WO2014173466A1 - Procédé pour le fonctionnement d'un réseau sans fil et réseau sans fil - Google Patents

Procédé pour le fonctionnement d'un réseau sans fil et réseau sans fil Download PDF

Info

Publication number
WO2014173466A1
WO2014173466A1 PCT/EP2013/063723 EP2013063723W WO2014173466A1 WO 2014173466 A1 WO2014173466 A1 WO 2014173466A1 EP 2013063723 W EP2013063723 W EP 2013063723W WO 2014173466 A1 WO2014173466 A1 WO 2014173466A1
Authority
WO
WIPO (PCT)
Prior art keywords
flow
service
queue
qoe
data
Prior art date
Application number
PCT/EP2013/063723
Other languages
English (en)
Inventor
Faqir Zarrar YOUSAF
Andreas Maeder
Stefan Schmid
Original Assignee
Nec Europe Ltd.
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Nec Europe Ltd. filed Critical Nec Europe Ltd.
Publication of WO2014173466A1 publication Critical patent/WO2014173466A1/fr

Links

Classifications

    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L47/00—Traffic control in data switching networks
    • H04L47/50—Queue scheduling
    • H04L47/62—Queue scheduling characterised by scheduling criteria
    • H04L47/6215—Individual queue per QOS, rate or priority
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L47/00—Traffic control in data switching networks
    • H04L47/10—Flow control; Congestion control
    • H04L47/24—Traffic characterised by specific attributes, e.g. priority or QoS
    • H04L47/2441—Traffic characterised by specific attributes, e.g. priority or QoS relying on flow classification, e.g. using integrated services [IntServ]
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L47/00—Traffic control in data switching networks
    • H04L47/10—Flow control; Congestion control
    • H04L47/24—Traffic characterised by specific attributes, e.g. priority or QoS
    • H04L47/2475—Traffic characterised by specific attributes, e.g. priority or QoS for supporting traffic characterised by the type of applications

