An efficient hybrid multicast transport protocol for collaborative virtual environment with networked haptic

In recent years, we have witnessed a growing interest in the synchronous collaboration based class of applications. Several techniques for collaborative virtual environments (CVE), haptic, audio and visual environments (C-HAVE) have been designed. However, several challenging issues remain to be resolved before CVE and C-HAVE become a common place. In this paper, we focus on applications that are based on closely coupled and highly synchronized haptic tasks that require a high-level of coordination among the participants. Four main protocols have been designed to resolve the synchronization issues in such environments: the synchronous collaboration transport protocol, the selective reliable transmission protocol, the reliable multicast transport protocol and the scalable reliable multicast. While these four protocols have shown good performance for CVE and C-HAVE class of applications, none of these protocols has been able to meet all of the basic CVE requirements, i.e., scalability, reliability, synchronization, and minimum delay. In this paper, we present a hybrid protocol that is able to satisfy all of the CVE and C-HAVE requirements and discuss its implementation and results in two tele-surgery applications. This work is partially supported by Grants from Canada Research Chair Program, NSERC, OIT/Ontario Distinguished Researcher Award, Early Research Award and ORNEC Research Grant.     

Direction-based adaptive data propagation for heterogeneous sensor mobility

We consider sensor networks where the sensor nodes are attached on entities that move in a highly dynamic, heterogeneous manner. To capture this mobility diversity we introduce a new network parameter, the direction-aware mobility level, which measures how fast and close each mobile node is expected to get to the data destination (the sink). We then provide local, distributed data dissemination protocols that adaptively exploit the node mobility to improve performance. In particular, “high” mobility is used as a low cost replacement for data dissemination (due to the ferrying of data), while in the case of “low” mobility either (a) data propagation redundancy is increased (when highly mobile neighbors exist) or (b) long-distance data transmissions are used (when the entire neighborhood is of low mobility) to accelerate data dissemination toward the sink. An extensive performance comparison to relevant methods from the state of the art demonstrates significant improvements, i.e. latency is reduced by even four times while keeping energy dissipation and delivery success at very satisfactory levels.     

Silicene Nanoribbons on an Insulating Thin Film

Silicene, a new 2D material has attracted intense research because of the ubiquitous use of silicon in modern technology. However, producing free-standing silicene has proved to be a huge challenge. Until now, silicene could be synthesized only on metal surfaces where it naturally forms strong interactions with the metal substrate that modify its electronic properties. Here, the authors report the first experimental evidence of silicene nanoribbons on an insulating NaCl thin film. This work represents a major breakthrough, for the study of the intrinsic properties of silicene, and by extension to other 2D materials that have so far only been grown on metal surfaces.     

A performance evaluation of a fault-tolerant path recommendation protocol for smart transportation system

Recommending traveling vehicles to take a certain path towards their targeted destinations have received great interest recently. At the downtown area several paths can lead to the same located destination, this is due to the grid-layout architecture of modern downtowns. Drivers always wish to reach their destinations as fast as possible and without traveling drastically long distance or without consuming extra fuel. The best path towards any destination is determined based on the relative location of the vehicle from its destination and based on other vehicles traffic distribution on the road network. Although numerous studies have investigated this issue over the road network, the communication failures and their effects on the obtained path have been neglected in those previous studies. In this paper, we investigate these potential faults and their effects on the correctness of the selected paths. We then proposed a new protocol to tackle these potential failures while selecting the best path towards each destination over the road network, fault tolerant path recommendation protocol (FT-PR). From the experimental results, we can see that the FT-PR protocol has a higher success ratio than previous path recommendation protocols, such as ICOD. This is demonstrated by obtaining paths with shorter traveling time and shorter traveling distance. The FT-PR protocol also eliminates extra loops over the road network in each selected path.     

