavior, including the size of the queue corresponding to the maximum delay. Figure 9 graph Time on the x-axis versus the cumulative number of items on the y-axis. By estimating the arrival speed and the service speed, we can calculate the expected queue size and therefore the flow delay. Based on the size of the buffer, the
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The results in Figures 10A and 10B represent simulation results of time (x-axis) versus cumulative (y-axis) arrival and service speeds for a DOCSIS 3.0 Example. In this example, 41 HD (High Definition) Videos are multiplexed as VBR traffic. The graph on the left in Figure 10A shows the average arrival and service of a flow. The graph to the right in Figure 10A shows the queuing delay for this stream. The graph on the left in Figure 10B is the enlarged version of the graph on the left in Figure 10A for the time interval with maximum delay. Comparing the graph on the left in Figure 10B against Figure 9 shows a corresponding tail behavior. The difference between arrival and service speeds, that is, the speed of traffic and network performance, providing the size of the queue. The graph on the right in Figure 10B shows the queue and delay size for this stream in the corresponding time interval.
Figure 11 demonstrates that the service speed of
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Admission control and rate adaptation are now described with the results of an exemplary implementation of admission control with rate adaptation. In this example, admission control with rate adaptation is based on a delay limit calculation from a CMTS DS scheduler.
Figure 12 represents the simulation model. Admission control is implemented in Matlab to define the flows that can be accepted. Three streams are represented from three sources, source # 1 defined by user device 1201a, hub 1202a, and cable modem 1203a; source # 2 defined by user device 1201b, hub 1202b, and cable modem 1203b; and
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INTXISTUAL the source #N defined by user device 1201η, concentrator 1202η and cable modem 1203η, where N and n represent any number of streams that can be received.
The video source located at the remote server node 1209a gets measurement time interval from the traf_stat node 1206, and sends the traffic information for the next time interval to the traf_stat node 1206 which maintains the traffic information for each stream . The CMTS node 1204 maps each video stream to DOCSIS stream, takes traffic information from traf_stat for each measurement time interval, and calculates delay limits. If the delay limit is exceeded, a lower rate is applied for flows with higher rates offered until the delay limit is reduced to acceptable levels. Note that the selection of flows can be done randomly, based on a priority order or the equity index. The speed changes for each flow are maintained during the run time to ensure that the flows that exceeded the percentage of not using the premium speeds are not selected for speed change. The rate change request is sent back to the remote server node 1209b which provides the
The selection of measurement times and traffic information available during these times define the accuracy of the delay limit calculation. For example, the DRR scheduler is implemented based on active flow orders, not the first due date or the highest delay values. As illustrated in Figure 13, transmission times for NP4 and NP5 frames depend on packets queued up to Wt3 and arrivals on Wt2. Therefore, different actions can be taken to optimize speed adaptation. One can adjust the speed of the flows in Wtl (selecting W based on the delay limit and assuming all arrivals early in W) or adjust the speed of the flows in Wt2 (taking into account the calculation of Wtl). For such problems, known video traffic characteristics can be used. For example, the long-range dependence of the video footprints would indicate that the next time the measurement would have large frames with a high probability of a stream with large frames at the current measurement time, assuming that the measurement time it is in the order of GOP time.
The system architecture that can implement the described techniques can be implemented in a variety of ways to distribute signaling and traffic control functionalities among modules.
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INSTÍTUTO MÍMICA NO Df LA ηΟΠΙΟΑΠ INDUSTRIAL
In embodiments, the system architecture includes encoders and speed control modules in separate locations and connected through an IP network, eg, LAN or WAN. In modalities, the system requires constant measurements of video (eg bit rate, complexity), video information (eg resolution), and available bandwidth (buffers must be adjusted for this information). In modalities, multicast is used for signaling.
Although the techniques described can benefit from a perfectly synchronized network, since traffic control is based on delay limit calculation for admission control with rate adaptation, close timing is not so crucial. Delay guard bands can be defined in such a way that estimated time errors can still be accommodated at the expense of less utilization.
In the absence of Packet Cable MultiMedia (PCMM) or Dynamic Quality of Service (DQoS) compliance, both admission control and rate adaptation can be implemented in the CMTS, where new signaling is established between the CMTS and the sources. (for example, encoders) (all video destinations are assumed to be Client Type 1). Policies can be
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ΙΝΓΠΤυΤΟ MEXICANO «the ηβΠΠΜΓ iNfcurnuAi configured in CMTS where the parameters can be changed through the management of the service provider.