Definitions

  • the present invention relates to a method for operating a wireless network, wherein data flows aggregating at a traffic aggregation point will be managed for controlling congestion of data flows at said traffic aggregation point. Further, the present invention relates to a wireless network, wherein data flows aggregating at a traffic aggregation point will be managed by a system for controlling congestion of data flows of said traffic aggregation point.
  • Mobile networks are experiencing a data explosion that is forecasted to grow exponentially in the near future. This data explosion has been spurred by the proliferation of smart phones and other mobile devices that are capable of handling high bandwidth applications, such as live/progressive video streams and even video conferencing applications.
  • the more advanced scheduling policies such as WFQ and DRR assume that all traffic that belongs to a specific class is aggregated in a separate queue, and that each queue is assigned a specific weight according to the traffic class, corresponding to the amount of packets that are transmitted from these class based queues.
  • the aforementioned object is accomplished by a method comprising the features of claim 1 and by a network comprising the features of claim 26.
  • the method is characterized by the following managing steps:
  • the network is characterized by:
  • At least one data flow will be classified according to a rule used to differentiate traffic of said data flows for providing a service signature of said at least one data flow.
  • the provided service signature will be used in the next step wherein at least one data flow will be assigned to a Service Queue in the form of a Per Flow Queue or an Aggregate Flow Queue based on said at least one service signature of the at least one data flow.
  • available bandwidth will be allocated amongst the Service Queues based on a QoE estimation.
  • the invention provides a QoE/context aware priority queuing concept that will ensure a very high degree of fairness amongst multiple simultaneous heterogeneous flows while meeting the end-user QoE expectations. Further, the invention proposes a more dynamic and diverse queuing model that can be used by many weight-based schedulers/traffic-shapers and can take into account a variety of context information and can provide a higher degree of flow isolation to prevent against bandwidth starvation due to misbehaving flows.
  • the method can be realized in an access device or network element at said traffic aggregation point or as a middle box solution to be placed at said traffic aggregation point.
  • the method can be employed at traffic aggregation points, either integrated in access devices at such locations or as a middle box solution to be placed at traffic aggregation points.
  • the rule can comprise at least one service template, ST.
  • Such a service template is a rule used to differentiate traffic.
  • the rule can use at least one property of said at least one data flow to differentiate traffic.
  • Said at least one property can preferably be, and not limited to, IP-5-tuples and/or application type and/or subscriber information and/or header information and/or payload information and/or type of Service information and/or QoS information, particularly Differentiated Service Code Points, and/or QoS requirements and/or QoE requirements and/or security requirements and/or device capabilities.
  • the rule can be associated with at least one Service Policy, SP, for defining a handling of said at least one classified data flow.
  • SP Service Policy
  • a simple and effective classifying step can be realized.
  • said at least one Service Policy defines the Service Queue type and/or a priority of handling and/or an associated bandwidth and/or a key performance indicator, KPI, of said at least one data flow.
  • KPI key performance indicator
  • a data flow being sensitive to QoS and/or QoE variations will trigger a creation of a new Per Flow Queue to which the data flow will be assigned to.
  • long-lived traffic flows which are sensitive to QoS/QoE variations such as adaptive or non-adaptive video streaming are assigned to Per Flow Queues in order to be able to meet the QoS/QoE requirements of traffic flows individually and to provide efficient isolation from other traffic.
  • a data flow not being sensitive to QoS and/or QoE variations and/or being not suitable for a per-flow scheduling will be assigned to an Aggregate Flow Queue.
  • Traffic which is not suitable for a per-flow scheduling could be short-lived flows or bursty traffic such as web-traffic, instant messaging or signaling massages.
  • data flows belonging to a specific application type and/or sharing the same priority will be assigned to a dedicated Aggregate Flow Queue, wherein preferably - in case the Aggregated Flow Queue has not been created - the first data flow associated with said AFQ will trigger the dynamic creation of said AFQ.
  • an effective handling of such data flows can be ensured.
  • data flows that can not be classified will be assigned to a default Aggregate Flow Queue.
  • all data flows can be assigned to suitable Service Queues.
  • the classifying step can comprise an analyzing step of at least one packet, preferably the first packet with application data payload, of the at least one data flow. Based on that, the method or network is able to detect the application type and can then instantiate a new Per Flow Queue or Aggregate Flow Queue, if no adequate queue is available yet, or assign the new flow to an already existing AFQ.
  • the analyzing step can comprise a Deep Packet Inspection, DPI.
  • DPI Deep Packet Inspection
