Managing computer networks using peer-to-peer technologies

Peer-to-peer systems and network management are usually related to each other because the traffic loads of P2P systems have to be controlled to avoid regular network services becoming unavailable due to network congestion. In this context, from a network operation point of view, P2P systems often mean problems. In this article we take a different perspective and look at P2P technologies as an alternative to improve current network management solutions. We introduce an approach where P2P networks are used as flexible interdomain distributed management systems able to provide facilities often absent in traditional management systems. We present three examples of P2P-based network management: how managed network views can be shared in a P2P network, how P2P-based application layer routing can improve connectivity between management entities, and how groups of peers can be used to process management tasks in a balanced way. Our main goal is to show that P2P technologies are a feasible tool for network management, and thus motivate further investigations on the subject.     

Improved Message Forwarding for Multi-Hop HaRTES Real-Time Ethernet Networks

Nowadays, switched Ethernet networks are used in complex systems that encompass tens to hundreds of nodes and thousands of signals. Such scenarios require multi-switch architectures where communications frequently occur in multiple hops. In this paper we investigate techniques to allow efficient multi-hop communication using HaRTES switches. These are modified Ethernet switches that provide real-time traffic scheduling, dynamic bandwidth management and temporal isolation between real-time and non-real-time traffic. This paper addresses the problem of forwarding traffic in HaRTES networks. Two methods have been recently proposed, namely Distributed Global Scheduling (DGS) that buffers traffic between switches, and Reduced Buffering Scheme (RBS), that uses immediate forwarding. In this paper, we discuss the design and implementation of RBS within HaRTES and we carry out an experimental validation with a prototype implementation. Then, we carry out a comparison between RBS and DGS using worst-case response time analysis and simulation. The comparison clearly establishes the superiority of RBS concerning end-to-end response times. In fact, with sample message sets, we achieved reductions in end-to-end delay that were as high as 80 %.     

Fully digital BPSK demodulator for satellite supressed carrier telecommand system

In this paper, we present the design of a fully digital binary phase shift keying demodulator for application in satellite high‐rate suppressed carrier telecommand system. The proposed system digitalizes the received signal in the intermediate frequency stage using bandpass sampling technique, and the resulting baseband signal is used to synchronization of symbol and phase and to bit detection. The design of all functional modules is presented in details. Another innovation presented in this work is the inclusion of a non‐linearity in the phase synchronizer module to permit its operation independent from the signal amplitude. Moreover, aiming the characterization and performance evaluation of the system, we do some original mathematical analyses. Finally, test results show that the demodulator complies all the project requirements, and the prototype implementation loss, in terms of bit energy to noise power density ratio, is less than 0.3 dB. Copyright © 2016 John Wiley & Sons, Ltd.     

Comb-Push Ultrasound Shear Elastography (CUSE): A Novel Method for Two-Dimensional Shear Elasticity Imaging of Soft Tissues

Fast and accurate tissue elasticity imaging is essential in studying dynamic tissue mechanical properties. Various ultrasound shear elasticity imaging techniques have been developed in the last two decades. However, to reconstruct a full field-of-view 2-D shear elasticity map, multiple data acquisitions are typically required. In this paper, a novel shear elasticity imaging technique, comb-push ultrasound shear elastography (CUSE), is introduced in which only one rapid data acquisition (less than 35 ms) is needed to reconstruct a full field-of-view 2-D shear wave speed map (40 × 38 mm). Multiple unfocused ultrasound beams arranged in a comb pattern (comb-push) are used to generate shear waves. A directional filter is then applied upon the shear wave field to extract the left-to-right (LR) and right-to-left (RL) propagating shear waves. Local shear wave speed is recovered using a time-of-flight method based on both LR and RL waves. Finally, a 2-D shear wave speed map is reconstructed by combining the LR and RL speed maps. Smooth and accurate shear wave speed maps are reconstructed using the proposed CUSE method in two calibrated homogeneous phantoms with different moduli. Inclusion phantom experiments demonstrate that CUSE is capable of providing good contrast (contrast-to-noise ratio ≥ 25 dB) between the inclusion and background without artifacts and is insensitive to inclusion positions. Safety measurements demonstrate that all regulated parameters of the ultrasound output level used in CUSE sequence are well below the FDA limits for diagnostic ultrasound.     

Revamping SiO2 Spheres by Core–Shell Porosity Endowment to Construct a Mazelike Nanoreactor for Enhanced Catalysis in CO2 Hydrogenation to Methanol

Beyond the catalytic activity of nanocatalysts, the support with architectural design and explicit boundary could also promote the overall performance through improving the diffusion process, highlighting additional support for the morphology-dependent activity. To delineate this, herein, a novel mazelike-reactor framework, namely multi-voids mesoporous silica sphere (MVmSiO₂), is carved through a top-down approach by endowing core-shell porosity premade Stöber SiO₂ spheres. The precisely-engineered MVmSiO₂ with peripheral one-dimensional pores in the shell and interconnecting compartmented voids in the core region is simulated to prove combined hierarchical and structural superiority over its analogous counterparts. Supported with CuZn-based alloys, mazelike MVmSiO₂ nanoreactor experimentally demonstrated its expected workability in model gas-phase CO₂ hydrogenation reaction where enhanced CO₂ activity, good methanol yield, and more importantly, a prolonged stable performance are realized. While tuning the nanoreactor composition besides morphology optimization could further increase the catalytic performance, it is accentuated that the morphological architecture of support further boosts the reaction performance apart from comprehensive compositional optimization. In addition to the found morphological restraints and size-confinement effects imposed by MVmSiO₂, active sites of catalysts are also investigated by exploring the size difference of the confined CuZn alloy nanoparticles in CO₂ hydrogenation employing both in-situ experimental characterizations and density functional theory calculations.     

