Guillaume Noel

Network coding and competitive approach for gradient based routing in wireless sensor networks

Energy efficiency is a key design criterion for routing protocols in wireless sensor networks since sensor nodes are strongly constrained in terms of energy supply. Gradient-Based Routing (GBR) is a well known energy efficient routing protocol that is used in WSNs. However, there exist shortcomings in the GBR scheme such as: (1) sinks make use of flooding to broadcast interest messages which leads to a lot of duplication packets which are transmitted. This leads to the waste of a lot of energy in the network and (2) nodes deliver messages in a point to point manner. As a result, the potential of data retransmissions in the network is high due to the unstable network environment in WSNs. In this study, network coding and a competitive approach are proposed to solve the above two problems. Firstly, an energy efficient broadcast algorithm using network coding for GBR (GBR-NC) is proposed. This algorithm aims to reduce network traffic, and furthermore, reduce the energy consumption and prolong the lifetime of the network. Secondly, two competing algorithms (GBR-C and auto-adaptable GBR-C) are proposed for GBR. The basic idea of the proposed competing algorithms is to reduce the retransmission attempts and save the energy by considering two forward candidates. Simulation results show that the proposed schemes give better results when compared to the traditional GBR in terms of energy efficiency.

Bilateral mesh filtering

The paper presents a new graph-based implementation of bilateral filtering. Based on the Laplacian mesh smoothing framework, the proposed filter mimics the behaviour of the classical mesh filter while retaining some of the interesting properties of mesh smoothing. The comparison between the filters is twofold. First of all, the two filters are benchmarked according to their ability to denoise complex synthetic image transitions. The respective performance of the filters are then assessed in a multiresolution denoising scheme for grayscale images, combining wavelet decomposition, shrinkage and bilateral filtering. The results obtained are encouraging and shows that the BMF is a viable alternative to classical bilateral filtering.

IP Mobility Support: Solutions for Vehicular Networks

Internet potocol (IP) mobility support is one of the major challenges in vehicular networks for intelligent transportation systems (ITS) applications. The existence of mobile nodes onboard units (OBUs) exhibiting rapid changes in both speed and direction in the presence of static nodes (roadside units) presents a complex wireless network environment. Satisfactory levels of quality of service (QoS) can be attained by requiring efficient mobility support in terms of session and service continuity. This article provides a latest survey of the major IP mobility support solutions that have been proposed for vehicular networks. An overview of vehicular network communications is also presented. Thereafter, key aspects of IP addressing and handovers in vehicular networks are discussed. Many state-of-the-art IP mobility support solutions proposed by different researchers are explained. Several open-research challenges concerning IP mobility support for vehicular networks are highlighted.

Coupled interference based rate adaptation in ad hoc networks

Link adaptation provides an efficient and flexible strategy to adapt transmission rates based on channel conditions. To attain distributed optimal local and global utility, network interference need to be mitigated therein allowing the users to transmit at the minimum transmission power enough to sustain connectivity. This paper proposes coupled interference network utility maximization (NUM) strategy (i.e., CIN) for rate adaptation in WLANs that is solved using “reverse-engineering” based on Karush-Kuhn-Tucker (KKT) conditions. In that way, users determine data rates based on their local link observations (i.e., coupled interference). Both pricing and limited message passing mechanisms are employed in the NUM so that pricing restrict users from self-interest behaviours while limited message passing assists users to announce their prices and transmit powers. It is demonstrated theoretically that CIN satisfies the conditions of the super-modular games, thereby resulting in an optimal solution. Simulation results have shown that adapting data rates based on the link conditions can improve the performance of ad hoc networks for both stationary and mobile users.