  • a check of a Flow-Database, flow-db, on the basis of the flow-id will be performed to determine if the packet belongs to an already known or classified data flow, and in case the data flow already exists, the packet or data flow will be directly assigned to its associated Service Queue without the classifying step, and in case the data flow does not exist, a new flow-id will be derived and the classifying step will be performed.
  • the flow-id can be a hash derived from a packet's header information and/or payload information, preferably depending on the system's DPI capabilities.
  • the flow-db contains a mapping of the flow-ids with its corresponding service signature.
  • user and/or network context information from at least one control entity of the network can be used during said classifying and/or assigning and/or allocating step.
  • said user and/or network context information can be provided - preferably via an access and/or an interface - to said at least one control entity.
  • the QoE estimation can be based on an application type and/or flow statistics.
  • flow statistics can include average throughput over some time windows or the total flow time, jitter, delay etc.
  • the individual and preferred realization of such a QoE estimation can depend on individual application situations.
  • a target bandwidth can be computed and used as input to parameterize a scheduler within the allocating step.
  • the allocating step can provide maximum bandwidth utilization.
  • the allocating step targets to maximize the QoE for all data flows under the constraint of limited network resources, which preferably can be bandwidth and/or processing power.
  • a Service Profile Matrix that lists the QoS and/or QoE requirements or QoS and/or QoE profiles of different service types in terms of target bitrates for different load or congestion levels can be used for determining the target bitrate for each Service Queue.
  • QoS and/or QoE profiles and/or the QoE estimation of all the flows or of individual flows with lower priority according to a Service Profile Matrix, SPM can be decremented, if the sum of all computed target bitrates exceeds the available/measured bandwidth.
  • the allocating step can be performed, when a new SQ is created or when a number of data flows assigned to an AFQ exceeds a specified number or during each evaluation epoch.
  • the above invention proposes a system's or network's method of dynamic queue management for effective congestion management that will allow for a high degree of demarcation and flow isolation between multiple traffic flows based on application or service requirements. Such a method will enable intelligent and QoE/context aware scheduling of flows in times of congestion, or even prevent against the buildup of congestion. With reference to the proposed method, it is described a novel bandwidth sharing/management method for optimizing per- application utility of the bottleneck capacity.
  • the above invention which is aimed at managing user plane congestion while ensuring to meet user expected QoE, can either be employed in an existing mobile network entity that aggregates traffic, or it can be deployed as a middle box solution at the traffic aggregation point.
  • the invention proposes a system's or network's method of dynamic queue management for effective congestion management by QoS/QoE/context aware management of individual flows.
  • the proposed system or network method classifies flows and assigns them to a specific Service Queue (SQ), or dynamically instantiates a relevant new SQ if none exists, based on the flow's service signature. Once the flow session terminates, and no flows are associated to a particular queue, then the associated queue will be destroyed.
  • SQL Service Queue
  • SQs can thus be driven by the traversing traffic flows and their classification according to service templates (STs), and the associated service policies (SPs).
  • ST is a rule used to differentiate traffic; it can use a multitude of properties such as IP-5-tuples, application type, subscriber information, etc. for differentiation.
  • the SP then defines the handling of the categorized traffic, such as defining the associated queue type, the priority, associated bandwidth, key performance indicators (KPIs), etc.
  • the system or network can in general have the following basic types of SQs: 1. Per Flow Queues (PFQ)
  • PFQ Per Flow Queues
  • Long-lived traffic flows which are sensitive to QoS/QoE variations such as adaptive or non-adaptive video streaming are assigned to PFQs in order to be able to meet the QoS/QoE requirements of traffic flows individually and to provide efficient isolation from other traffic.
  • Traffic which is either not suitable for per-flow scheduling, e.g. short-lived flows/traffic bursts such as web-traffic, instant messaging or signaling messages, or which is less sensitive to QoS/QoE variations is put to AFQs.
  • the aggregation can be based on common application type, where all flows belonging to a specific application type and sharing the same priority are aggregated in a dedicated AFQ. For example, all web traffic flows for users with the same subscription level, e.g. "gold", may be aggregated in a dedicated AFQ with certain QoS properties such that on average, the expectations of the users with this subscription level for web traffic are fulfilled.
  • a separate AFQ can be instantiated for users with "bronze” subscription. All other flows that could not be classified, e.g. encrypted flows, can be aggregated in a separate AFQ, and handled accordingly. The latter type can be considered as a default queue which is not application specific, but aggregates all unclassified flows.
  • high priority signaling traffic for example TCP SYN/ACK messages or IMS signaling messages
  • TCP SYN/ACK messages or IMS signaling messages can be aggregated in a dedicated AFQ with a high priority.
  • the application type could not already be detected by the src/dst IP address and port pairs and protocol type, i.e. "five tuple”
