QoE Management with SDN: Concepts and Use Cases

Transcription

1 QoE Management with SDN: Concepts and Use Cases ICTGEN Ognjen Dobrijević and Lea Skorin-Kapov Networked Media Research Group University of Zagreb, Faculty of EE and Computing {ognjen.dobrijevic, COST ACROSS, 2nd Int l Summer School - Opatija, Croatia, May 31 st, 2016

2 Outline Short intro - NetMedia research group Quality of Service (QoS) vs. Quality of Experience (QoE) From QoE modeling to QoE management QoE management with Software-Defined Networking (SDN) Case study: the ICTGEN project Future challenges 2/77

3 Outline Short intro - NetMedia research group Quality of Service (QoS) vs. Quality of Experience (QoE) From QoE modeling to QoE management QoE management with Software-Defined Networking (SDN) Case study: the ICTGEN project Future challenges 3/77

4 Zagreb, Croatia Opatija Zagreb 4/77

5 University of Zagreb, FER University of Zagreb, Faculty of Electrical Engineering and Computing (FER): 12 departments; ~500 employees; ~3,300 students = ~2,050 B.S. (3 years) + ~1000 M.S. (2 years) + ~100 specialist (1 year) + ~150 PhD (3+ years) 5/77

6 The NetMedia group: who we are The Networked Media (NetMedia) research group belongs to FER, Department of Telecommunications NetMedia group members: professor Maja Matijašević assistant professors Lea Skorin-Kapov and Ognjen Dobrijević postdoctoral researchers Sanja Grubeša, Tomislav Grgić and Mirko Sužnjević doctoral students Ivan Slivar, Dunja Vučić and Haris Hadžić 6/77

7 The NetMedia laboratories 7/77

8 Research goals Specification of QoS/QoE requirements for advanced and interactive multimedia services; capture relationships between network-level and application-level metrics Model interplay between multimedia services and network infrastructure Case studies: multi-player online and cloud-based networked games, adaptive video streaming, video conferencing Focus on: cooperative QoE-centric management and resource allocation software-defined networking as technical realization user behavior based traffic modeling; online charging 8/77

9 Outline Short intro - NetMedia research group Quality of Service (QoS) vs. Quality of Experience (QoE) From QoE modeling to QoE management QoE management with Software-Defined Networking (SDN) Case study: the ICTGEN project Future challenges 9/77

10 Quality of Service (QoS) ITU-T Rec. E.800 (2008) defines QoS as: Totality of characteristics of a telecommunications service that bear on its ability to satisfy stated and implied needs of the user of the service. In practice, QoS has focused on technical performance parameters COST ACROSS, 2nd Int l Summer School May 31st, /77

11 Is QoE simply a re-branding of the term QoS? COST ACROSS, 2nd Int l Summer School May 31st, /77

12 Quality of Experience (QoE) QoE is the degree of delight or annoyance of the user of an application or service. It results from the fulfillment of his or her expectations with respect to the utility and / or enjoyment of the application or service in the light of the user s personality and current state. In the context of communication services, QoE is influenced by service, content, network, device, application, and context of use. - definition taken from Qualinet White paper on Definitions of Quality of Experience, May 2012 QoE focuses on subjective user perception COST ACROSS, 2nd Int l Summer School May 31st, /77

13 What impacts QoE? Long list of influence factors, some difficult (nearly impossible) to measure - go beyond traditional QoS factors Application/service related parameters (encoding, resolution, content type...) Resources (technical system, network resources...) QoE Context (environment, cost, social context, user task) COST ACROSS, 2nd Int l Summer School User (preferences, expectations, demographics, motivation, mood) May 31st, /77

14 QoS vs. QoE Distinguishing factors Scope Focus Method QoS Typically telecom services Performance aspects of physical systems Technology oriented, empirical or simulative measurements QoE Broader domain (not necessarily networkbased) Users assessment of system performance Multi-disciplinary and multi-methodological approach source: Qualinet White Paper on definitions of QoE, 2012 COST ACROSS, 2nd Int l Summer School May 31st, /77

15 Why is understanding QoE important? COST ACROSS, 2nd Int l Summer School May 31st, /77

16 Competitive advantage Increasing competition among stakeholders in ICT domain Future and emerging services Ubiquitous devices, sensors, new and distributed data sources Adaptable in real-time to changing end-user needs Understanding parameters that impact the quality of an application or service as subjectively perceived by the enduser key issue in providing a competitive advantage COST ACROSS, 2nd Int l Summer School May 31st, /77

