Systemic risk in dynamical networks with stochastic failure criterion

Complex non-linear interactions between banks and assets we model by two time-dependent Erd\H{o}s Renyi network models where each node, representing bank, can invest either to a single asset (model I) or multiple assets (model II). We use dynamical network approach to evaluate the collective financial failure---systemic risk---quantified by the fraction of active nodes. The systemic risk can be calculated over any future time period, divided on sub-periods, where within each sub-period banks may contiguously fail due to links to either (i) assets or (ii) other banks, controlled by two parameters, probability of internal failure $p$ and threshold $T_h$ ("solvency" parameter). The systemic risk non-linearly increases with $p$ and decreases with average network degree faster when all assets are equally distributed across banks than if assets are randomly distributed. The more inactive banks each bank can sustain (smaller $T_h$), the smaller the systemic risk---for some $T_h$ values in I we report a discontinuity in systemic risk. When contiguous spreading becomes stochastic (ii) controlled by probability $p_2$---a condition for the bank to be solvent (active) is stochastic---the systemic risk decreases with decreasing $p_2$. We analyse asset allocation for the U.S. banks.Comment: 7 pages, 7 figure

A new generalized particle approach to parallel bandwidth allocation

This paper presents a new generalized particle (GP) approach to dynamical optimization of network bandwidth allocation, which can also be used to optimize other resource assignments in networks. By using the GP model, the complicated network bandwidth allocation problem is transformed into the kinematics and dynamics of numerous particles in two reciprocal dual force-fields. The proposed model and algorithm are featured by the powerful processing ability under a complex environment that involves the various interactions among network entities, the market mechanism between the demands and service, and other phenomena common in networks, such as congestion, metabolism, and breakdown of network entities. The GP approach also has the advantages in terms of the higher parallelism, lower computation complexities, and the easiness for hardware implementation. The properties of the approach, including the correctness, convergency and stability, are discussed in details. Simulation results attest to the effectiveness and suitability of the proposed approach. © 2006 Elsevier B.V. All rights reserved.postprin

Experimental Test bed to De-Risk the Navy Advanced Development Model

This paper presents a reduced scale demonstration test-bed at the University of Texas’ Center for Electromechanics (UT-CEM) which is well equipped to support the development and assessment of the anticipated Navy Advanced Development Model (ADM). The subscale ADM test bed builds on collaborative power management experiments conducted as part of the Swampworks Program under the US/UK Project Arrangement as well as non-military applications. The system includes the required variety of sources, loads, and controllers as well as an Opal-RT digital simulator. The test bed architecture is described and the range of investigations that can be carried out on it is highlighted; results of preliminary system simulations and some initial tests are also provided. Subscale ADM experiments conducted on the UT-CEM microgrid can be an important step in the realization of a full-voltage, full-power ADM three-zone demonstrator, providing a test-bed for components, subsystems, controls, and the overall performance of the Medium Voltage Direct Current (MVDC) ship architecture.Center for Electromechanic