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Faced with intense competition, network service providers, supported by their respective network operations centers (NOCs), must ensure the best possible quality of service (QoS) and corresponding quality of experience (QoE) for end-users or face the loss of business. QoE represents the perception of quality experienced by end-users of a real-time system, such as VoIP. The QoE challenge becomes significant when real-time applications running on net-centric enterprise systems, driven by methodologies such as service oriented architecture (SOA), encounter issues that require time-sensitive problem determination and resolution. Optimizing end-user QoE becomes daunting as system complexity grows to span multiple applications and functions across different administrative areas of responsibility. Available tools fall short in their support of enterprise QoE monitoring because they examine only portions of the available data within their respective purview resulting in a fractionalized picture of the true state of the enterprise system. This paper addresses the above limitation by presenting an approach for aggregating observed real-time applications data across the enterprise, thereby permitting timely and effective interpretation and response to real-time application events. This approach uses a proven framework, reference architecture, and QoE metrics categories to produce simulation results for the collection, correlation and analysis of application information on net-centric enterprise systems. Results are presented for several VoIP scenarios including a denial of service (DoS) event that causes noticeable applications delay. These results represent measurements for over one billion packets derived from a large- scale simulation running on the UK national supercomputing service, HECToR. The paper concludes by highlighting key benefits to the service provider's business from using this approach.