Paul C. Hershey

Monitoring real-time applications events in net-centric enterprise systems to ensure high quality of experience

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 providers business from using this approach.

Methodology for monitoring and measurement of complex broadband networks

A robustly engineered monitoring and measurement capability provides comprehensive and timely performance information that allows broadband network operators and service providers to observe and proactively respond to events that occur during deployment and operation of their respective networks. As network complexity increases, so do the requirements for monitoring and measurement to ensure the high-quality service to internal and external customers. A methodology for monitoring and measurement of complex broadband networks is presented. This methodology includes a framework and reference architecture, essential metrics categories to refine and focus the collection of information and extensions to support net-centric enterprise systems driven by service-oriented architecture (SOA). Examples of the application of the methodology to complex broadband networks are provided along with suggestions for further work.

Systems engineering approach for event monitoring and analysis in high speed enterprise communications systems

Disparate customer support centers in an enterprise system apply different monitoring and analysis tools while attempting to ensure quality of service for the end-user. These tools provide inconsistent metrics that make problem resolution inefficient and reactive rather than proactive and effective. A systems engineering approach is proposed that considers enterprise monitoring and analysis in high-speed enterprise communications systems done by support centers via collaboration rather than in isolation. This paper presents graphical representations of various aspects of the monitoring and analysis approach that include architectural, operational, systems-level, and technical views. For each of these views we identify the applicable system components and the integration of these components that enable solution of system-wide problems.

A policy-based approach to automated data reduction for intelligence, surveillance, and reconnaissance systems

Department of Defense (DoD) intelligence, surveillance, and reconnaissance (ISR) assets; including manned and unmanned airborne, space-borne, maritime, and terrestrial systems; play critical roles in support of current and future military operations. However, military services and defense agencies face an ever growing challenge of effectively processing, exploiting, and disseminating ISR data from multiple, diverse senor platforms for end-users who collaborate and share information within a net-centric enterprise environment. Adding to the physical limitations of transport and infrastructure are personnel shortages with respect to the number of operator and analytical staff possessing the required skill sets to effectively exploit collected ISR information. This shortage raises the risk that important information may not be available to war fighters in a timely manner that assures mission success. The Multifactor Analytics Information Engine (MAIE) directly addresses the aforementioned issues by reducing the flood of sensor data to only actionable information that is directly applicable to the mission-at-hand. MAIE focuses on target discovery, communication capacity management, and automation techniques that enable ISR system operators and analysts to derive the knowledge they need to meet end-user mission requirements. A primary feature of the MAIE approach is the use of on-board processing, close to the sensor on the platform where the data originates. This processing includes screening and then compressing the data using established algorithms before transmission to the operations center for dissemination and exploitation. A major contribution of MAIE is its novel approach for automatically selecting these algorithms based on premeditated mission plans and dynamically occurring mission events. We implement a policy-based management system driven by a rules-based, event-correlation engine to select the most appropriate algorithms to reduce sensor data to only mission-required exploitation products. By doing so, MAIE greatly improves productivity of operators and analysts to enable them to meet end-user time-critical needs while using fewer resources.

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

Real-time voice communications capabilities over wireless medium, using the Wi-Fi standard IEEE 802.11, 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 net-centric enterprise systems. In this setting, time-sensitive events may require immediate problem determination and resolution. The paper also introduces a new approach for aggregating Wi-Fi 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 providers business from using this approach, such as supporting real-time information sharing over Wi-Fi within net-centric 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.

End-to-End Applications and Algorithm Integration (E2A2I) Method and Architecture

DoD manned and unmanned air systems require multiple mission phases, each with unique procedures, algorithms and checklists that are implemented through a variety of hardware and software mechanisms, all within the same mission. This approach is not efficient with respect to mission processing, staffing, and training. The End-to-End Applications and Algorithm Integration (E2A2I) Method and Architecture addresses this issue using a checklist application that receives a complete mission checklist for all mission phases (e.g., pre-mission, launch and recovery, on-mission, post-mission, and maintenance) from a data broker enforcement entity that has access to a data store. This data store contains many checklists in support of multiple diverse missions. The E2A2I application automatically executes the checklists, invoking other mission applications in order of their mission usage. The E2A2I application runs on a mobile computing device with software services that invoke one mobile application from another so that the same applications can be used in multiple mission phases and for multiple missions.

Monitoring and management approach for cyber security events over complex systems

DoD, agency and commercial operations centers that manage complex enterprise systems face the problem of protecting both the systems and the data they carry against cyber attacks while, at the same time, providing high quality end-to-end services that meet service level agreements and help ensure mission success. Presently there exists no comprehensive tool suite that encompasses the procedures, methods, and policies to provide an effective enterprise cyber security monitoring and management solution. This paper provides a basis from which to fill that void by introducing a new framework for monitoring and managing cyber security events in complex systems. We demonstrate application of this framework using several realistic scenarios.

Systems of Systems approach for monitoring and response across net-centric enterprise systems

As the communications systems of the Department of Defense (DoD), academia, and the commercial world transform from autonomous entities into network centric enterprise systems, service providers and operators struggle to monitor and mange these systems in order to meet customer service commitments. These once independent networks now comprise interdependent systems that integrate into a higher order system resulting in growing complexity. Management of this emerging System of Systems (SoS) requires the capability to monitor and respond to all relevant data, called information, with respect to the service of interest within the required time frame to satisfy customer needs. This paper presents a SoS approach for monitoring and response across net-centric enterprise systems and proposes an implementation for this approach.