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Towards Unified Management A Common Approach for Telecommunication and Enterprise Usage

Routing Knowledge = Metadata + node id. Scripting Language. High-level Scripting Language: writing distributed jobs. Generic Application Services. Distributed Execution Engine. Distributed execution, fault- tolerance, job scheduling. Cached Data. Business-Enabled Services.

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Towards Unified Management A Common Approach for Telecommunication and Enterprise Usage

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  1. Routing Knowledge = Metadata + node id Scripting Language High-level Scripting Language: writing distributed jobs Generic Application Services Distributed Execution Engine Distributed execution, fault- tolerance, job scheduling Cached Data Business-Enabled Services Composition Services Distributed File System Orchestration Services Security Services External Portal Services Management Services Naming, storage Knowledge Management and Query Services Towards Unified Management A Common Approach for Telecommunication and Enterprise Usage Sung-Su Kim, Jae Yoon Chung, Byungchul Park, John Strassner, and James W. Hong Server Server Server Server AE Component Services Physical resources Core Framework Services To organize the routing table and cache store List of routing knowledge Introduction and Motivation Autonomic Management Element of The FI • Functions of Autonomic Management Element • Management of Emerging Networks and Services • Next generation networks and the future Internet are gaining increasing importance • New era of cloud computing expands the enterprise • Current Network Management • Different views between enterprise and telecommunication provider • We Need Unified Management for the Future Internet and for Data Center Networks (DCNs) DCN Measurement • Understanding Data Center’s Behavior is Indispensable for Managing Large Clusters Management Challenges • Knowledge Representation • Equating different syntaxes and semantics describing management data • Attaching context to management data through inference • Translating semantics between different constituencies • QoS and QoE Management for End User • Accurate and fast traffic classification method is needed to provide personalized services • Modeling of QoS and QoE for dynamic code generation and reconfiguration • Monitoring tool for Various Purpose • Monitoring of Data Center Network (DCN) • Conclusions and Applicability for Management • Autonomic management of networks and DCNs New Network Management Architecture Traffic classification for FI applications • Traffic Classification by Similarity Analysis • Compared different metrics • Jaccard Similarity: • Cosine Similarity: • The Gaussian Radial Basis Function: • Each provides improved accuracy with low complexity QoE Modeling Based on DEN-ng • Definition of Quality of Experience (QoE): The quality perceived by end user Discussion and Future Research • A New Architecture is Need to Manage FI and DCNs • We will extend FOCALE, which is an autonomic distributed management architecture • Uses models and ontologies to learn and reason about facts discovered to make context-aware decisions • Applies Beyond the Network to, for Example, DCN • Both Require Better Understanding of Data and Patterns of Data • Research on traffic classification to manage QoS and QoE of end-user • Research on future management node architecture, protocols, and semantic interoperability • QoETrafficAddingService : • Introduction of additional traffic to an existing session (e.g., a FEC encoder ) • QoETrafficModifyingService: • Modification of the actual payload of packets (e.g., a video transcoder) • QoETrafficStoreAndForwardService: • Alteration of future sessions based on information about the current session (e.g., a caching mechanism)

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