17 Outline Short intro - NetMedia research group Quality of Service (QoS) vs. Quality of Experience (QoE) From QoE modeling to QoE management QoE management with Software-Defined Networking (SDN) Case study: the ICTGEN project Future challenges 17/77

18 Towards managing the end-user experience Understand fundamental relationships between user perception (QoE) and network performance (QoS) Based on subjective user studies, develop objective QoE models Understanding root cause of unsatisfactory or degraded QoE effective QoE management COST ACROSS, 2nd Int l Summer School May 31st, /77

19 QoE management: 3 basic stages QoE model development MOS Quality 5 Excellent 4 Good 3 Fair 2 Poor 1 Bad Parameter monitoring (e.g., network, context, user feedback) QoE-driven network / service management COST ACROSS, 2nd Int l Summer School May 31st, /77

20 QoE assessment and modeling What are the key QoE influence factors? What do we really need to measure (e.g., in the network, at the client side) to be able to estimate end user QoE? Assessment methodologies: lab, field studies, crowdsourcing tests Subjective methods User studies data used to find models Objective methods QoE prediction based on models and algorithms QoE = f(x, y, z, ) COST ACROSS, 2nd Int l Summer School May 31st, /77

21 Mapping between network performance metrics/traffic features, application-layer KPIs, and QoE sources: M. Varela, L. Skorin-Kapov and T. Ebrahimi. "Quality of Service vs. Quality of Experience", in "Quality of Experience: Advanced Concepts, Applications and Methods", T-Labs Series in Telecommunication Services, S. Möller and A. Raake (eds.), Springer, March 2014, pp T. Hoßfeld, et al. Context monitoring for improved system performance and QoE, under review, extended version of paper "Can Context Monitoring Improve QoE? A Case Study of Video Flash Crowds in the Internet of Services", 3rd IFIP/IEEE International Workshop on Quality of Experience Centric Management (QCMan), Ottawa, Canada, May /77

22 Example QoE modeling studies COST ACROSS, 2nd Int l Summer School May 31st, /77

23 Generic relationships between QoE and QoS In the majority of cases, QoE is dependent on QoS source: M. Fiedler, T. Hossfeld and Phuoc Tran-Gia, A generic quantitative relationship between quality of experience and quality of service, IEEE Network, COST ACROSS, 2nd Int l Summer School May 31st, /77

24 QoE modeling for YouTube Subjective user studies identified video stalling and stalling length as key QoE influence factors Poor network conditions: aviod service interruptions, even at cost of increased initial buffering delays QoE f ( stalling freq., stalling length ) Still under study models considering multiple influence factors (stalling, initial delays, quality levels and switches) source: T. Hossfeld et al. Internet Video Delivery in YouTube: From Traffic Measurements to Quality of Experience, LNCS, vol. 7754, COST ACROSS, 2nd Int l Summer School May 31st, /77

25 Example: Cloud gaming QoE studies Internet user commands video stream Low hardware requirements Instant access Controlled platform High bandwidth and strict delay requirements 25/77

26 Cloud gaming QoE models QoE modeled as function of bitrate and framerate Different models for different game genres source: I. Slivar, L. Skorin-Kapov, M. Sužnjević, "Cloud Gaming QoE Models for Deriving Video Coding Adaptation Strategies," to appear in Proceedings of ACM Multimedia Systems (MMSys'16), Klagenfurt, Austria, 12 pp., May /77

27 Studies on mobile Web browsing QoE source: S. Baraković, L. Skorin-Kapov, "Multidimensional Modelling of Quality of Experience for Mobile Web Browsing", Computers in Human Behavior, Sept. 2015, vol. 50, Elsevier 27/77

28 Objective QoE models COST ACROSS, 2nd Int l Summer School May 31st, /77

29 Objective quality assessment models Parametric and planning models Predict impact of coding and network impairments on multimedia QoE Signal-based Use decoded signal to calculate quality score Signal - based Planning Parametric Bitstream Input Media signal Service and quality design parameters Packet headers Packet header and payload Use case Quality benchmarking Network planning, terminal/application design In-service monitoring (network probes) In-service monitoring (e.g., terminal) COST ACROSS, 2nd Int l Summer School May 31st, /77