  • the system will analyze the first packet with application data payload, e.g. through DPI. Based on that, the system is able to detect the application type and can then instantiate a new PFQ or AFQ, if no adequate queue is available yet, or assign the new flow to an already existing AFQ.
  • flow whose application cannot be detected by analyzing the first data packet only, i.e.
  • a system or network employing the method can have a multiple instances of PFQ and AFQ, the numbers of which will change dynamically, owing to traffic classes.
  • the effectiveness of the invention depends on the system's ability to accurately identify the flow's application type.
  • Fig. 1 is a general overview of an embodiment of a method according to the invention in the form of a flow diagram
  • Fig. 2 is showing important features of an example system or network employing and managing a hybrid queuing system according to an embodiment of the invention
  • Fig. 3 is showing a generic overview of a bandwidth evaluation/distribution method according to an embodiment of the invention.
  • Fig. 4 is showing an example of a Service Profile Matrix.
  • Fig. 1 shows a general process overview of how a data flow is classified and assigned to a specific queue type according to an embodiment of the invention.
  • the system will do the following:
  • the flow-id can be a hash derived from the packet's header information, and possible payload information depending on the system's DPI capabilities.
  • the flow-db will contain a mapping of the flow-id with its service signature.
  • the packet will be directly assigned to its associated queue. 4. If the flow entry is not found, then the system will derive a new flow-id and perform flow classification based on the header information, and additionally payload information. For flow classification, the supporting system will maintain and/or have access to a Service Template (ST) database.
  • ST Service Template
  • a ST will typically have preconfigured filters that will discriminate between different flows based on, but not limited to, the application type, header information, payload type, QoS/QoE requirements, security requirements etc.
  • the ST will also have access to subscriber profile information, accessed from an external/internal Subscriber Information Database, to derive flow profiles for same application type but for different user profiles.
  • the classifier will derive/assign a service signature for the new flow based on the flow profile match obtained from the ST and the Service Policy (SP) rule defined by the operator defining how the flow should be managed, for example, defining the queue type.
  • SP Service Policy
  • the classifier uses the input from the ST and SP to derive a service signature including the specification/definition/characterization of a Service Queue (SQ) for the particular flow.
  • SQL Service Queue
  • SQ Service Queue
  • the system scheduler With the new flow in the system and assigned to a queue, either existing or new, the system scheduler will be appropriately (re)configured to ensure fair scheduling of packets from the multiple queues within the system.
  • FIG. 2 A functional architecture of an embodiment of a system or network employing our invention is illustrated in Fig. 2, and is assumed to have the following functional capabilities: 1.
  • the system should be able to detect/identify application type of each flow.
  • the system should be able to classify and prioritize the flows and assign relevant queues.
  • the system should have access/interface to relevant control entities of a network, e.g., PCRF (Policy Charging and Rules Function), HSS (Home Subscriber Service) of a 3GPP infrastructure, to be able to determine relevant user/network context information.
  • PCRF Policy Charging and Rules Function
  • HSS Home Subscriber Service
  • the system should be able to make QoE estimate based on the knowledge of application type, flow statistics, such as but not limited to throughput, delay, jitter, PER/BER (Packet Error Rate/Bite Error Rate) and other context information.
  • flow statistics such as but not limited to throughput, delay, jitter, PER/BER (Packet Error Rate/Bite Error Rate) and other context information.
  • the challenge presented by the proposed dynamic queuing system is the dynamic and optimal parameterization of the scheduler to multiple instances of PFQ and AFQ.
  • the bandwidth distribution method should be such that the system ensures maximum bandwidth utilization of the egress link such that:
  • Fig. 3 gives a generic overview of a bandwidth evaluation/distribution method that can be employed with respect to our invention.
  • the system iterates over all SQs and computes the Target Bandwidth (TBW) for all the flows.
  • TW Target Bandwidth
  • the TBW is the sum of the bandwidth (data rate) of all flows that the classifier would have recommended based on the SS (Subscriber Service) of the individual flow to meet the maximum quality requirements of a service. It can be represented as:
  • the system will then compare the computed TBW with ⁇ . If it is less than or equal to ⁇ , then the SQ-Rates are assigned to the respective SQs and the underlying scheduler is configured accordingly, where the SQ-Rate (3 ⁇ 4) is represented by ln case the TBW exceeds ⁇ then the system will decrement the QoS/QoE profile of all the flows sequentially until it becomes equal to ⁇ , and the underlying scheduler is configured corresponding to the new
  • the bandwidth distribution method is executed when
  • the system periodically monitors the SQs and evaluates flow statistics with reference to compliance to specific QoE/QoS requirements. At each evaluation epoch, the system can then (re)compute the 3 ⁇ 4 ⁇ ? for all SQs in order to ensure that the QoE/QoS objectives are being met, while at the same time enable maximum bandwidth utilization of the egress link.
