Joseph Timothy Foley

Use of the manufacturing system design decomposition for comparative analysis and effective design of production systems

The focus of this paper is on the use of the Manufacturing System Design Decomposition (MSDD) to make effective cost and production system design decisions. A comparative study is conducted to illustrate how and why the total cost is reduced when the functional requirements defined by the MSDD are achieved. The ultimate goal of this research was to advance manufacturing and production system development to being guided by engineering science and design rather than the common practice of duplicating another person’s or entity’s notion of the best physical implementation.

Extending wireless algorithm design to arbitrary environments via metricity

Efficient spectrum use in wireless sensor networks through spatial reuse requires effective models of packet reception at the physical layer in the presence of interference. Despite recent progress in analytic and simulations research into worst-case behavior from interference effects, these efforts generally assume geometric path loss and isotropic transmission, assumptions which have not been borne out in experiments. Our paper aims to provide a methodology for grounding theoretical results into wireless interference in experimental reality. We develop a new framework for wireless algorithms in which distance-based path loss is replaced by an arbitrary gain matrix, typically obtained by measurements of received signal strength (RSS). We experimentally evaluate the framework in two indoors testbeds with 20 and 60~motes, and confirm superior predictive performance in packet reception rate for a gain matrix model over a geometric distance-based model. At the heart of our approach is a new parameter ζ called metricity which indicates how close the gain matrix is to a distance metric, effectively measuring the complexity of the environment. A powerful theoretical feature of this parameter is that all known SINR scheduling algorithms that work in general metric spaces carry over to arbitrary gain matrices and achieve equivalent performance guarantees in terms of ζ as previously obtained in terms of the path loss constant. Our experiments confirm the sensitivity of ζ to the nature of the environment. Finally, we show analytically and empirically how multiple channels can be leveraged to improve metricity and thereby performance. We believe our contributions will facilitate experimental validation for recent advances in algorithms for physical wireless interference models.