If PCMM is implemented, the PCMM policy can be signaled to the traffic module (push or push methods) that is connected to the CMTS DS scheduler. Application server or administrator signaling can be used for a priori information distribution. The functions defined in this document can be implemented in other centralized controllers as a device or common entity software.
Figure 14 is a block diagram of an example CMTS device that may include the disclosed admission control functionality. However, it should be understood that many different types of network devices (eg, including network hubs, bridges, routers, edge termination devices, etc.) can implement congestion control. The CMTS 1400 may include a processor 1410, a memory 1420, a storage device 1430, and an input / output device 1440. Each of the components 1410, 1420, 1430, and 1440 may, for example, be interconnected via a bus. 1450. Processor 1410 is capable of processing instructions for execution within system 1400. In one implementation, processor 1410 is a
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MWCAMO INSTITUTE
MLAraOñEDAD industry i single threaded processor. In another application, processor 1410 is a multi-threaded processor. Processor 1410 is capable of processing instructions stored in memory 1420 or storage device 1430.
Memory 1420 stores information within system 1400. In one implementation, memory 1420 is a computer-readable medium. In one implementation, memory 1420 is a volatile memory unit. In another implementation, memory 1420 is a non-volatile memory unit.
In some implementations, storage device 1430 is capable of providing mass storage for system 1400. In one implementation, storage device 1430 is a computer-readable medium. In several different implementations, the storage device 1430 may, for example, include a hard disk device, an optical disk device, flash memory, or some other large capacity storage device.
The input / output device 1440 provides input / output operations for the system 1400. In one implementation, the input / output device 1440 can include one or more of a flat old telephone interface (eg, an RJ11 connector), a network device
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INDUSTRIAL ”interface, for example, an Ethernet card, a serial communication device, for example, and an RS-232 port, and / or a wireless interface device, for example, and an 802.11 card. In another implementation, the input / output device may include controller devices configured to receive input data and send output data to other input / output devices, such as one or more CPE 1460 devices (eg, set-top box, modem cable, etc.), as well as sending communications to and receiving communications from a 1470 network. Other implementations, however, can also be used, for example, mobile computing devices, mobile communication devices, set-top box television client devices, etc.
In one or more examples, the functions described herein can be implemented in hardware, software, firmware, or any combination thereof. If implemented in software, the functions can be stored in or transmitted through as one or more instructions or code on a computer-readable medium and executed by a hardware-based processing unit. Computer-readable media may include computer-readable storage media, which corresponds to a tangible medium such as a data storage medium, or communication media including any medium that facilitates the transfer of a computer program from one place to another, for example, according to a communication protocol. In this way, computer-readable media can generally correspond to (1) non-transient, tangible, computer-readable storage medium or (2) a communication medium such as a carrier wave or signal. Data storage media can be any available medium that can be accessed by one or more computers or one or more processors to retrieve instructions, code and / or data structures for the application of the techniques described in this description. A computer program product can include a computer-readable medium.
A computer-readable storage medium may have stored therein the instructions that, when executed, cause a processor to split the OFDM channel for a plurality of modulation levels across the plurality of subcarriers based on a modulation level. . The instructions further cause the processor to define a metric associated with a measurable characteristic of the network elements, where at least one value of the metric for the metric is associated with each of the plurality of modulation levels, and collects measurements
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INRUrnUAL for a plurality of the network elements that communicates through the OFDM channel, each measurement corresponding to one of the plurality of network elements and a respective one of the plurality of subcarriers. For each of the plurality of network elements , the instructions cause the processor to translate the collected measurements for the respective network element for comparison with the metric values associated with the plurality of levels, and assigning each of the plurality of network elements to a level in the plurality of modulation levels based on comparing the collected measurements for the plurality of network elements to the metric values associated with the plurality of modulation levels. .
By way of example, and not limitation, such computer-readable storage media may comprise RAM, ROM, EEPROM, CD-ROM, or other optical disk storage, magnetic disk storage or other magnetic storage devices, flash memory, or any other medium that can be used to store the desired program code in the form of instructions or data structures and that can be accessed by a computer. Also, any connection is correctly called a computer-readable medium. For example, if instructions are transmitted from a web page, the
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server or other remote source using a coaxial cable, fiber optic cable, twisted pair, digital subscriber line (DSL), or wireless technologies such as infrared, radio and microwave, then the coaxial cable, fiber optic cable, twisted pair, DSL or wireless technologies such as infrared, radio and microwave are included in the definition of medium. It should be understood, however, that computer-readable storage media and data storage media do not include connections, carrier waves, signals, or other transient media, but are directed to non-transient tangible storage media. Disc, as used herein, includes compact discs (CDs), laser discs, optical discs, digital versatile discs (DVD), discs, and Blu-ray discs where the discs generally reproduce the data magnetically, while the discs reproduce the data optically with laser. Combinations of the above should also be included within the scope of computer-readable media.
