Disaster-Resilient Control Plane Design and Mapping in Software-Defined Networks

Communication networks, such as core optical networks, heavily depend on their physical infrastructure, and hence they are vulnerable to man-made disasters, such as Electromagnetic Pulse (EMP) or Weapons of Mass Destruction (WMD) attacks, as well as to natural disasters. Large-scale disasters may cause huge data loss and connectivity disruption in these networks. As our dependence on network services increases, the need for novel survivability methods to mitigate the effects of disasters on communication networks becomes a major concern. Software-Defined Networking (SDN), by centralizing control logic and separating it from physical equipment, facilitates network programmability and opens up new ways to design disaster-resilient networks. On the other hand, to fully exploit the potential of SDN, along with data-plane survivability, we also need to design the control plane to be resilient enough to survive network failures caused by disasters. Several distributed SDN controller architectures have been proposed to mitigate the risks of overload and failure, but they are optimized for limited faults without addressing the extent of large-scale disaster failures. For disaster resiliency of the control plane, we propose to design it as a virtual network, which can be solved using Virtual Network Mapping techniques. We select appropriate mapping of the controllers over the physical network such that the connectivity among the controllers (controller-to-controller) and between the switches to the controllers (switch-to-controllers) is not compromised by physical infrastructure failures caused by disasters. We formally model this disaster-aware control-plane design and mapping problem, and demonstrate a significant reduction in the disruption of controller-to-controller and switch-to-controller communication channels using our approach.Comment: 6 page

Surface-guided computing to analyze subcellular morphology and membrane-associated signals in 3D

Signal transduction and cell function are governed by the spatiotemporal organization of membrane-associated molecules. Despite significant advances in visualizing molecular distributions by 3D light microscopy, cell biologists still have limited quantitative understanding of the processes implicated in the regulation of molecular signals at the whole cell scale. In particular, complex and transient cell surface morphologies challenge the complete sampling of cell geometry, membrane-associated molecular concentration and activity and the computing of meaningful parameters such as the cofluctuation between morphology and signals. Here, we introduce u-Unwrap3D, a framework to remap arbitrarily complex 3D cell surfaces and membrane-associated signals into equivalent lower dimensional representations. The mappings are bidirectional, allowing the application of image processing operations in the data representation best suited for the task and to subsequently present the results in any of the other representations, including the original 3D cell surface. Leveraging this surface-guided computing paradigm, we track segmented surface motifs in 2D to quantify the recruitment of Septin polymers by blebbing events; we quantify actin enrichment in peripheral ruffles; and we measure the speed of ruffle movement along topographically complex cell surfaces. Thus, u-Unwrap3D provides access to spatiotemporal analyses of cell biological parameters on unconstrained 3D surface geometries and signals.Comment: 49 pages, 10 figure

3D billiards: visualization of regular structures and trapping of chaotic trajectories

The dynamics in three-dimensional billiards leads, using a Poincar\'e section, to a four-dimensional map which is challenging to visualize. By means of the recently introduced 3D phase-space slices an intuitive representation of the organization of the mixed phase space with regular and chaotic dynamics is obtained. Of particular interest for applications are constraints to classical transport between different regions of phase space which manifest in the statistics of Poincar\'e recurrence times. For a 3D paraboloid billiard we observe a slow power-law decay caused by long-trapped trajectories which we analyze in phase space and in frequency space. Consistent with previous results for 4D maps we find that: (i) Trapping takes place close to regular structures outside the Arnold web. (ii) Trapping is not due to a generalized island-around-island hierarchy. (iii) The dynamics of sticky orbits is governed by resonance channels which extend far into the chaotic sea. We find clear signatures of partial transport barriers. Moreover, we visualize the geometry of stochastic layers in resonance channels explored by sticky orbits.Comment: 20 pages, 11 figures. For videos of 3D phase-space slices and time-resolved animations see http://www.comp-phys.tu-dresden.de/supp

An extensive English language bibliography on graph theory and its applications, supplement 1

Graph theory and its applications - bibliography, supplement

Characterization of a turbulent separating/ reattaching flow using optical pressure and velocity measurements

The turbulent wake flow behind a generic spacecraft was investigated experimentally in the trisonic wind tunnel Munich at subsonic Mach numbers M = [0.3; 0.7]. The flow/ structure interaction which raised critical safety aspects on the real spacecraft in the past was studied. The characterization of the coherent flow structures was performed by means of transient optical and classical measurement techniques. The topology and dynamics of the wake flow and the pressure field were investigated with the 2C2D-PIV and the instationary PSP. The reattachment position as well as the local dynamic behavior of strong flow structures were successfully characterized and the presence of dominant vortex shedding at expected frequencies around f ≈ [400; 900] Hz was confirmed. It was the first time that the fluid/ structure interaction and the position of strongest stresses could be characterized experimentally with very high spatial and temporal resolution. A PSP system had to be established in order to perform the desired experiments. Therefore, basic components (e.g. calibration chamber, excitation, evaluation tool) had to be developed and the performance of the entire system had to be validated

A topological solution to object segmentation and tracking

The world is composed of objects, the ground, and the sky. Visual perception of objects requires solving two fundamental challenges: segmenting visual input into discrete units, and tracking identities of these units despite appearance changes due to object deformation, changing perspective, and dynamic occlusion. Current computer vision approaches to segmentation and tracking that approach human performance all require learning, raising the question: can objects be segmented and tracked without learning? Here, we show that the mathematical structure of light rays reflected from environment surfaces yields a natural representation of persistent surfaces, and this surface representation provides a solution to both the segmentation and tracking problems. We describe how to generate this surface representation from continuous visual input, and demonstrate that our approach can segment and invariantly track objects in cluttered synthetic video despite severe appearance changes, without requiring learning.Comment: 21 pages, 6 main figures, 3 supplemental figures, and supplementary material containing mathematical proof

Geometrical Spinoptics and the Optical Hall Effect

33 pages. Two subsections and new references added. To appear in the Journal of Geometry and PhysicsGeometrical optics is extended so as to provide a model for spinning light rays via the coadjoint orbits of the Euclidean group characterized by color and spin. This leads to a theory of ``geometrical spinoptics'' in refractive media. Symplectic scattering yields generalized Snell-Descartes laws that include the recently discovered optical Hall effect