Small aperture evanescent-mode waveguide antenna matched using distributed coupled resonators

Presented is a design methodology which permits the application of distributed coupled resonator bandpass filter principles to form wideband small-aperture evanescent-mode waveguide antenna designs. This approach permits matching of the complex antenna aperture admittance of an evanescent-mode open-ended waveguide to a real impedance generator, and thereby to a coaxial feed probe. A simulated reflection coefficient of < - 10 dB was obtained over a bandwidth of 20%, from 2.0-2.45 GHz, in a 2.58 GHz cutoff waveguide. Dielectric-filled propagating waveguide and air-filled evanescent-mode waveguide sections are used to form the resonators/coupling elements of the antenna's coupled resonator matching sections. Simulated realised gain variation from 3.4-5.0 dBi is observed across the bandwidth. The antenna's maximum aperture dimension is < 0.47 wavelength at the upper operating frequency and so it is suitable for use in a wide angle scanning phased array.

Distributed passive intermodulation generation in coplanar waveguide transmission lines

A phenomenology of distributed passive intermodulation generation in coplanar waveguide transmission line is presented. The theoretical analysis is based upon the generalised nonlinear transmission line model, which accounts for the coupling of two propagating modes. The case of weak substrate nonlinearity is considered and the model is given qualitative verification through the mapping of passive intermodulation products generated in coplanar waveguide fabricated on a commercial laminate. Implications for future research are discussed. © 2012 IEEE.

Swarm scheduling approaches for work-flow applications with security constraints in distributed data-intensive computing environments

The scheduling problem in distributed data-intensive computing environments has become an active research topic due to the tremendous growth in grid and cloud computing environments. As an innovative distributed intelligent paradigm, swarm intelligence provides a novel approach to solving these potentially intractable problems. In this paper, we formulate the scheduling problem for work-flow applications with security constraints in distributed data-intensive computing environments and present a novel security constraint model. Several meta-heuristic adaptations to the particle swarm optimization algorithm are introduced to deal with the formulation of efficient schedules. A variable neighborhood particle swarm optimization algorithm is compared with a multi-start particle swarm optimization and multi-start genetic algorithm. Experimental results illustrate that population based meta-heuristics approaches usually provide a good balance between global exploration and local exploitation and their feasibility and effectiveness for scheduling work-flow applications. © 2010 Elsevier Inc. All rights reserved.

The Forgiving Graph: a distributed data structure for low stretch under adversarial attack

We consider the problem of self-healing in peer-to-peer networks that are under repeated attack by an omniscient adversary. We assume that, over a sequence of rounds, an adversary either inserts a node with arbitrary connections or deletes an arbitrary node from the network. The network responds to each such change by quick “repairs,” which consist of adding or deleting a small number of edges. These repairs essentially preserve closeness of nodes after adversarial deletions, without increasing node degrees by too much, in the following sense. At any point in the algorithm, nodes v and w whose distance would have been l in the graph formed by considering only the adversarial insertions (not the adversarial deletions), will be at distance at most l log n in the actual graph, where n is the total number of vertices seen so far. Similarly, at any point, a node v whose degree would have been d in the graph with adversarial insertions only, will have degree at most 3d in the actual graph. Our distributed data structure, which we call the Forgiving Graph, has low latency and bandwidth requirements. The Forgiving Graph improves on the Forgiving Tree distributed data structure from Hayes et al. (2008) in the following ways: 1) it ensures low stretch over all pairs of nodes, while the Forgiving Tree only ensures low diameter increase; 2) it handles both node insertions and deletions, while the Forgiving Tree only handles deletions; 3) it requires only a very simple and minimal initialization phase, while the Forgiving Tree initially requires construction of a spanning tree of the network.