30 Example of ITU activities (SG12) Well-known models: E-model (parametric planning model) Recent (10/7712): Recom. P Parametric non-intrusive assessment of audiovisual media streaming quality IP headers Stream info Buffering Parameter extraction (encoding information, decoding, packet information) parameters Video quality estimation Audio quality estimation Audiovisual Video MOS Audiovisual MOS Audio MOS Goal: lightweight models based on parametric or bit stream input enable large-scale QoE assessment in a network COST ACROSS, 2nd Int l Summer School May 31st, /77

31 Towards QoE management COST ACROSS, 2nd Int l Summer School May 31st, /77

32 QoE monitoring approaches Application-layer monitoring (performed at the client or cloud/service provider) Direct application-layer KPI monitoring High accuracy Network-layer monitoring (performed in ISP network) Data collected via multiple probes (radio statistics, flow records, etc.) Methodology needed for estimating application-layer KPIs from network data Traffic encryption has left ISPs in the dark High complexity of problem (different traffic patterns for different clients, device capabilities, access networks, etc.) QoE impairment root cause analysis, control mechanisms COST ACROSS, 2nd Int l Summer School May 31st, /77

33 QoE-based management: common approaches Network management: monitoring and control on core and access network level Application management: adaptation of quality and performance on end-user and application host/cloud level Different QoE optimization and control loops involved (e.g. dynamic application adaptation, network management) how do they interact? source: R. Schatz, M. Fiedler and L. Skorin-Kapov. "QoE-based Network and Application Management". in "Quality of Experience: Advanced Concepts, Applications and Methods", T-Labs Series in Telecommunication Services, Springer, March 2014 Example control loops 33/77

34 QoE-driven optimization strategies Overall goal: optimizing end-user QoE (end-user perspective), while making efficient (current and future) use of network resources and extending/maintaining a satisfied customer base (provider perspective) Different QoE-driven optimization strategies, for example: maximize individual user s QoE, maximize domain-wide average QoE, maximize number of satisfied users, while minimizing network costs, consider fairness among users, etc. COST ACROSS, 2nd Int l Summer School May 31st, /77

35 Selected QoE management topics (1) QoE-driven network resource allocation Core network: policy-based decision making Wireless access networks: radio resource scheduling Core Network signaling, QoE reporting QoE Optimizer optimized bearer allocation Policy control and enforcement Application Server source: Skorin-Kapov, L. et al., Approaches for Utility-Based QoE-Driven Optimization of Network Resource Allocation for Multimedia Services, 2013 COST ACROSS, 2nd Int l Summer School May 31st, /77

36 Selected QoE management topics (2) End-to-end (E2E) QoE in next-generation networks (NGNs) Multiple network domains; QoE includes complete E2E system QoE/QoS reporting QoE management QoE management QoE management collect / send QoS/QoE reports receive/send QoS/QoE reports probe/ adjust transport receive/send QoS/QoE reports probe/ adjust transport receive QoS/QoE reports adjust appl. level cfgs Network Network source: J. Zhang, N. Ansari, On Assuring End-to-End QoE in Next Generation Networks:Challenges and a Possible Solution, IEEE Comm Magazine, COST ACROSS, 2nd Int l Summer School May 31st, /77

37 Potential for integrated/cooperative QoE management schemes Many (potentially new) players involved in E2E service delivery Paradigm shift towards an Internet of Services Effectiveness of QoE management/control mechanisms is potentially limited due to lack of information exchange and cooperation among players End user: QoE MME ISP PCRF CDN Cloud/Service provider S-GW P-GW Measurement data useful for QoE estimation IP and access network data IP-level data Client measurements/ feedback 37/77

38 Information consumer Information exchange between players for improved QoE (1) cloud provider network provider end user current QoE measured at application-level user location to determine close locations current QoS measured at networking level network situation and structure anonymized for overlay adaptation network situation to reduce load network situation for inter-domain networking network situation to adapt/reduce resource consumption, e.g. lower video quality Service Level Agreements between IaaS, PaaS, SaaS application and QoE req. for network traffic management, req. for resource management, e.g.qoe-based scheduling announcement of administrative tasks, e.g. moving server farms, large backups end user network provider cloud provider Information provider source: T. Hoßfeld, R. Schatz, M. Varela, and C. Timmerer, "Challenges of QoE management for cloud applications," IEEE Communications Magazine, vol. 50, no. 4 (2012), pp /77

39 Information exchange between players for improved QoE (2) Offering application providers access to network-level performance information through APIs could provide potential for enhanced network-aware adaptation decisions Offering network providers access to application-level requirements could provide the potential for application-aware and QoE-driven cross-layer resource management The SDN paradigm is a promising solution, in terms of technical realization, for a cooperative QoE management 39/77