  • SPM Service Profile Matrix
  • the SPM can be manipulated in a variety of ways while determining the TBW for a SS, depending on the service type priority and operator's policy.
  • Our proposed invention is independent of any particular type of scheduler and can be used with any weight based fair scheduler.
  • Embodiment 1 The invented dynamic queue management and scheduling system can be implemented in any packet switched/routed forwarding node, e.g. a router or switch, that targets to support application/QoE aware traffic differentiation and bandwidth scheduling for the forwarded traffic.
  • packet switched/routed forwarding node e.g. a router or switch
  • nodes are routers, switches, wireless base station, e.g. WLAN APs or LTE eNBs, WiMAX base stations, or other middle boxes or packet gateways, e.g. NAT entities, Firewall nodes.
  • the dynamic queue management and scheduling system operates autonomously and is managed based on common network management principles - i.e. operators would provide the policies and parameters that control/drive via the network management system or configure them locally - through a direct control/management interface.
  • Embodiment 2 The invented dynamic queue management and scheduling system can be implemented in a 3GPP based packet gateway, e.g. the GGSN, SGSN, PDN-GW, Serving-GW, ePDG, TWAG, (e)BNG or TDF (Traffic Detection Function).
  • a 3GPP based packet gateway e.g. the GGSN, SGSN, PDN-GW, Serving-GW, ePDG, TWAG, (e)BNG or TDF (Traffic Detection Function).
  • the operator could - besides the available network management interface or local configuration - also provide the policies for the dynamic queue management and bandwidth scheduling via the Gx interface from the PCRF.
  • the dynamic queue management system could be part of the PCEF function of the GGSN or P-GW or a separate function.
  • the existing Application Detection and Control (ADC) function of the PCEF would be leveraged to detect the application type and the information would be used to assign application flows to the adequate queues.
  • a close cooperation between the ADC and the invented functions would be foreseen.
  • the invented queuing and scheduling functions would be either integrated before the bearer binding function, i.e. to schedule the order by which packets are passed into the related - default/non-GBR (Guaranteed Bite Rate) - bearers, or integrated into and extend the existing, bearer centric queuing and scheduling functions of the gateway entities.
  • the operator could - besides the available network management interface or local configuration - also provide the policies for the dynamic queue management and bandwidth scheduling via the Sd interface from the PCRF.
  • the existing traffic detection function of the TDF would be leveraged to detect the application type and the information would be used to assign application flows to the adequate queues.
  • the invented queuing and scheduling functions would be integrated into and extend the TDF's existing packet forward/routing function and its queuing and scheduling functions.
  • the operator could - besides the available network management interface or local configuration - also provide the policies for the dynamic queue management and bandwidth scheduling via the Gxx interface, i.e. Gxc for Serving GW, Gxa for TWAG or (e)BNG, or Gxb for ePDG, from the PCRF.
  • the dynamic queue management system could be part of the bearer binding function of the Serving GW or general packet forwarding function of the TWG, (e)BNG or ePDG.
  • the invented queuing and scheduling functions would be integrated into and extend the entities' existing packet forward/routing function and its queuing and scheduling functions.
  • Important steps of embodiments of the invention are indicated in the following: 1) A method and a system or network that enables congestion management through traffic differentiation based on application type, subscriber class and according to network provider policies, wherein at aggregate points in the network the system performs real-time application flow classification, dynamic management of per application-class or per-flow queues and dynamic parameterization of the scheduler based on a QoE utility optimization function with reference to the available resources.
  • the invention encompasses: a.
  • the queue management system dynamically creates a mix of Per Flow Queues (PFQ) and - application-specific - Aggregate Flow Queues (AFQ).
  • PFQ Per Flow Queues
  • AFQ Application-specific - Aggregate Flow Queues
  • PFQ/AFQs are dynamically instantiated and created when a new flow arrives, and destroyed when the last flow session terminates.
  • the PFQ/AFQs are created and destroyed dynamically based on the currently detected traffic.
  • Traffic flows are assigned to the PFQ/AFQs based on the application QoE and/or context information, e.g., subscription profile, device capabilities etc.
  • Incoming flows are classified on-the-fly according to service queue templates and assigned to specific type of service queue depending on the policies, e.g. based on flow application type and priority.
  • the bandwidth allocated to the different queues dynamically adapts to the current traffic situation, maximizing the overall QoE of the application traffic flows for a given egress bandwidth.
  • the invention is aimed at managing user plane congestion at traffic aggregate points in the network by ensuring that the aggregate service queues' (SQ) bandwidth does not exceed the total bandwidth of the egress link, while ensuring maximum utilization of the link bandwidth.
  • SQ aggregate service queues'
  • a QoE aware dynamic SQ bandwidth demand optimization method is used to dynamically parameterize the scheduler.
  • This embodiment utilizes a Service Profile Matrix for bandwidth assignment to different SQs based on the flow priority.