Transmission Fiber Chromatic Dispersion Dependence on Temperature: Implications on 40 Gb/s Performance

In this letter, we will evaluate the performance degradation of a 40 km high‐speed (40 Gb/s) optical system, induced by optical fiber variations of the chromatic dispersion induced by temperature changes. The chromatic dispersion temperature sensitivity will be estimated based on the signal quality parameters.     

Impurity ‘Hot Spots’ in MBE HgCdTe/CdZnTe

In this work, impurity ‘hot spot’ macro-defects—high impurity level macro-defect contaminates were examined. ‘Hot spots’ have very high localized concentrations of: K, Mg, Ni, Cr, Mn, Ca, Al, Na, Fe, and Cu. For example, these ‘hot spot’ macro-defects can have Cu concentrations >?1?×?10¹⁸ cm^?3. Focused ion beam scanning transmission electron microscopy analysis of four ‘hot spots’ was performed. The origin of ‘hot spot’ defects is unresolved—however, our analysis has shown ‘hot spots’ can arise due to molecular beam epitaxy spit defects and CdZnTe substrate defects. The estimated ‘hot spot’ density is ～?30 cm^?2. The presence of impurity ‘hot spot’ macro-defects in HgCdTe/CdZnTe is confirming evidence for the occurrence of L. Bubulac’s impurity ‘pipe’ mechanism.     

Spectroscopic ellipsometry for monitoring and control of molecular beam epitaxially grown HgCdTe heterostructures

A systematic study of the effect of measurement perturbation on in situ monitoring of the composition of molecular beam epitaxially (MBE) grown Hg_1−xCd_xTe using spectroscopic ellipsometry was carried out. Of the five variables investigated, which included angle of incidence, wavelength of the light beam, modulator rotation, analyzer rotation, and modulator amplitude, the angle of incidence and the modulator rotation had the strongest effect on the in situ Hg_1−xCd_xTe composition monitoring process. A wobble-free sample manipulator was installed to reduce the impact of these two variables. With these improvements, the spectroscopic ellipsometer is now routinely used to monitor Hg _1−xCd_xTe compositions during MBE growth of heterostructures and is a useful tool in diagnosing growth-related problems. Examples are included for both application areas, that include the control of the interface between Hg_1−xCd_xTe layers of different compositions, i.e. device engineering.     

Towards a Sustainable Green Design for Next-Generation Networks

Recently distributed real-time database systems are intended to manage large volumes of dispersed data. To develop distributed real-time data processing, a reality and stay competitive well defined protocols and algorithms must be required to access and manipulate the data. An admission control policy is a major task to access real-time data which has become a challenging task due to random arrival of user requests and transaction timing constraints. This paper proposes an optimal admission control policy based on deep reinforcement algorithm and memetic algorithm which can efficiently handle the load balancing problem without affecting the Quality of Service (QoS) parameters. A Markov decision process (MDP) is formulated for admission control problem, which provides an optimized solution for dynamic resource sharing. The possible solutions for MDP problem are obtained by using reinforcement learning and linear programming with an average reward. The deep reinforcement learning algorithm reformulates the arrived requests from different users and admits only the needed request, which improves the number of sessions of the system. Then we frame the load balancing problem as a dynamic and stochastic assignment problem and obtain optimal control policies using memetic algorithm. Therefore proposed admission control problem is changed to memetic logic in such a way that session corresponds to individual elements of the initial chromosome. The performance of proposed optimal admission control policy is compared with other approaches through simulation and it depicts that the proposed system outperforms the other techniques in terms of throughput, execution time and miss ratio which leads to better QoS.

     

Directional Estimation of Block-Fading MIMO Channels Using Spherical Harmonics Expansion and Tensor Analysis

The well-known benefits of multiple input multiple output (MIMO) wireless communication systems suppose an efficient use of spatial diversity at both the transmitter and receiver. An important and not well-explored path toward improving MIMO system performance using spatial diversity takes into account the interactions among the antennas and the (physical) propagation medium. In this work, spherical harmonics and tensor analysis are originally combined into the problem of MIMO channel modeling and estimation. The use of spherical harmonics allows to represent the antenna radiation patterns in terms of coefficients of an expansion of spatially orthogonal functions, thus decoupling the transmit and receive antenna array responses from the physical propagation medium. Assuming a single-scattering propagation scenario driven by a finite number of specular multipaths, the parallel factor model is used to decompose the spherical modes of the MIMO channel into a sum of rank-one spherical mode tensors, whose dimensions are transmit modes, receive modes, and time. Then, we extend the tensor modeling framework to double scattering channels by resorting to the PARATUCK model that captures the interactions between multiple-scattering clusters. Capitalizing on the structure of these tensor models, we derive tensor-based alternating least squares algorithms for estimating directional MIMO channels in the spherical harmonics domain, from which the directions of arrival and directions of departure are extracted by means of a MUSIC-based method. Simulation results are provided to assess the performance of the proposed algorithms in selected system configurations. Our results also show the impact of the spherical expansion order on the accuracy of DoD/DoA estimates using the proposed algorithms.