We will demonstrate the Secure Wireless Agent Testbed (SWAT), a unique facility developed at Drexel University to study integration, networking and information assurance for next-generation wireless mobile agent systems. SWAT is an implemented system that fully integrates: 1) mobile agents, 2) wireless ad hoc multi-hop networks, and 3) security. The demonstration will show the functionality of ...

Using the probably approximately correct (PAC) learning hypothesis, we have conducted experiments using clustered computers, high-performance workstations and ad-hoc grids of personal computers, to develop an analytical model for, and demonstrate asymptotic convergence of simple parallel search in the parameter space of complex environmental models such as the Soil and Water Assessment Tool (SW...

SWAT (Soil and Water Assessment Tool) is a comprehensive, semi-distributed river basin model that requires a large number of input parameters, which complicates model parameterization and calibration. Several calibration techniques have been developed for SWAT, including manual calibration procedures and automated procedures using the shuffled complex evolution method and other common methods. ...

The temptation to include model parameters and high resolution input data together with the availability of powerful optimization and uncertainty analysis algorithms has significantly enhanced the complexity of hydrologic and water quality modeling. However, the ability to take advantage of sophisticated models is hindered in those models that need a large number of input files, such as the Soi...

This paper proposes and evaluates a decentralized self-healing mechanism that detects and recovers from wormhole attacks in wireless multi-hop sensor networks. Upon detecting a wormhole attack, the proposed mechanism, called SWAT, identifies the locations of malicious nodes (or wormhole nodes), isolates them from the network and recovers the routing structure distorted by them. SWAT is the firs...

Calibration of large watershed models requires multi-gage calibration, however there are limited tools available for performing these calibrations of SWAT models. Non-Dominated Sorting Genetic Algorithm II (NSGA-II) has been shown to be an effective and efficient multi-objective calibration algorithm in various disciplines. Although NSGA-II has been used with SWAT before, there is no publically...

This study explored the application of a multi-objective evolutionary algorithm (MOEA) and Pareto ordering in the multiple-objective automatic calibration of the Soil and Water Assessment Tool (SWAT). SWAT was calibrated in the Calapooia watershed, Oregon, USA, with two different pairs of objective functions in a cluster of 24 parallel computers. The non-dominated sorting genetic algorithm (NSG...