40 Outline Short intro - NetMedia research group Quality of Service (QoS) vs. Quality of Experience (QoE) From QoE modeling to QoE management QoE management with Software-Defined Networking (SDN) Case study: the ICTGEN project Future challenges 40/77

41 SDN: a basic principles summary Introduction to SDN given by prof. Andreas Kassler Software-defined networking (SDN): a new network control paradigm that promotes innovation and evolution Main SDN s pillars: separation of network functions - decouple the control and data planes (logical) centralization of control - offer network abstractions and generic services in terms of an SDN controller (SDNC) programmability of network infrastructure - enable applications to demand specific network behavior from SDNC forwarding of flows - decide based on different packet field values 41/77

42 A simplified view on SDN architecture Programmability of network infrastructure Centralization of control Separation of network functions Forwarding of flows 42/77

43 In the focus: multimedia services Examples: Netflix, YouTube, Spotify, Skype, World of Warcraft (WoW), etc. Different characteristics and implementation requirements Complexity: involve different media types (e.g. audio, video, 3D graphics) Multi-user communication: 2 or more remote users in different topological relations Time dependency: common need to establish a real-time communication Data synchronization: inside a single media stream or among different media streams Stringent network QoS demands: minimum throughput, maximum allowed delay, maximum allowed packet loss rate, etc. 43/77

44 Traditional network s limitations Conventional network architectures limited Examples: Internet, other IP-based communication networks Network architectures not designed for: stringent network resource demands (e.g., video streaming services call for large bandwidth shares) differentiation among service types (e.g. so as to offer a specific treatment to traffic belonging to cloud-based gaming) Multimedia services require differentiated packet processing and forwarding Services with diverse QoS demands contend for same resources Allow traffic prioritization and QoS differentiation among distinct service categories 44/77

45 QoE management cycle Application-level monitoring (at the client or service provider) Media bit rate, status of playout buffer, energy consumption, etc. Network-level monitoring (in provider network) Network topology, throughput, delay, packet loss rate, etc. Reporting of critical performance indicators Per end-user (client) and/or per service Application-level management Adapt media codec bit rate, change media resolution, terminate a media flow, etc. Network-level management Reserve bandwidth, prioritize media flows, adjust routing paths, etc. 45/77

46 SDN as a QoE management enabler (1) Application-level monitoring (at the client or service provider) Independent of SDN Network-level monitoring (in provider network) SDNC has a global network view (e.g. on topology and packet loss) Reporting of critical performance indicators SDN architecture offers open (Northbound and Southbound) APIs Application-level management Independent of SDN Network-level management SDN facilitates programmable, per-flow forwarding decisions SDN enables differentiated packet processing and forwarding 46/77

47 SDN as a QoE management enabler (2) Different QoE-driven optimization strategies (including domain-wide decision making) SDNC provides a global insight into network (and its hosts) SDNC allows for enforcement of optimal, domain-wide decisions Integrated/cooperative QoE management (including information exchange between the stakeholders) SDN architecture offers Northbound APIs SDN facilitates programmable network infrastructure (tailored to application needs) 47/77

48 QoE management with SDN efforts Plethora of research results Can generally be categorized according to: targeted (multimedia) service categories Solutions focusing on video services prevail QoE management aspects included Application-level vs. network-level monitoring, application-level vs. networklevel management supported degree of cooperation between service and network providers Recent move towards a more comprehensive solutions ( frameworks ) for cooperative QoE management 48/77

49 Examples of QoE management with SDN results COST ACROSS, 2nd Int l Summer School May 31st, /77

50 QoE-centric network management (1) Increase QoE for YouTube in a multi-application setting by bandwidth (i.e. virtual channel) reservation Enforce traffic classification and prioritization Exploit: network state information; and deep packet inspection (DPI) for detecting service category source: M. Jarschel et al., SDN-based Application-Aware Networking on the Example of YouTube Video Streaming, The 2nd European Workshop on Software Defined Networks (EWSDN 2013), pp /77

51 QoE-centric network management (2) Increase QoE for YouTube over a mobile broadband access by dynamic bandwidth allocation Aggregate resources of multiple access networks into a single communication tunnel Estimate state of media playout buffer based on DPI source: F. Wamser et al., Dynamic Bandwidth Allocation for Multiple Network Connections: Improving User QoE and Network Usage of YouTube in Mobile Broadband, The 2014 ACM SIGCOMM Capacity Sharing Workshop (CSWS), pp /77