Landscapes

  • Engineering & Computer Science (AREA)
  • Computer Networks & Wireless Communication (AREA)
  • Signal Processing (AREA)
  • Data Exchanges In Wide-Area Networks (AREA)

Abstract

La présente invention concerne un procédé de fonctionnement d'un réseau sans fil permettant d'assurer un degré élevé d'équité entre une pluralité de flux de données hétérogènes simultanés tout en satisfaisant des attentes de qualité d'expérience (QoE) d'utilisateurs finaux, selon lequel les flux de données sont agrégés à un point d'agrégation de trafic vont être gérés pour le contrôle de congestion de flux de données au niveau dudit point d'agrégation, le procédé comprenant les étapes de gestion suivantes : la classification d'au moins un flux de données selon une règle pour différencier le trafic desdits flux de données pour fournir une signature de service dudit au moins un flux de données ; l'attribution dudit au moins un flux de données à une file d'attente de service, SQ, sous la forme d'une file d'attente par flux, PFQ, ou d'une file d'attente de flux agrégés, AFQ, sur la base de ladite signature dudit au moins un flux de données ; et l'allocation de bande passante disponible parmi les files d'attente de service sur la base d'une estimation de qualité d'expérience, de sorte que la qualité d'expérience dudit flux de données et/ou de l'estimation globale de qualité d'expérience sur tous les flux de données traversant ledit point d'agrégation soit améliorée. L'invention concerne également un réseau sans fil correspondant, de préférence pour la mise en œuvre dudit procédé.
PCT/EP2013/063723 2013-04-26 2013-06-28 Procédé pour le fonctionnement d'un réseau sans fil et réseau sans fil WO2014173466A1 (fr)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
EP13165620.9 2013-04-26
EP13165620 2013-04-26

Publications (1)

Publication Number Publication Date
WO2014173466A1 true WO2014173466A1 (fr) 2014-10-30

Family

ID=48874998

Family Applications (1)

Application Number Title Priority Date Filing Date
PCT/EP2013/063723 WO2014173466A1 (fr) 2013-04-26 2013-06-28 Procédé pour le fonctionnement d'un réseau sans fil et réseau sans fil

Country Status (1)

Country Link
WO (1) WO2014173466A1 (fr)

Cited By (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN105373118A (zh) * 2015-12-07 2016-03-02 高新兴科技集团股份有限公司 一种智能设备数据采集方法
WO2017131674A1 (fr) * 2016-01-27 2017-08-03 Hewlett Packard Enterprise Development Lp Gestion d'un trafic de réseau à l'aide d'une capacité expérientielle
EP3220681A1 (fr) * 2016-03-18 2017-09-20 Nokia Technologies Oy Adaptative et dynamique qos / qoe exécution
WO2018006929A1 (fr) * 2016-07-04 2018-01-11 Telefonaktiebolaget Lm Ericsson (Publ) Mise en mémoire tampon de paquets dans un réseau de télécommunications
US10171369B2 (en) * 2016-12-22 2019-01-01 Huawei Technologies Co., Ltd. Systems and methods for buffer management
EP3410641A4 (fr) * 2016-03-14 2019-02-20 Huawei Technologies Co., Ltd. Procédé de régulation de trafic de réseau et dispositif de réseau associé
CN111918340A (zh) * 2020-07-08 2020-11-10 河北百亚信息科技有限公司 一种WiFi无线网络带宽分配方法

Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20090034426A1 (en) * 2007-08-01 2009-02-05 Luft Siegfried J Monitoring quality of experience on a per subscriber, per session basis
WO2009049676A1 (fr) * 2007-10-17 2009-04-23 Ericsson Hungary Ltd Procédé et appareil à utiliser dans un réseau
US20120327779A1 (en) * 2009-06-12 2012-12-27 Cygnus Broadband, Inc. Systems and methods for congestion detection for use in prioritizing and scheduling packets in a communication network
WO2013041587A1 (fr) * 2011-09-19 2013-03-28 Nec Europe Ltd. Procede et systeme de commande d'admission d'un flux de trafic d'un équipement utilisateur

Patent Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20090034426A1 (en) * 2007-08-01 2009-02-05 Luft Siegfried J Monitoring quality of experience on a per subscriber, per session basis
WO2009049676A1 (fr) * 2007-10-17 2009-04-23 Ericsson Hungary Ltd Procédé et appareil à utiliser dans un réseau
US20120327779A1 (en) * 2009-06-12 2012-12-27 Cygnus Broadband, Inc. Systems and methods for congestion detection for use in prioritizing and scheduling packets in a communication network
WO2013041587A1 (fr) * 2011-09-19 2013-03-28 Nec Europe Ltd. Procede et systeme de commande d'admission d'un flux de trafic d'un équipement utilisateur

