Computer Engineering Commons^™

Blockchain Based Communication Architectures With Applications To Private Security Networks, Ashley N. Mayle

Computer Science ETDs

Existing communication protocols in security networks are highly centralized. While this naively makes the controls easier to physically secure, external actors require fewer resources to disrupt the system because there are fewer points in the system can be interrupted without the entire system failing. We present a solution to this problem using a proof-of-work-based blockchain implementation built on MultiChain. We construct a test-bed network containing visual imagers and microwave sensor information. These data types are ubiquitous in perimeter security systems and allow a realistic representation of a real-world network architecture. The cameras in this system use an object detection algorithm …

Criticality Assessments For Improving Algorithmic Robustness, Thomas B. Jones

Computer Science ETDs

Though computational models typically assume all program steps execute flawlessly, that does not imply all steps are equally important if a failure should occur. In the "Constrained Reliability Allocation" problem, sufficient resources are guaranteed for operations that prompt eventual program termination on failure, but those operations that only cause output errors are given a limited budget of some vital resource, insufficient to ensure correct operation for each of them.

In this dissertation, I present a novel representation of failures based on a combination of their timing and location combined with criticality assessments---a method used to predict the behavior of systems …

Improving Large Scale Application Performance Via Data Movement Reduction, Dewan M. Ibtesham

Computer Science ETDs

The compute capacity growth in high performance computing (HPC) systems is outperforming improvements in other areas of the system for example, memory capacity, network bandwidth and I/O bandwidth. Therefore, the cost of executing a floating point operation is decreasing at a faster rate than moving that data. This increasing performance gap causes wasted CPU cycles while waiting for slower I/O operations to complete in the memory hierarchy, network, and storage. These bottlenecks decrease application time to solution performance, and increase energy consumption, resulting in system under utilization. In other words, data movement is becoming a key concern for future HPC …