Randomized Load Balancing under Loosely Correlated State Information in Fog Computing

Fog computing infrastructures must support increasingly complex applications where a large number of sensors send data to intermediate fog nodes for processing. As the load in such applications (as in the case of a smart cities scenario) is subject to significant fluctuations both over time and space, load balancing is a fundamental task. In this paper we study a fully distributed algorithm for load balancing based on random probing of the neighbors' status. A qualifying point of our study is considering the impact of delay during the probe phase and analyzing the impact of stale load information. We propose a theoretical model for the loss of correlation between actual load on a node and stale information arriving to the neighbors. Furthermore, we analyze through simulation the performance of the proposed algorithm considering a wide set of parameters and comparing it with an approach from the literature based on random walks. Our analysis points out under which conditions the proposed algorithm can outperform the alternatives

Power analysis for stepped wedge trials with delayed treatment initiation and longitudinal measurements

Stepped wedge trials (SWT) is a special type of crossover cluster randomized trials (CRT) in which clusters are randomized to initiate treatment at different points in time. This design is proposed for a future trial that aims to study the effectiveness of a population health management (PHM) intervention based on Electronic Health Record (EHR) among patients with CKD. This study will collect multi-level data with longitudinal kidney function measurements from patients nested within practices. There are two challenges in powering this trial: (1) existing literature to power SWTs focus on cross-sectional design and single level of clustering; and (2) patients enrolled in the EHR-PHM trial may experience delayed treatment initiation in which they receive treatment later than expected. The effect of delayed treatment initiation to power has not been discussed in the current literature. The goal of this thesis is to develop a simulation-based method for power and sample size analysis for SWTs with longitudinal outcomes and delayed treatment initiation. We assumed random effects mixed models to account for correlation introduced by multiple levels of clustering. Simulation parameters are acquired from preliminary EHR data and verified by nephrologists. We determined the power and sample size requirements with varying levels of delayed treatment initiation. We have found that delayed treatment initiation results in slight loss of power. The impact of varying levels of subject delay for a fixed time delay is similar to the impact of varying levels of time delay for a fixed subject delay. Simulation-based power calculation is a flexible and practical tool in designing SWT with longitudinal measurements. Public health significance: In clinical trials, the simulation-based power calculation method provides a practical and flexible approach for power calculation and sample size determination in designing SWTs with longitudinal outcomes while incorporating the effect of delayed treatment initiation. This method will be useful in the design of the EHR-PHM trial which could potentially improve care for and outcomes of high risk CKD patients

FPGA-SPICE: A Simulation-Based Architecture Evaluation Framework for FPGAs

In this paper, we developed a simulation-based architecture evaluation framework for field-programmable gate arrays (FPGAs), called FPGA-SPICE, which enables automatic layout-level estimation and electrical simulations of FPGA architectures. FPGA-SPICE can automatically generate Verilog and SPICE netlists based on realistic FPGA configurations and a high-level eTtensible Markup Language-based FPGA architectural description language. The outputted Verilog netlists can be used to generate layouts of full FPGA fabrics through a semicustom design flow. SPICE simulation decks can be generated at three levels of complexity, namely, full-chip-level, grid-level, and component-level, providing different tradeoff between accuracy and simulation time. In order to enable such level of analysis, we presented two SPICE netlist partitioning techniques: loads extraction and parasitic net activity estimation. Electrical simulations showed that averaged over the selected benchmarks, the grid-/component-level approach can achieve 6.1x/7.5x execution speed-up with 9.9%/8.3% accuracy loss, respectively, compared to the full-chip level simulation. FPGA-SPICE was showcased through three different case studies: 1) an area breakdown analysis for static random access memory-based FPGAs, showing that configuration memories are a dominant factor; 2) a power breakdown comparison to analytical models, analyzing the source of accuracy loss; and 3) a robustness evaluation against process corners, studying their impact on energy consumption of full FPGA fabrics

Statistical Challenges and Methods for Missing and Imbalanced Data

Missing data remains a prevalent issue in every area of research. The impact of missing data, if not carefully handled, can be detrimental to any statistical analysis. Some statistical challenges associated with missing data include, loss of information, reduced statistical power and non-generalizability of findings in a study. It is therefore crucial that researchers pay close and particular attention when dealing with missing data. This multi-paper dissertation provides insight into missing data across different fields of study and addresses some of the above mentioned challenges of missing data through simulation studies and application to real datasets. The first paper of this dissertation addresses the dropout phenomenon in single-cell RNA (scRNA) sequencing through a comparative analyses of some existing scRNA sequencing techniques. The second paper of this work focuses on using simulation studies to assess whether it is appropriate to address the issue of non-detects in data using a traditional substitution approach, imputation, or a non-imputation based approach. The final paper of this dissertation presents an efficient strategy to address the issue of imbalance in data at any degree (whether moderate or highly imbalanced) by combining random undersampling with different weighting strategies. We conclude generally, based on findings from this dissertation that, missingness is not always lack of information but interestingness that needs to investigated

Secure Massive MIMO Communication with Low-resolution DACs

In this paper, we investigate secure transmission in a massive multiple-input multiple-output (MIMO) system adopting low-resolution digital-to-analog converters (DACs). Artificial noise (AN) is deliberately transmitted simultaneously with the confidential signals to degrade the eavesdropper's channel quality. By applying the Bussgang theorem, a DAC quantization model is developed which facilitates the analysis of the asymptotic achievable secrecy rate. Interestingly, for a fixed power allocation factor $\phi$, low-resolution DACs typically result in a secrecy rate loss, but in certain cases they provide superior performance, e.g., at low signal-to-noise ratio (SNR). Specifically, we derive a closed-form SNR threshold which determines whether low-resolution or high-resolution DACs are preferable for improving the secrecy rate. Furthermore, a closed-form expression for the optimal $\phi$ is derived. With AN generated in the null-space of the user channel and the optimal $\phi$, low-resolution DACs inevitably cause secrecy rate loss. On the other hand, for random AN with the optimal $\phi$, the secrecy rate is hardly affected by the DAC resolution because the negative impact of the quantization noise can be compensated for by reducing the AN power. All the derived analytical results are verified by numerical simulations.Comment: 14 pages, 10 figure

Simulation of How Jack Pine Budworm (Lepidoptera: Tortricidae) Affects Economic Returns From Jack Pine Timber Production in Michigan

The impact of jack pine budworm on economic returns from jack pine timber production in Lower Michigan and management actions that might be taken to reduce this impact were evaluated with a simulation model. Results indicate that current jack pine rotation ages arc excessive and should be reduced. Insecticide application is not a viable strategy for reducing jack pine budworm impact