A Graph Model for DynamicWaveband Switching in WDM Mesh Networks

We investigate the problem of waveband switching (WBS) in a wavelength-division multiplexing (WDM) mesh network with dynamic traffic requests. To solve the WBS problem in a homogeneous dynamic WBS network, where every node is a multi-granular optical cross-connect (MG-OXC), we construct an auxiliary graph. Based on the auxiliary graph, we develop two heuristic on-line WBS algorithms with different grouping policies, namely the wavelength-first WBS algorithm based on the auxiliary graph (WFAUG) and the waveband-first WBS algorithm based on the auxiliary graph (BFAUG). Our results show that the WFAUG algorithm outperforms the BFAUG algorithm.

SimSight: A Virtual Machine Based Dynamic Call Graph Generator

One problem with using component-based software development approach is that once software modules are reused over generations of products, they form legacy structures that can be challenging to understand, making validating these systems difficult. Therefore, tools and methodologies that enable engineers to see interactions of these software modules will enhance their ability to make these software systems more dependable. To address this need, we propose SimSight, a framework to capture dynamic call graphs in Simics, a widely adopted commercial full-system simulator. Simics is a software system that simulates complete computer systems. Thus, it performs nearly identical tasks to a real system but at a much lower speed while providing greater execution observability. We have implemented SimSight to generate dynamic call graphs of statically and dynamically linked functions in x86/Linux environment. A case study illustrates how we can use SimSight to identify sources of software errors. We then evaluate its performance using 12 integer programs from SPEC CPU2006 benchmark suite.

Applications and Potentials for Biogenic Methane Recovery Operations in Nebraska Agriculture, Industry, and Economic Development

ABSTRACT: This thesis report illustrates the applications and potentials of biogenic methane recovery in Nebraska’s agricultural and industrial sectors and as a means for increasing sustainable economic development in the state’s rural communities. As the nation moves toward a new green economy, biogenic methane recovery as a waste management strategy and renewable energy resource presents significant opportunities for Nebraska to be a national and world leader in agricultural and industrial innovation, advanced research and development of renewable energy technology, and generation of new product markets. Nebraska’s agricultural economy provides a distinct advantage to the state for supporting methane recovery operations that provide long-term economic and environmental partnerships among producers, industry, and communities. These opportunities will serve to protect Nebraska’s agricultural producers from volatile energy input markets and as well as creating new markets for Nebraska agricultural products. They will also serve to provide quality education and employment opportunities for Nebraska students and businesses. There are challenges and issues that remain for the state in order to take advantage of its resource potential. There is a need to produce a comprehensive Nebraska biogenic methane potential study and digital mapping system to identify high-potential producers, co-products, and markets. There is also a need to develop a web-based format of consolidated information specific to Nebraska to aid in connecting producers, service providers, educators, and policy-makers.

REDUCTION IN RODENT POPULATIONS THROUGH INTERMITTENT CONTROL OPERATIONS IN THE CROPPING ECOSYSTEM OF THE INDIAN DESERT

Control operations at 6-month intervals, continued for four years in crop fields, reduced the rodent population to 5.08 percent losses to agricultural production. After eight crop seasons, a significant reduction in rodent density was observed in treated areas when compared with that of the control areas (P < 0.01). Correlation between pre-treatment population index (y) and number of seasons (log of x) was found to be 0.91 (P < 0.01). A relationship was established between y and x : y = 0.804.0-0.9621 log x. From this equation, it can be inferred that rodent population will reach zero level after treating crop fields continuously for6.85 or say 7.0 (seven) seasons. After control, the numbers of predominant rodents, Tatera indica, Meriones hurrianae and Rattus meltada. were significantly reduced and the residual population was composed of Mus booduga. Gerbillus spp., Rattus gleadowi. Golunda ellioti and Funambulus pennanti.