QoS routing optimization strategy using genetic algorithm in optical fiber communication networks

Abstract This paper describes the routing problems in optical ber networks, denes ve constraints, induces and simplies the evaluation function and tness function, and proposes a routing approach based on the genetic algorithm, which includes an operator [OMO] to solve the QoS routing problem in optical ber communication networks. The simulation results show that the proposed routing method by using this optimal maintain operator genetic algorithm (OMOGA) is superior to the common genetic algorithms (CGA). It not only is robust and eÆcient but also converges quickly and can be carried out simply, that makes it better than other complicated GA. Keywords genetic algorithm, optimal maintain operator (OMO), optical ber communication network

An evolutionary approach to routing in mobile AD HOC networks using dominating sets.

This thesis presents a new approach to routing in ad-hoc wireless networks using virtual backbones that may be approximated by the graph theoretic concept of dominating sets. · Ad hoc wireless networks provide a flexible and quick means of establishing wireless peer-to-peer communications. Routing remains the main challenging problem in an ad hoc network due to its multihop nature and dynamic network topology. Several protocols based on virtual backbones in ad hoc wireless networks have been proposed that may be used to simplify the routing process. However, little is known about the network routing performance of these protocols and no attempt has previously been made to directly compare them. This thesis is the first research effort to implement, analyze and compare the routing performance of dominating-set-based routing protocols. In this study, we examine four existing routing approaches using a virtual backbone, or spine , imposed on the ad­hoc network. We then propose an evolutionary approach to constructing a stable minimum connected dominating set in an ad hoc wireless network: this employs the use of a genetic algorithm. Since the mobile· nodes that constitute an ad hoc wireless network are constantly in motion, the network configuration is subject to constant change in a manner that resembles the biological process of mutation. This evolution of networks over time lends itself naturally to a model based on genetic algorithms. As part of an in-depth study of the application of genetic algorithms in the field of wireless networks, a scatternet formation protocol for Bluetooth networks was designed, developed and evaluated. This helped to build the knowledge base required to implement new routing protocols using the network simulator ns-2. Simulation studies were then conducted using ns-2 to compare the performance of previously proposed dominating­set-based routing approaches. In this thesis, we analyze the performance of our evolutionary routing approach and compare it with the previous approaches. We present our simulation results and show that our evolutionary routing approach outperforms the other routing algorithms with respect to end-to-end packet delay, throughput, packet delivery ratio and routing overhead· across several different scenarios. Thus, we demonstrate the advantages of utilizing a genetic algorithm to construct a backbone that is · used to effectively route packets in an ad-hoc wireless network

Genetic algorithms with immigrants and memory schemes for dynamic shortest path routing problems in mobile ad hoc networks

This article is posted here with permission of IEEE - Copyright @ 2010 IEEEIn recent years, the static shortest path (SP) problem has been well addressed using intelligent optimization techniques, e.g., artificial neural networks, genetic algorithms (GAs), particle swarm optimization, etc. However, with the advancement in wireless communications, more and more mobile wireless networks appear, e.g., mobile networks [mobile ad hoc networks (MANETs)], wireless sensor networks, etc. One of the most important characteristics in mobile wireless networks is the topology dynamics, i.e., the network topology changes over time due to energy conservation or node mobility. Therefore, the SP routing problem in MANETs turns out to be a dynamic optimization problem. In this paper, we propose to use GAs with immigrants and memory schemes to solve the dynamic SP routing problem in MANETs. We consider MANETs as target systems because they represent new-generation wireless networks. The experimental results show that these immigrants and memory-based GAs can quickly adapt to environmental changes (i.e., the network topology changes) and produce high-quality solutions after each change.This work was supported by the Engineering and Physical Sciences Research Council of U.K. underGrant EP/E060722/

Joint QoS multicast routing and channel assignment in multiradio multichannel wireless mesh networks using intelligent computational methods

Copyright @ 2010 Elsevier B.V. All rights reserved.In this paper, the quality of service multicast routing and channel assignment (QoS-MRCA) problem is investigated. It is proved to be a NP-hard problem. Previous work separates the multicast tree construction from the channel assignment. Therefore they bear severe drawback, that is, channel assignment cannot work well with the determined multicast tree. In this paper, we integrate them together and solve it by intelligent computational methods. First, we develop a unified framework which consists of the problem formulation, the solution representation, the fitness function, and the channel assignment algorithm. Then, we propose three separate algorithms based on three representative intelligent computational methods (i.e., genetic algorithm, simulated annealing, and tabu search). These three algorithms aim to search minimum-interference multicast trees which also satisfy the end-to-end delay constraint and optimize the usage of the scarce radio network resource in wireless mesh networks. To achieve this goal, the optimization techniques based on state of the art genetic algorithm and the techniques to control the annealing process and the tabu search procedure are well developed separately. Simulation results show that the proposed three intelligent computational methods based multicast algorithms all achieve better performance in terms of both the total channel conflict and the tree cost than those comparative references.This work was supported by the Engineering and Physical Sciences Research Council (EPSRC) of UK under Grant EP/E060722/1