Browsing by Author "Singh, Hermanpreet"

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    Controlling Scalability in Distributed Virtual Environments
    Singh, Hermanpreet (Virginia Tech, 2013-05-01)
    A Distributed Virtual Environment (DVE) system provides a shared virtual environment where physically separated users can interact and collaborate over a computer network. More simultaneous DVE users could result in intolerable system performance degradation. We address the three major challenges to improve DVE scalability: effective DVE system performance measurement, understanding the controlling factors of system performance/quality and determining the consequences of DVE system changes. We propose a DVE Scalability Engineering (DSE) process that addresses these three major challenges for DVE design. DSE allow us to identify, evaluate, and leverage trade-offs among DVE resources, the DVE software, and the virtual environment. DSE has three stages. First, we show how to simulate different numbers and types of users on DVE resources. Collected user study data is used to identify representative user types. Second, we describe a modeling method to discover the major trade-offs between quality of service and DVE resource usage. The method makes use of a new instrumentation tool called ppt. ppt collects atomic blocks of developer-selected instrumentation at high rates and saves it for offline analysis. Finally, we integrate our load simulation and modeling method into a single process to explore the effects of changes in DVE resources. We use the simple Asteroids DVE as a minimal case study to describe the DSE process. The larger and commercial Torque and Quake III DVE systems provide realistic case studies and demonstrate DSE usage. The Torque case study shows the impact of many users on a DVE system. We apply the DSE process to significantly enhance the Quality of Experience given the available DVE resources. The Quake III case study shows how to identify the DVE network needs and evaluate network characteristics when using a mobile phone platform. We analyze the trade-offs between power consumption and quality of service. The case studies demonstrate the applicability of DSE for discovering and leveraging tradeoffs between Quality of Experience and DVE resource usage. Each of the three stages can be used individually to improve DVE performance. The DSE process enables fast and effective DVE performance improvement.
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    Introspective C++
    Singh, Hermanpreet (Virginia Tech, 2004-08-20)
    Introspection has become a significant language feature to enable new component technologies. It enables such capabilities as runtime component discovery, new levels of component flexibility and change tolerance, dynamic reconfiguration and system self healing. Three levels of introspection are discussed: simple type identification, structural introspection, and behavioral introspection The C++ programming language offers type identification, but neither structural or behavioral introspection. Through its use and combination of several language features, C++ has provided a flexible system for achieving some of the features of introspection without explicitly providing it. Features such as templates, operator overloading, polymorphism, and multiple inheritance have allowed software systems in C++ to build flexible components that tolerate change and support dynamic reconfiguration and self healing. The template system in particular has recently been shown to be more capable than expected, being Turing complete in its own right. Despite their existing capabilities, the language features have their limits and would benefit from an introspective mechanism. Unlike traditional introspective systems that execute solely at run-time, Introspective C++ has chosen a compile-time approach that tightly integrates with the template mechanism. This approach enables interaction with the other language mechanisms during the compilation, enabling the resolution of many introspective questions before the compiled program is ever run. Furthermore, the mechanism can serve as a base for developing run-time introspective systems.