Introduction and Motivation

1. Service Provider SLA Consumer Role Calculated QoE QoE Control QoS Mechanism A Quality of Experience Model and an Ontology for High Quality Multimedia Services Arum Kwon1, Joon-Myung Kang1, Sin-seok Seo1, Sung-Su Kim1, Jae Yoon Chung1, John Strassner2, and James Won-Ki Hong2 1 Dept. of Computer Science and Engineering, 2 Division of IT Convergence Engineering, Pohang University of Science and Technology (POSTECH), Korea QoE Control Loop Model Introduction and Motivation • Evolution of the Network Based Services • Advanced multimedia services (e.g., IPTV, VoD, VoIP) • Different services have conflicting resource demands on a shared infrastructure • Quality of Experience (QoE) • A subjective measure of a customer’s experiences for services • Relate objective network data to customer experience to improve QoE • Use a control loop to manage services based on the measured QoE Network • QoE Control Loop • Many types of changes to the service can be managed by a single control loop • Subjective, objective, and contractual changes are captured as QoE data • Our model manages QoE data changes using QoS mechanisms • Our control loop self-regulates • QoEServiceFeedback • Triggers the change of network configuration according to management policy when any SLA data changes Research Goal • Design of a QoE model based on the DEN-ng model • Define appropriate QoE metrics and their relationship with performance indicators and consumers • Present a control loop to optimize the quality of services based on the measured QoE among networks, end-users and service providers Network Service for QoE DEN-ng Model Performance Indicators Ontology and SWRL rules • Key Performance Indicator (KPI): • Quantifiable measurements that reflect the critical successful or unsuccessful factors of a particular resource or service • Key Quality Indicator (KQI): • An indicator for a specific performance aspect of the product or product components • Customer Quality Indicator (CQI): • Quality indicators that are experienced and perceived by customers PerformanceInfo SLA influence influence influence influence influence influence KQI KPI NP hasThreshold hasPerformanceInfo PerformanceInfo Threshold isViolated hasOperator ProductKQI ServiceKQI ResourceKPI STBNP InfrastructureNP True or False Operator ResourceKQI ProductKPI ServiceKPI Aggregation SwitchNP • We designed an ontology for detecting SLA changes by relating MIB data to SLA data • Service Level Agreement (SLA): high-level business descriptions • Management Information Base (MIB): low-level network data • Semantic Web Rule Language (SWRL) for • Computing SLA changes from lower level performance indicators (Network Performance, KPI, and KQI) • Mapping between different performance indicators • Calculating performance indicators • Mapping between network data, KPIs, KQIs, and SLAs • SLAViolationCheckEqTrue • SLA(?sla) ∧ hasPerformanceInfo(?sla, ?indicator) ∧ hasThreshold(?sla, ?threshold) ∧ hasOperator(?sla, ?operator) ∧ hasValue(?indicator, ?value) ∧ swrlb:equal(?operator, "eq") ∧ swrlb:notEqual(?value, ?threshold) → isViolated(?sla, "true") QoE Metrics Model • Define a new Customer Role Quality Indicator (CRQI) • Roles abstract people and organizations • ConsumerRole abstracts different responsibilities and functionality that a customer has • CRQI is a measurement of a specific aspect of the quality of a product, service, or resource as perceived by a particular customer • CRQI captures the semantics between a given ConsumerRoleand a particular context as represented by QoE data Future Research • Create an Autonomic SLA management system • Define semantics to create a knowledge continuum to relate diverse business, management, and operational data to each other • Validate using a simulator and/or a network testbed