52 QoE-centric network management (3) Provide fair QoE for adaptive video streaming in a multi-client setting Employ network-level strategies (e.g. bandwidth reservation, BR) BR designates video flows to pre-defined queues on network interfaces source: G. Cofano et al., Design and Experimental Evaluation of Network-assisted Strategies for HTTP Adaptive Video Streaming, to appear at The 7th ACM Multimedia Systems Conference (MMSys 2016). 52/77

53 QoE-centric network management (4) Improve QoE for adaptive video streaming by re-routing flows An SDN application collects performance indicators and calculates best available paths when video buffering occurs Clients report application-level KPIs (e.g., video start-up latency and buffering rate) SDN controller acquires network-level KPIs (e.g., throughput and jitter) source: H. Nam et al., Towards QoE-aware Video Streaming using SDN, The 2014 IEEE Global Communications Conference (GLOBECOM), pp /77

54 QoE-centric network management (5) Internet Service quality Assessment and Automatic Reaction (ISAAR) QoE Framework for mobile networks (e.g. 3G, LTE) Focuses on traffic classification and different access network specific mechanisms Includes 3 entities: QoE Monitoring - estimates QoE in the network based on measured QoS parameters (e.g., estimates video buffer level and freezes) QoE Policy and Rules - classifies packets into service classes based on, e.g., buffer level, so as to direct different packet handling QoE Enforcement - applies appropriate mechanism(s) for different service classes (e.g., set up virtual tunnel, adjust packet scheduling) source: M. Eckert and T. M. Knoll, "QoE Management Framework for Internet Services in SDN-Enabled Mobile Networks," Software Defined Mobile Networks (SDMN): Beyond LTE Network Architecture, pp /77

55 Cooperative QoE management (1) QoE Fairness Framework (QFF) for adaptive video streaming Fairly maximize amount of network resources for competing heterogeneous video clients Monitor network bandwidth; report end-user device capabilities; collect video streaming metainformation; calculate appropriate video bitrates for all clients source: P. Georgopoulos, et al., Towards Network-wide QoE Fairness using Openflow-assisted Adaptive Video Streaming, The 2013 ACM SIGCOMM Workshop on Future Human-centric Multimedia Networking (FhMN 2013), pp /77

56 Cooperative QoE management (2) OpenFlow-based framework for adaptive video streaming SDNC prioritizes specific video segments in the network and instructs the associated video client to adapt media quality Reporting of application-level KPIs (e.g., client buffer status and video segments length) Periodic retrieval of traffic statistics from network elements source: S. Petrangeli et al., Network-based Dynamic Prioritization of HTTP Adaptive Streams to Avoid Video Freezes, The 2015 IFIP/IEEE Int l Symposium on Integrated Network Management (IM), pp /77

57 Cooperative QoE management (3) Collaboration between service (Over-the-Top, OTT) providers and mobile network operators to enhance end-user QoE QoE-Service (an SDN application) steers traffic management source: E. Liotou et al., "An SDN QoE-service for dynamically enhancing the performance of OTT applications," The 7th International Workshop on Quality of Multimedia Experience (QoMEX 2015), pp /77

58 Outline Short intro - NetMedia research group Quality of Service (QoS) vs. Quality of Experience (QoE) From QoE modeling to QoE management QoE management with Software-Defined Networking (SDN) Case study: the ICTGEN project Future challenges 58/77

59 The ICTGEN project Information and communication technology for generic and energyefficient communication solutions with application in e-/m-health (ICTGEN) Project co-financed by the European Union from the Regional Development Fund Project beneficiary: University of Zagreb, FER Project leader: prof. Maja Matijašević Project partner: Ericsson Nikola Tesla, Zagreb, Croatia Overall project worth: ~ ,00 EUR Running time: mid October, mid March, 2016 ICTGEN 59/77

60 Project objectives Design a solution for integration and interoperability of Electronic Health Record with the imaging/radiology e-health and m-health systems Develop generic components of the SDN infrastructure for the delivery of ICT services with optimal user experience Optimize energy efficiency of software-defined networks based on model and measurements gathered by using sensor network from the user environment Build laboratory environment and integrated demo solution for conducting functional validation Case studies: e-health/m-health and IPTV/video on demand (VoD) services 60/77

