Fuzzy Controller Based QoS Routing Algorithm with a Multiclass Scheme for MANET

A mobile ad hoc network (MANET) consists of a set of mobile hosts that can communicate with each other without the assistance of base stations. Due to the dynamic nature of the network topology and restricted resources, quality of service (QoS) and multicast routing in MANET are challenging tasks which attract the interests of many people. In this paper, we present a fuzzy controller based QoS routing algorithm with a multiclass scheme (FQRA) in mobile ad hoc networks. The performance of this scheduler is studied using NS2 (Network Simulator version 2) and evaluated in terms of quantitative measures such as packet delivery ratio, path success ratio and average end-to-end delay. Simulations show that the approach is efficient, promising and applicable in ad hoc networks

Quality of Service for Multimedia and Control System Applications in Mobile Ad-hoc Network

A Mobile Ad-Hoc Network (MANET) is a collection of randomly distributed infrastructure-less mobile nodes that form a wireless network. These Mobile nodes have the capability to act as a host or relay. As a host, the mobile nodes can be the source and/or destination of traffic, and when acting as a relay, they can be an intermediate node that forwards the traffic to its destination. Some of the challenges of a MANET include the dynamic network topology, device discovery, power constraints, wireless channel conditions and limited network resources. These challenges degrade the network performance and thus affect the network stability and robustness. Therefore, it is difficult for a MANET to attain the Quality of Service (QoS) of a wired network. This thesis aims to address the problem of the limited wireless network resources by proposing two adaptive scheduling algorithms that can adapt in real-time to the changes in the network. To achieve the aim; this thesis first analyses the behaviour of various application profiles in a queue. It models Voice, Email, and Internet Browsing traffic (by specifying packet sizes, and inter-arrival rates based on various distributions) separately and then simultaneously in a common network for uncongested and congested conditions, after which scheduling is applied in order to improve the overall network performance. The Voice traffic profile is then added to the UDP/IP protocol stack and the network performance is compared to a simple node without the UDP/IP protocol stack. A realistic wireless propagation model for the simulation is developed from a point-to-point open-field outdoor experiment. This thesis proposes two adaptive priority fuzzy based scheduler for a MANET, the priority of packets in the queue are determined based on the real-time available network resources. The methodology for transmitting a live-feed video stream over OPNET to validate the scheduler is also presented. An interface between the simulation and hardware is created to send real-time video traffic through the simulation network. This thesis concludes by showing that the performance of a MANET network can be improved by applying an adaptive scheduler

Supporting Protocols for Structuring and Intelligent Information Dissemination in Vehicular Ad Hoc Networks

The goal of this dissertation is the presentation of supporting protocols for structuring and intelligent data dissemination in vehicular ad hoc networks (VANETs). The protocols are intended to first introduce a structure in VANETs, and thus promote the spatial reuse of network resources. Segmenting a flat VANET in multiple cluster structures allows for more efficient use of the available bandwidth, which can effectively increase the capacity of the network. The cluster structures can also improve the scalability of the underlying communication protocols. The structuring and maintenance of the network introduces additional overhead. The aim is to provide a mechanism for creating stable cluster structures in VANETs, and to minimize this associated overhead. Further a hybrid overlay-based geocast protocol for VANETs is presented. The protocol utilizes a backbone overlay virtual infrastructure on top of the physical network to provide geocast support, which is crucial for intervehicle communications since many applications provide group-oriented and location-oriented services. The final contribution is a structureless information dissemination scheme which creates a layered view of road conditions with a diminishing resolution as the viewing distance increases. Namely, the scheme first provides a high-detail local view of a given vehicle\u27s neighbors and its immediate neighbors, which is further extended when information dissemination is employed. Each vehicle gets aggregated information for road conditions beyond this extended local view. The scheme allows for the preservation of unique reports within aggregated frames, such that safety critical notifications are kept in high detail, all for the benefit of the driver\u27s improved decision making during emergency scenarios

