A methodology for the design of application-specific cyber-physical social sensing co-simulators

Cyber-Physical Social Sensing (CPSS) is a new trend in the context of pervasive sensing. In these new systems, various domains coexist in time, evolve together and influence each other. Thus, application-specific tools are necessary for specifying and validating designs and simulating systems. However, nowadays, different tools are employed to simulate each domain independently. Mainly, the cause of the lack of co-simulation instruments to simulate all domains together is the extreme difficulty of combining and synchronizing various tools. In order to reduce that difficulty, an adequate architecture for the final co-simulator must be selected. Therefore, in this paper the authors investigate and propose a methodology for the design of CPSS co-simulation tools. The paper describes the four steps that software architects should follow in order to design the most adequate co-simulator for a certain application, considering the final users’ needs and requirements and various additional factors such as the development team’s experience. Moreover, the first practical use case of the proposed methodology is provided. An experimental validation is also included in order to evaluate the performing of the proposed co-simulator and to determine the correctness of the proposal

SIMULATION OF MANYCORE ARCHITECTURES ON MULTICORE HOSTS

Computer architects heavily rely on software simulation to evaluate new and existing processor designs. As target designs become more complex, a growing gap has emerged between single-threaded simulator performance and simulation requirements. Even though modern machines feature multiple cores, most host cores are typically unused or underutilized by state-of-the-art simulators. Parallel simulators are inherently limited by their need to synchronize threads for correctness. In my thesis, I study accurate and efficient parallelization techniques for architecture simulation. This thesis contains several contributions. First, I study synchronization between simulator threads simulating homogeneous hardware structures such as cores or network tiles. Based on this study, I introduce a new synchronization policy, weighted-tuple synchronization, and show that it provides a better performance-accuracy trade-off compared to synchronization currently used by state-of-the-art parallel simulators. Next, I study synchronization between separate simulators responsible for modeling heterogeneous components and introduce reciprocal abstraction. Reciprocal abstraction allows asynchronous simulators to exchange information at runtime for more accurate event timing. Lastly, the reciprocal abstraction model relaxes communication latency restrictions and synchronization requirements; I show how relaxed synchronization requirements allows for coprocessor acceleration

Modeling Occupant Behavior, Systems Life Cycle Performance, and Energy Consumption Nexus in Buildings Using Multi-Method Distributed Simulation

Buildings consume 40% of the total energy produced in the United States (US), making this sector an opportune choice for devising strategies aimed at reducing energy consumption. Even though various tools and simulation frameworks have been developed in prior work for evaluating, monitoring, and regulating the energy use in buildings, their deployment has primarily been in the form of standalone applications that consider limited aspects of the entire system. For example, energy simulation programs provided by the US Department of Energy such as EnergyPlus and eQuest calculate the annual operating energy in a building by assuming static parameters for occupancy schedules and performance of building systems. However, this approach does not consider the effects of occupants’ dynamic energy use behavior or the effects of material and systems degradation over the life cycle of a building, among other influencing factors. Therefore, the primary objective of this dissertation is to create a simulation framework that is capable of modeling and analyzing a building’s energy consumption with improved accuracy by considering dynamic influencing factors through an interdependent analysis. A primary contribution of this research effort is the Lightweight and Adaptive Building Simulation (LABS) framework, an innovative distributed computing environment that can conduct a life cycle based building energy simulation by incorporating several dynamic energy-influencing factors in unison. The LABS framework integrates all the energy requirements occurring in a building’s life cycle such as embodied, operational and end of life energy demands, thereby visualizing the inter-dependency among these energy requirements and all dynamic influencers affecting a building’s life cycle energy profile. The effectiveness of the LABS framework was evaluated and demonstrated through several case-study analyses. A system dynamics based energy simulation analysis performed on a case study building located in Chicago has shown that energy savings of up to 20.5% are possible by adopting effective operational and maintenance schemes in a building’s entire life cycle. Similarly, it has also been demonstrated that influencing occupant behavioral choices through energy based interventions, can achieve energy savings of up to 13% per month. These two observations highlight the importance of analyzing the effects of dynamic factors in a building’s life cycle and the capabilities of the LABS framework in analyzing and quantifying the interdependent effects of such factors during a building’s life cycle. By allowing coupled effects of multiple energy-influencing processes to be concurrently explored, this research opens future possibilities for the performance-based assessment of building energy systems.PHDCivil EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/138685/1/albertth_1.pd

Solving the year 2000 dilemma

https://egrove.olemiss.edu/aicpa_guides/1551/thumbnail.jp

Solving the year 2000 dilemma

https://egrove.olemiss.edu/aicpa_guides/1552/thumbnail.jp

A Neural Network-Based Situational Awareness Approach for Emergency Response

publishedVersio

An architectural comparison of contemporary apporaches and products for integrating heterogeneous information systems

Includes bibliographical references.principal investigator: Amar Gupta, technical advisor: Stuart E. Madnick, researchers: Teresa Wingfield and Christopher Poulsen