61 Research in the focus: QoE-centric flow routing Goal: improve the routing process in IP-based communication networks for ICT (multimedia) services by considering QoE Conventional IP networks: media flows typically follow the same path between a source host-destination host pair Might not be the optimal path with respect to multimedia service demands on network resources and to network resource limitations Taking multimedia service/media flow category and end-users expectations on QoE into account: calculate the best available network path for each media flow in order to (fairly) maximize end-user QoE Exploit QoE models to estimate a measure of QoE Going beyond network-related QoS parameters to include other QoE influence factors as well QoE-centric flow routing 61/77

62 QoE-centric routing: VoD illustration Shortest path routing QoE-flow routing Possible packet loss No packet loss 62/77

63 QoE-centric routing: image retrieval illustration Shortest path routing QoE-flow routing Slower retrieval Faster retrieval 63/77

64 QoE-centric flow routing design and evaluation COST ACROSS, 2nd Int l Summer School May 31st, /77

65 QoE-centric flow routing model Cooperation between service and network providers 65/77

66 QoE-centric routing: optimization model Objective: maximize aggregated QoE across all end-users and multimedia sessions in a network domain Perform centralized, multi-user path optimization Calculate the best path (in terms of impact on QoE) for each flow Consider distinct multimedia service categories VoIP-based conversations, high-definition IPTV/VoD sessions, (non real-time) file transfers Use different QoE models for estimating a QoE measure The problem is formulated as a mixed integer linear program source: O. Dobrijevic et al., Q-POINT: QoE-Driven Path Optimization Model for Multimedia Services, The 12th Int l Conference on Wired & Wireless Internet Communications (WWIC 2014), pp /77

67 QoE-centric routing: heuristic algorithm QoE models involve different influence factors (KPIs) multiple constraints for the path calculation problem Resulting routing problem is NP-complete the need to design a heuristic algorithm for QoE-centric flow routing in an SDN network Optimization method chosen: ant colony optimization (ACO) Well-known and widely applied meta-heuristic method Suitable for calculating (near-)optimal paths in a weighted graph ACO simulates the way real-life ants look for food Ants initially move on a random basis until finding a food source After finding a path to the food source ( path destination ), ants move back to their colony ( path source ) and leave a pheromone trail After a while, the optimal (e.g. shortest) path is more likely to be followed by other ants as well 67/77

68 QoE-centric routing: heuristic design SDNC simulates ACO in a weighted graph for each new flow The weighted graph corresponds to topology and measured KPIs of a real SDN network For each media flow category a different ant type is simulated source: O. Dobrijevic et al., Ant Colony Optimization for QoE-centric Flow Routing in Software-defined Networks, The 11th Int l Conference on Network and Service Management (CNSM 2015), pp /77

69 Laboratory environment: functional elements 69/77

70 Laboratory environment: infrastructure overview SDNC OpenDaylight with a Java heuristic algorithm implementation 70/77

71 Examples of research equipment Hardware network emulator Hardware network tap Network rack with HP SDN switches 71/77

72 QoE-centric routing: evaluation methodology Prototype ICT (multimedia) services: e-health - medical image retrieval & doctor consultation m-health - nutrition tracking VoD Emulate different QoS parameters in the laboratory network Delay, packet loss rate Objective and subjective testing Subjective testing: compare QoE obtained with shortest path (SP) routing and with QoE-centric flow routing 72/77

73 QoE-centric routing: a glimpse of evaluation results Subjective testing is based on the Comparison Category Rating (CCR) scale Index Category -3 Much worse -2 Worse -1 Slightly worse 0 About the same +1 Slightly better +2 Better +3 Much better Effects of emulated network delay: QoE-centric flow routing outperforms SP routing 73/77

74 Outline Short intro - NetMedia research group Quality of Service (QoS) vs. Quality of Experience (QoE) From QoE modeling to QoE management QoE management with Software-Defined Networking (SDN) Case study: the ICTGEN project Future challenges 74/77

75 Questions and challenges How can new QoE models be exploited (in a practical sense) in the context of QoE management with SDN schemes? Many models are still missing (e.g., interactive cloud-based applications, adaptive video streaing to some extent) To what extent can cooperative business models involving multiple players (e.g., cloud/service providers, (mobile) network operators, content providers) achieve more efficient management of network/system resources, while enhancing customer QoE? What are stakeholder incentives? What (novel?, SDN-based?) solutions are needed for coordination and information exchange among actors involved in the service delivery chain in order to provide channels for QoE control/improvement? 75/77

76 Instead of a conclusion Feel free to contact us for more information, or just to... visit 76/77

77 THANK YOU! COST ACROSS, 2nd Int l Summer School May 31st, /77