Cognitive virtual ad hoc mobile cloud-based networking architecture

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University LondonThis thesis proposed cognitive techniques and intelligent algorithms that offered adaptive and advanced facilities to cloud-based networking by using Virtual Ad Hoc Mobile Cloud Computing Networks architecture (VAMCCNs). This is presented as a working case to address their global network challenges and to add cognitive support to the network design and implementation for better meeting traffic management and application requirements in mission objectives. The thesis concentrates on three main contributions. Firstly, an adaptive model, namely: a Heterogeneous Mobile Cloud Computing Network (HMCCN), was proposed to integrate different cloud networks architectures into one workflow. The cognitive data offloading task and the routing decision methods were applied using two different approaches: Fuzzy Analytic Hierarchy system (FAH) as a first approach and cognitive Software Defined Network (SDN) model as a second centralised approach. Experimental results show improvement in network reliability and throughputs, minimised in both nodes’ energy consumption and network latency with efficient intelligent data load balance and network resources allocation with best cloud model selection. Secondly, based on a virtual Ad Hoc cloud network with a realistic Random Waypoint Motion (RWM) model, an innovative cognitive routing algorithm was presented to improve efficient and reliable route selection among multiple possible routes. Routing protocols based on conventional, Fuzzy logic used important parameters with two data collections and decisions techniques and a new adaptive Intelligent Hybrid Fuzzy-Neural routing protocol (IHFN) that included prior knowledge to the network of the underlying motion and energy parameters were all proposed and compared. Results with the new hybrid algorithm shown a significant improvement to solve the network end-to-end performance degradation problem. The new hybrid protocol improved network throughput with an average of 20% higher than traditional Ad Hoc On-Demand Distance Vector (AODV) Routing protocol, improved the usage of network resources and reduced the maintenance process in adynamic topologies network. Finally, based on datasets collected from a realistic motion RWM model in a virtual Ad Hoc cloud network, the performance behaviour of six selected deep learning algorithms to predict the next steps of positions, speed and residual battery energy values of these mobile nodes have been evaluated and compared. This work goes further by presenting two algorithm's training techniques to predict the next 300-time steps of position, speed, and energy. Results and dissuasion show the differences concerning prediction accuracy between using the single node dataset model or Multiple node's dataset model

Formulations and identification of algorithmic solutions for enabling opportunistic networks - M4.1

Milestone M4.1 del projecte Europeu OneFIT (ICT-2009-257385).This document contains a detailed description of the algorithms to be implemented to manage the opportunistic networks. There are defined according to the functional and system architecture (WP2) to fulfil the technical challenges. These algorithms will implemented during the WP4.2 and validated during the WP4.3Postprint (published version

Formulation, implementation considerations, and first performance evaluation of algorithmic solutions - D4.1

Deliverable D4.1 del projecte Europeu OneFIT (ICT-2009-257385)This deliverable contains a first version of the algorithmic solutions for enabling opportunistic networks. The presented algorithms cover the full range of identified management tasks: suitability, creation, QoS control, reconfiguration and forced terminations. Preliminary evaluations complement the proposed algorithms. Implementation considerations towards the practicality of the considered algorithms are also included.Preprin

Mobile Ad-Hoc Networks

Being infrastructure-less and without central administration control, wireless ad-hoc networking is playing a more and more important role in extending the coverage of traditional wireless infrastructure (cellular networks, wireless LAN, etc). This book includes state-of-the-art techniques and solutions for wireless ad-hoc networks. It focuses on the following topics in ad-hoc networks: quality-of-service and video communication, routing protocol and cross-layer design. A few interesting problems about security and delay-tolerant networks are also discussed. This book is targeted to provide network engineers and researchers with design guidelines for large scale wireless ad hoc networks

Enhancing service quality and reliability in intelligent traffic system

Intelligent Traffic Systems (ITS) can manage on-road traffic efficiently based on real-time traffic conditions, reduce delay at the intersections, and maintain the safety of the road users. However, emergency vehicles still struggle to meet their targeted response time, and an ITS is vulnerable to various types of attacks, including cyberattacks. To address these issues, in this dissertation, we introduce three techniques that enhance the service quality and reliability of an ITS. First, an innovative Emergency Vehicle Priority System (EVPS) is presented to assist an Emergency Vehicle (EV) in attending the incident place faster. Our proposed EVPS determines the proper priority codes of EV based on the type of incidents. After priority code generation, EVPS selects the number of traffic signals needed to be turned green considering the impact on other vehicles gathered in the relevant adjacent cells. Second, for improving reliability, an Intrusion Detection System for traffic signals is proposed for the first time, which leverages traffic and signal characteristics such as the flow rate, vehicle speed, and signal phase time. Shannon’s entropy is used to calculate the uncertainty associated with the likelihood of particular evidence and Dempster-Shafer (DS) decision theory is used to fuse the evidential information. Finally, to improve the reliability of a future ITS, we introduce a model that assesses the trust level of four major On-Board Units (OBU) of a self-driving car along with Global Positioning System (GPS) data and safety messages. Both subjective logic (DS theory) and CertainLogic are used to develop the theoretical underpinning for estimating the trust value of a self-driving car by fusing the trust value of four OBU components, GPS data and safety messages. For evaluation and validation purposes, a popular and widely used traffic simulation package, namely Simulation of Urban Mobility (SUMO), is used to develop the simulation platform using a real map of Melbourne CBD. The relevant historical real data taken from the VicRoads website were used to inject the traffic flow and density in the simulation model. We evaluated the performance of our proposed techniques considering different traffic and signal characteristics such as occupancy rate, flow rate, phase time, and vehicle speed under many realistic scenarios. The simulation result shows the potential efficacy of our proposed techniques for all selected scenarios.Doctor of Philosoph