Instructions can be executed by one or more processors, such as one or more digital signal processors (DSP), general purpose microprocessors, application specific integrated circuits (ASIC), field programmable logic gate arrays (FPGA) , or other equivalent integrated or discrete logic circuitry.
EE M4XÍCANO INITITUTE <sup>33</sup> Μ ΙΑ NIOMUMD iNDUmUAL
Accordingly, the term "processor" as used herein may refer to any of the above structure or any other structure suitable for the application of the techniques described herein. Furthermore, in some aspects, the functionality described in this document may be provided within dedicated hardware and / or software modules configured for encoding and decoding, or incorporated into a combined codec. Furthermore, the techniques could be fully applied in one or more circuits or logic elements.
The techniques of this disclosure can be implemented in a wide variety of devices or apparatus, including a cordless telephone, an integrated circuit (IC), or a set of integrated circuits (eg, a chip set). Various components, modules, or units are described in this description to emphasize the functional aspects of devices configured to perform the described techniques, but do not necessarily require the modality of different hardware units. Rather, as described above, various units can be combined into one codec hardware unit or provided by a collection of interoperable hardware units, including one or more processors as described above, in conjunction with appropriate software and / or firmware. .
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Contents41
43 sheets
Sheet 1 Sheet 2 Sheet 3 Sheet 4 Sheet 5 Sheet 6 Sheet 7 Sheet 8 Sheet 9 Sheet 10 Sheet 11 Sheet 12 Sheet 13 Sheet 14 Sheet 15 Sheet 16 Sheet 17 Sheet 18 Sheet 19 Sheet 20 Sheet 21 Sheet 22 Sheet 23 Sheet 24 Sheet 25 Sheet 26 Sheet 27 Sheet 28 Sheet 29 Sheet 30 Sheet 31 Sheet 32 Sheet 33 Sheet 34 Sheet 35 Sheet 36 Sheet 37 Sheet 38 Sheet 39 Sheet 40 Sheet 41 Sheet 42 Sheet 43
14 members in 7 offices
Priority claims14
| Document | Office | Kind | Date |
|---|---|---|---|
| 201361800311 | United States of America | P | |
| 201361800311 | United States of America | P | |
| 61800311 | United States of America | – | |
| 14210338 | United States of America | – | |
| 2014026891 | United States of America | W | |
| 2014026891 | United States of America | W | |
| 201414210338 | United States of America | A | |
| 201414210338 | United States of America | A | |
| 14210338 | – | – | – |
| 61800311 | – | – | – |
| PCTUS2014026891 | – | – | – |
| US201361800311P | – | – | – |
| US201414210338 | – | – | – |
| WO2014US26891 | – | – | – |
Members14
| Document | Office | Kind | |
|---|---|---|---|
| US2014269314A1 | United States of America | A1 | |
| CA2903858A1 | Canada | A1 | |
| WO2014152056A1 | World Intellectual Property Organization (WIPO) | A1 | |
| MX2015012150A | Mexico | A | |
| EP2954662A1 | European Patent Office (EPO) | A1 | |
| CN105340234A | China | A | |
| US9608923B2 | United States of America | B2 | |
| MX347339BThis record | Mexico | B | |
| BR112015022278A2 | Brazil | A2 | |
| CA2903858C | Canada | C | |
| CN105340234B | China | B | |
| EP2954662B1 | European Patent Office (EPO) | B1 | |
| BR112015022278A8 | Brazil | A8 | |
| BR112015022278B1 | Brazil | B1 |
1 legal event, as the office reported them to INPADOC
Events
| Event | Code | |
|---|---|---|
| Grant or registrationFG | FG |
Numbers
- Publication
- 347339
- Publication, DOCDB
- 347339
- Publication, EPODOC
- MX347339
- Application
- 2015012150
- Application, DOCDB
- 2015012150
- Application, EPODOC
- MX202015012150
Titles2
- Spanish
- GESTION ADAPTABLE DE RECURSOS PARA APLICACIONES DE VIDEO MULTIPANTALLA SOBRE REDES DE CABLE WI-FI.
- English
- ADAPTABLE RESOURCE MANAGEMENT FOR MULTI-SCREEN VIDEO APPLICATIONS OVER WI-FI CABLE NETWORKS.
Classification
- CPC, 5
- H04L65/752
- H04L47/25
- H04L65/80
- H04L65/765
- H04L65/612
- IPC, 2
- H04L12 825
- H04L29 06