Cited By (9)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN105373118A (zh) * 2015-12-07 2016-03-02 高新兴科技集团股份有限公司 一种智能设备数据采集方法
WO2017131674A1 (fr) * 2016-01-27 2017-08-03 Hewlett Packard Enterprise Development Lp Gestion d'un trafic de réseau à l'aide d'une capacité expérientielle
EP3410641A4 (fr) * 2016-03-14 2019-02-20 Huawei Technologies Co., Ltd. Procédé de régulation de trafic de réseau et dispositif de réseau associé
US11316795B2 (en) 2016-03-14 2022-04-26 Huawei Technologies Co., Ltd. Network flow control method and network device
EP3220681A1 (fr) * 2016-03-18 2017-09-20 Nokia Technologies Oy Adaptative et dynamique qos / qoe exécution
US10439943B2 (en) 2016-03-18 2019-10-08 Nokia Technnologies Oy Adaptive and dynamic quality of service/quality of experience enforcement
WO2018006929A1 (fr) * 2016-07-04 2018-01-11 Telefonaktiebolaget Lm Ericsson (Publ) Mise en mémoire tampon de paquets dans un réseau de télécommunications
US10171369B2 (en) * 2016-12-22 2019-01-01 Huawei Technologies Co., Ltd. Systems and methods for buffer management
CN111918340A (zh) * 2020-07-08 2020-11-10 河北百亚信息科技有限公司 一种WiFi无线网络带宽分配方法

Similar Documents

Publication Publication Date Title
KR100608904B1 (ko) 서비스 품질 보장을 위한 시스템 및 방법
US8868735B2 (en) Wide area network optimization
WO2014173466A1 (fr) Procédé pour le fonctionnement d'un réseau sans fil et réseau sans fil
Zinner et al. Dynamic application-aware resource management using software-defined networking: Implementation prospects and challenges
US20080080382A1 (en) Refined Assured Forwarding Framework for Differentiated Services Architecture
US9432874B2 (en) Service-aware profiling for transport networks
KR100501717B1 (ko) Ｕｄｐ/ｔｃｐ/ｉｐ 네트워크에서 버퍼관리를 기반으로 한음성 및 데이터 통합 전송방법
WO2012161868A1 (fr) Marqueur de priorité par paquet non uniforme à utiliser avec protocoles adaptatifs
Zoriđ et al. Fairness of scheduling algorithms for real-time traffic in DiffServ based networks
Parra et al. Quality of Service over IPV6 and IPV4
EP2946537A1 (fr) Identification de flux de données sur la base d'actions de politiques de qualité de service
Gómez et al. Quality of service drivers in lte and lte-a networks
Mukherjee et al. Fairness Evaluation of a DSCP Based SchedulingAlgorithm for Real-Time Traffic in Differentiated ServiceNetworks
Chaudhuri et al. Validation of a DiffServ based QoS model implementation for real-time traffic in a test bed
Cisco QC: Quality of Service Overview
Bahnasse et al. Policy-based smart adaptive quality of service for network convergence
Rashid et al. Traffic intensity based efficient packet schedualing
Bodamer A scheduling algorithm for relative delay differentiation
Domżał et al. Guide to Flow-Aware Networking: Quality-of-Service Architectures and Techniques for Traffic Management
Zoric et al. Fairness of scheduling algorithms for real-time UMTS traffic in case of IP link congestion
Ahmed et al. A design of packet scheduling algorithm to enhance QoS in high-speed downlink packet access (HSDPA) core network
Kulhari et al. Traffic shaping at differentiated services enabled edge router using adaptive packet allocation to router input queue
Siew et al. Congestion control based on flow-state-dependent dynamic priority scheduling
Wu et al. Direct congestion control scheme (DCCS) for differentiated services IP networks
Yousif et al. Improving QoS for Real-time Traffic using Multiple Low Latency Queueing Scheduling Mechanisms

Legal Events

Date Code Title Description
121 Ep: the epo has been informed by wipo that ep was designated in this application

Ref document number: 13741688

Country of ref document: EP

Kind code of ref document: A1

NENP Non-entry into the national phase

Ref country code: DE

122 Ep: pct application non-entry in european phase

Ref document number: 13741688

Country of ref document: EP

Kind code of ref document: A1