Grid smoothing: a graph-based approach

In the past few years, mesh representation of images has attracted a lot of research interest due to its wide area of applications in image processing. In the mesh framework, an image is represented by a graph in which the nodes represent the pixels and the edges reflect the connectivity. The definition of the most adapted mesh for a given image is a challenge in terms of computation cost and information representation. In this paper, a new method for content adaptive mesh representation of gray scale images, called grid smoothing, is presented. A cost function is defined using the spatial coordinates of the nodes and the gray levels present in the image. The minimisation of the cost function leads to new spatial coordinates for each node. Using an adequate cost function, the grid is compressed in the regions with large gradient values and relaxed in the other regions. The result is a grid which better fits the objects in the image. The mathematical framework of the method is introduced in the paper. An in-depth study of the convergence is presented as well as results on real gray scale images.

Kernel-based non-linear template matching

A new non-linear minimum norm template matching technique is introduced. Similar to the theory of Support Vector Machines the proposed framework is also based on Reproducing Kernel Hilbert Space principles. Promising results when applied to aerial image matching are reported and future work is highlighted.

Fast handover management in IP-based vehicular networks

Vehicular networks, despite being an important wireless communication technology for the transmission of Intelligent Transportation System (ITS) information are faced with challenges as far as handover management is concerned. This is due to the fact that the high mobility nodes tend to have rapid wireless link connections and disconnections thereby, demanding for fast IP configurations which current mobility schemes cannot support. These result in long handover latencies and packet loss effects which consequently degrade the Quality of Service (QoS). To support seamless mobility and guarantee acceptable QoS levels, fast and smooth handovers across various subnets have to be performed for session continuity to be maintained. In this work, we propose a network layer handover scheme called Vehicular Fast handovers for Mobile IPv6 (VFMIPv6) aimed at improving the QoS in vehicular networks by minimising the handover latency, packet loss problems and overhead cost effects. The system description of the proposed solution and an analytical model are outlined. Numerical performance evaluations show that our proposed scheme out-performs the standard solutions.

An analysis of handover probability and data throughput in vehicular networks

Recently, the networking and automobile industry has witnessed the emergence of vehicular networks which were developed to provide safety and non-safety Intelligent Transportation System (ITS) applications. The provision of seamless mobility and session continuity during handovers is critical for better Quality of Service (QoS) provisioning in vehicular networks. In this paper, we propose a scheme meant to improve handover performance in IP-based vehicular networks by maximising the correct handover initiation probability and increasing data throughput during inter-subnet handovers. We analyse the effects of mobile nodes speed and direction of motion on both correct handover probability and data throughput using numerical results.

A subscriber classification approach for mobile cellular networks

Abstract The classification of subscriber types in mobile cellular networks is valuable for network service providers since it provides a mechanism to plan network services by better understanding subscriber behaviour in a network. Mobile networks contain vast repositories of data that store valuable information regarding subscriber behaviour. In this paper, a new approach for subscriber classification in mobile cellular networks is proposed. The proposed approach considers network traffic generated from a mobile cellular network operator in South Africa. The proposed approach makes use of a difference histogram approach for feature extraction and a fuzzy c-means clustering algorithm to classify traffic data into subscriber classes. To validate the proposed approach, a comparative analysis of two different multi-resolution feature extraction approaches, the empirical mode decomposition (EMD) approach and the discrete wavelet packet transform (DWPT) are compared with results obtained with the difference histogram (DH) approach. It is shown that the difference histogram provides better clustering results when compared to the two multi-resolution approaches demonstrating the potential of the difference histogram approach.

Correction of atmospheric turbulence degraded sequences using grid smoothing

Heat scintillation occurs due to the index of refraction of air decreasing with an increase in air temperature, causing objects to appear blurred and waver slowly in a quasi-periodic fashion. This imposes limitations on sensors used to record images over long distances resulting in a loss of detail in the video sequences. A method of filtering turbulent sequences using grid smoothing is presented that can be used to either extract a single geometrically improved frame or filter an entire turbulent sequence. The extracted frame is in general sharper than when utilising simple GFATR (Generalized First Average Then Register). It also better preserves edges and lines as well as being geometrically improved.