An Evaluation of Routing Protocols for Vehicular Ad-Hoc Network Considering the Video Stream

Wireless Personal Communications - In promising application field such as Vehicular Ad hoc Networks, the ability of the driver to exchange video streams smoothly over the network regardless of his...     

A fuzzy geographical routing approach to support real-time multimedia transmission for vehicular ad hoc networks

Vehicular ad hoc networks known by their greatly active topology have given rise to new challenges related to routing protocols, issues of less concern in infrastructure-based networks or even in mobile ad hoc networks. Indeed, the high revocability of network topology makes the satisfaction of driver’s requirements very arduous, especially with multimedia applications that need strict quality of service (QoS) support. The main purpose of this paper is to promote real time video traffic by maximizing user gratification while keeping a good QoS. Thus, based on the well-known greedy perimeter stateless routing (GPSR) protocol, we propose a new approach called fuzzy geographical routing (FzGR) that incorporates two fuzzy logic usages. The first takes into consideration three input parameters of QoS: the delay, the size of buffer and the throughput, while it outputs a single relevant metric to prioritize the next-hop with lower concern. The other fuzzy system aims at preserving the concept of basic GPSR by considering the distance measure between each next-hop and the final destination. The proposal has been evaluated and compared to the GPSR using a rigorous metrics analysis regarding QoS and quality of experience. Our extensive experimental results using several simulators (e.g., NS-2, VanetMobiSim and Evalvid), show that FzGR has the ability to increase the performance of the network.

     

Prediction of onset of boundary layer transition in film condensation on a horizontal elliptical cylinder

This article is devoted to a numerical study of prediction of the onset of the boundary layer transition in film condensation of pure saturated vapor on a horizontal elliptical tube, under the simultaneous effects of gravity, shear stress, and the imposed pressure gradients, caused by the vapor flow and curvature, on the condensate film. The inertia and convection terms are retained in the analysis. The hypothesis of Shekriladze and Gomelauri is used at the liquid-vapor interface. Outside the boundary layer, the vapor phase velocity is obtained from potential flow. Temperature, velocity distribution, and dimensionless apparent turbulent stress of the fully developed flow are carried out using the implicit Keller method. The effects of pressure gradients characterized by Froude number, ellipticity, and Bond number on the transition position have been evaluated. The transition criterion has been given in terms of the critical film Reynolds number ( {\bf Re}_{\bGamma} ) C .     

High accuracy localization method using AoA in sensor networks

In sensor networks, several applications such as habitat monitoring and moving objects tracking, require the knowledge of nodes positions. Position estimation most often includes errors due to the measurements of distance and incoming angles between neighbors. Erroneous positions are propagated from a node to other nodes exacerbating the degree of errors in the estimation of the positions of these nodes. In this paper, we propose a new localization method, called HA-A2L (High Accuracy localization based on Angle to Landmark); it consists of (a) a new protocol that allows nodes to exchange information pertinent to the localization process; and (b) a localization algorithm that uses estimation of distances and incoming angles to locate nodes in sensors networks. Compared, via simulations, to previous methods, such as APS and A2L, HA-A2L considerably increases the number of located nodes with far better accuracy.     

Reinforcement learning based routing in wireless mesh networks

This paper addresses the problem of efficient routing in backbone wireless mesh networks (WMNs) where each mesh router is equipped with multiple radio interfaces and a subset of nodes serve as gateways to the Internet. Most routing schemes have been designed to reduce routing costs by optimizing one metric, e.g., hop count and interference ratio. However, when considering these metrics together, the complexity of the routing problem increases drastically. Thus, an efficient and adaptive routing scheme that takes into account several metrics simultaneously and considers traffic congestion around the gateways is needed. In this paper, we propose an adaptive scheme for routing traffic in WMNs, called Reinforcement Learning-based Distributed Routing (RLBDR), that (1) considers the critical areas around the gateways where mesh routers are much more likely to become congested and (2) adaptively learns an optimal routing policy taking into account multiple metrics, such as loss ratio, interference ratio, load at the gateways and end-to end delay. Simulation results show that RLBDR can significantly improve the overall network performance compared to schemes using either Metric of Interference and Channel switching, Best Path to Best Gateway, Expected Transmission count, nearest gateway (i.e., shortest path to gateway) or load at gateways as a metric for path selection.     

Confocal imaging of chromatographic fouling under flow conditions

BACKGROUND: The fouling impact of selected fouling species was assessed by utilising confocal scanning laser microscopy (CSLM) to image a packed chromatographic bed during operation. A custom‐made flow cell was packed with Q Sepharose FF and loaded with partially clarified E. coli homogenate. Selective, multicoloured fluorescent dyes were used to label a bovine serum albumin (BSA) test protein (Cy5.5), dsDNA (PicoGreen) and host cell proteins (HCPs) (Cy3). The fouling caused by the various fluorescently labelled components was visualised as a result of the fluorescence emitted by the PicoGreen‐labelled dsDNA and the Cy3‐labelled protein in the foulant stream, and by testing the adsorptive capacity of a test protein (BSA) onto the resin prior to and post‐fouling as well as following the application of a common CIP procedure. RESULTS: Values for the effective diffusivity of BSA (D_e) were derived from the confocal images and the fouling impact was assessed by comparing D_e values obtained from different fouling scenarios. Under the most extreme conditions examined, fouling caused a 20% reduction in capacity compared to a fresh bed. BSA diffusivity did not appear to be affected by the fouling conditions studied. Sequential CIP using 15 CVs of 1 mol L^?1 NaCl then 15 CVs of 1 mol L^?1 NaOH was shown to be effective in removing nucleic acids and HCPs. Subsequent BSA adsorption showed that the CIP regime successfully restored the column capacity to its original value. In contrast, 15 CVs of 1 mol L^?1 NaCl were ineffective in removing dsDNA but substantially removed HCPs. CONCLUSION: CSLM was demonstrated to be a useful tool for visualising fouling mechanisms. Comparing the results obtained by this technique using different modes of chromatographic operation provided insights into the fouling characteristics of finite baths versus packed beds. Copyright © 2007 Society of Chemical Industry     

Reliability bounds and direct computation of the reliability of a consecutive k-out-of-n:F system with Markov dependence

We propose bounds and direct computation of the reliability of a consecutive k-out-of-n:F system, in the case where each component can have only two states (good or failed) and the sequence of the states of the components forms a Markovian chain. Some interesting deterministic properties are also given.