Algorithms for Performance, Dependability, and Performability Evaluation using Stochastic Activity Networks

Modeling tools and technologies are important for aerospace development. At the University of Illinois, we have worked on advancing the state of the art in modeling by Markov reward models in two important areas: reducing the memory necessary to numerically solve systems represented as stochastic activity networks and other stochastic Petri net extensions while still obtaining solutions in a reasonable amount of time, and finding numerically stable and memory-efficient methods to solve for the reward accumulated during a finite mission time. A long standing problem when modeling with high level formalisms such as stochastic activity networks is the so-called state space explosion, where the number of states increases exponentially with size of the high level model. Thus, the corresponding Markov model becomes prohibitively large and solution is constrained by the the size of primary memory. To reduce the memory necessary to numerically solve complex systems, we propose new methods that can tolerate such large state spaces that do not require any special structure in the model (as many other techniques do). First, we develop methods that generate row and columns of the state transition-rate-matrix on-the-fly, eliminating the need to explicitly store the matrix at all. Next, we introduce a new iterative solution method, called modified adaptive Gauss-Seidel, that exhibits locality in its use of data from the state transition-rate-matrix, permitting us to cache portions of the matrix and hence reduce the solution time. Finally, we develop a new memory and computationally efficient technique for Gauss-Seidel based solvers that avoids the need for generating rows of A in order to solve Ax = b. This is a significant performance improvement for on-the-fly methods as well as other recent solution techniques based on Kronecker operators. Taken together, these new results show that one can solve very large models without any special structure

An open system transportation security sensor network: field trial experiences

Abstract Cargo shipments are subject to hijack, theft, or tampering. Furthermore, cargo shipments are at risk of being used to transport contraband, potentially resulting in fines to shippers. The Transportation Security Sensor Network (TSSN), which is based on open software systems and Service Oriented Architecture (SOA) principles, has been developed to mitigate these risks. Using commercial off-the-shelf (COTS) hardware, the TSSN is able to detect events and report those relevant to appropriate decision makers. However, field testing is required to validate the system architecture as well as to determine if the system can provide timely event notification. Field experiments were conducted to assess the TSSN's suitability for monitoring rail-borne cargo. Log files were collected from these experiments and postprocessed. We present the TSSN architecture and results of field experiments, including the time taken to report events using the TSSN as well as on the interaction between various components of the TSSN. These results show that the TSSN architecture can be used to monitor rail-borne cargo. i

Improving the near-metal performance of UHF RFID tags

Abstract—It is well-known that UHF RFID tag performance degrades when placed near metal. While the mechanisms for how dipole performance degrades near metal is known, it is generally not known how the parameters of the T-match change in the presence of metal, and what, if anything, can be done to improve near-metal performance. In this paper, we develop a set of expressions that describe the affect of antenna parameters on the input reactance of the antenna near metal, and a set of design principles that can be used to minimize the near-metal impedance mismatch. We conclude by demonstrating these principles with a simple antenna model yields a 12.7 meter free-space read distance, and a read distance of 7 meters when separated by a 3.2 mm HDPE foam dielectric spacer from a large ground plane

On Concurrent Events and Correctness in Stochastic Models

In performance / dependability modeling, it sometimes happens that two events are scheduled to occur at the same time. In this case, the modeler has two alternatives: specify an ordering, (perhaps deterministically or probabilistically), or leave the order unspecified. If the order is unspecified, it is assumed that the order does not matter, or that the events can happen concurrently (simultaneously). It is important to be able to express concurrency, but the ability to express concurrency may also lead to the specification of ambiguous models. There are a number of checks to determine whether models are or may be ambiguous (usually implying an incorrectly specified model) with different thresholds of ambiguity. We give a survey of a number of techniques, describing their relative usefulness and characteristics, and then provide the theoretical foundation for an efficient implementation of a particularly useful check called the well-specified check