Monitoring and response for real-time voice messages transmitted using wi-fi within net-centric enterprise systems

Abstract

Real-time voice communications capabilities over wireless medium, using the , have become a potential bottleneck in emerging net-centric enterprise systems used by the DoD and Federal Government agencies. Depending on the priority and precedence of a particular message, mission success may depend on achieving optimal performance with respect to transmission, reception, and interpretation of the message. This paper explores successful interpretation of Wi-Fi messages from the end user perspective as defined through the metric Quality of Experience (QoE). QoE represents the perception of quality experienced by end users of a real-time system. The specific challenge examined herein is that of communicating real-time events using Wi-Fi running within netcentric enterprise systems. In this setting, time-sensitive events may require immediate problem determination and resolution. The paper also introduces a new approach for aggregating WiFi messages across the enterprise, thereby enabling timely and effective interpretation and response to real-time events. Results for a disaster response scenario are presented that combine analysis and simulation measurements from a 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, such as supporting real-time information sharing over Wi-Fi within netcentric enterprise systems.This paper also provides recommendations for configuration of Wi-Fi QoS mechanisms to support priority and precedence in order to ensure timely response and mission critical communications from local to global operation centers.

Monitoring and management approach for cyber security events over complex systems

“…When the CS event occurs, the EMMRA CS agent notifies the relevant operations center (Ops Center) that then uses its CA node to analyze the event and determine the proper response. Table 2 describes a possible observation and response scenario to resolve the threat and maintain the end user quality of service [12].…”