A noise constrained least mean fourth (NCLMF) adaptive algorithm

The learning speed of an adaptive algorithm can be improved by properly constraining the cost function of the adaptive algorithm. In this work, a noise-constrained least mean fourth (NCLMF) adaptive algorithm is proposed. The NCLMF algorithm is obtained by constraining the cost function of the standard LMF algorithm to the fourth-order moment of the additive noise. The NCLMF algorithm can be seen as a variable step-size LMF algorithm. The main aim of this work is to derive the NCLMF adaptive algorithm, analyze its convergence behavior, and assess its performance in different noise environments. Furthermore, the analysis of the proposed NCLMF algorithm is carried out using the concept of energy conservation. Finally, a number of simulation results are carried out to corroborate the theoretical findings, and as expected, improved performance is obtained through the use of this technique over the traditional LMF algorithm.     

A surrogate model to assess the whole body SAR induced by multiple plane waves at 2.4?GHz

The assessment of the exposure to electromagnetic waves is nowadays a key question. Dealing with the relationship between exposure and incident field, most of previous investigations have been performed with a single plane wave. Realistic exposure in the far field can be modeled as multiple plane waves with random direction of arrival, random amplitude, and random phase. This paper, based on numerical investigations, studies the whole body specific absorption rate (SAR) linked to the exposure induced by five random plane waves having uniformly distributed angles of arrival in the horizontal plane, log-normal distributed amplitudes, and uniformly distributed phases. A first result shows that this random heterogeneous exposure generates maximal variations of ??25% for the whole body specific absorption. An important observation is that the exposure to a single plane wave arriving face to the body, used for the guidelines, does not constitute the worst case. We propose a surrogate model to assess the distribution of the whole body SAR in the case of an exposure to multiple plane waves. For a sample of 30 values of whole body SAR induced by five plane waves at 2.4?GHz, this simple approach, considering the resulting SAR as the sum of the SAR induced by each isolated plane wave, leads to an estimated distribution of whole body SAR following the real distribution with a p value of 76% according to the Kolmogorov statistical test.     

A Multichannel QoS MAC with Dynamic Transmit Opportunity for VANets

One of the most challenging issues facing vehicular networks lies in the design of an efficient MAC protocol due to the mobile nature of nodes and the interference associated with the dynamic environment. Moreover delay constraints for safety applications add complexity and latency requirements to the design. Existing MAC protocols overcome some challenges however don’t provide an integrated solution. Hence, the merit if this work lies in designing an efficient MAC protocol that incorporates various VANet’s challenges in a complete end-to-end solution. In this work, we propose an efficient Multichannel QoS Cognitive MAC (MQOG). MQOG assesses the quality of channel prior to transmission employing dynamic channel allocation and negotiation algorithms to achieve significant increase in channel reliability, throughput and delay constraints while simultaneously addressing Quality of Service. The uniqueness of MQOG lies in making use of the free unlicensed bands. The proposed protocols were implemented in OMNET++ 4.1, and extensive experiments demonstrated a faster and more efficient reception of safety messages compared to existing VANet MAC Protocols. Finally, improvements in delay, packet delivery ratios and throughput were captured.     

Estimation of pharmacokinetic parameters by orthogonal regression: comparison of four algorithms.

The contribution of non-linear orthogonal regression for estimation of individual pharmacokinetic parameters when drug concentrations and sampling times are subject to error was studied. The first objective was to introduce and compare four numerical approaches that involve different degrees of approximation for parameter estimation by orthogonal regression. The second objective was to compare orthogonal with non-orthogonal regression. These evaluations were based on simulated data sets from 300 'subjects', thereby enabling precision and accuracy of parameter estimates to be determined. The pharmacokinetic model was a one-compartment open model with first-order absorption and elimination rates. The inter-individual coefficients of variation (CV) of the pharmacokinetic parameters were in the range 33-100%. Eight measurement-error models for times and concentrations (homo- or heteroscedastic with constant CV) were considered. Accuracy of the four algorithms was very close in almost all instances (typical bias, 1-4%). Precision showed three expected trends: root mean squared error (RMSE) increased when the residual error was larger or the number of observations was smaller, and it was highest for the absorption rate constant and common error variance. Overall, RMSE ranged from 5 to 40%. It was found that the simplest algorithm for othogonal regression performed as well as the more complicated approaches. Errors in sampling time resulted in an increased bias and imprecision in individual parameter estimates (especially for k(a) in our example) and in common error variance when the estimation method did not take into account these errors. In this situation, use of orthogonal regression resulted in smaller bias and better precision.