QoS routing in ad-hoc networks using GA and multi-objective optimization

Much work has been done on routing in Ad-hoc networks, but the proposed routing solutions only deal with the best effort data traffic. Connections with Quality of Service (QoS) requirements, such as voice channels with delay and bandwidth constraints, are not supported. The QoS routing has been receiving increasingly intensive attention, but searching for the shortest path with many metrics is an NP-complete problem. For this reason, approximated solutions and heuristic algorithms should be developed for multi-path constraints QoS routing. Also, the routing methods should be adaptive, flexible, and intelligent. In this paper, we use Genetic Algorithms (GAs) and multi-objective optimization for QoS routing in Ad-hoc Networks. In order to reduce the search space of GA, we implemented a search space reduction algorithm, which reduces the search space for GAMAN (GA-based routing algorithm for Mobile Ad-hoc Networks) to find a new route. We evaluate the performance of GAMAN by computer simulations and show that GAMAN has better behaviour than GLBR (Genetic Load Balancing Routing).Peer ReviewedPostprint (published version

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

Multi-objective routing optimization using evolutionary algorithms

Wireless ad hoc networks suffer from several limitations, such as routing failures, potentially excessive bandwidth requirements, computational constraints and limited storage capability. Their routing strategy plays a significant role in determining the overall performance of the multi-hop network. However, in conventional network design only one of the desired routing-related objectives is optimized, while other objectives are typically assumed to be the constraints imposed on the problem. In this paper, we invoke the Non-dominated Sorting based Genetic Algorithm-II (NSGA-II) and the MultiObjective Differential Evolution (MODE) algorithm for finding optimal routes from a given source to a given destination in the face of conflicting design objectives, such as the dissipated energy and the end-to-end delay in a fully-connected arbitrary multi-hop network. Our simulation results show that both the NSGA-II and MODE algorithms are efficient in solving these routing problems and are capable of finding the Pareto-optimal solutions at lower complexity than the ’brute-force’ exhaustive search, when the number of nodes is higher than or equal to 10. Additionally, we demonstrate that at the same complexity, the MODE algorithm is capable of finding solutions closer to the Pareto front and typically, converges faster than the NSGA-II algorithm

Optimisation of Mobile Communication Networks - OMCO NET

The mini conference “Optimisation of Mobile Communication Networks” focuses on advanced methods for search and optimisation applied to wireless communication networks. It is sponsored by Research & Enterprise Fund Southampton Solent University. The conference strives to widen knowledge on advanced search methods capable of optimisation of wireless communications networks. The aim is to provide a forum for exchange of recent knowledge, new ideas and trends in this progressive and challenging area. The conference will popularise new successful approaches on resolving hard tasks such as minimisation of transmit power, cooperative and optimal routing

Polycyclic aromatic hydrocarbons biodegradation using isolated strains under indigenous condition

The treatment and disposal of domestic sIudge is an expensive and environmentally sensitive problem. It is also a growing problem since sludge production will continue to increase as new wastewzter treatment plants are built due to population increase. The large volume of domestic sIudge produced had made it difficult for many countries including Malaysia to assure complete treatment of the sludge before discharging to the receiving environment. Domestic sludge contains diverse range of pollutants such as pathogen, inorganic and organic compounds. These pollutants are toxic, mutagenic or carcinogenic and may threaten human health. Iiilproper disposal and handling of sludge may pose serious impact to the environment especially on soil and water cycles. Previous studies on Malaysian domestic sludge only reported on bulk parameters and heavy metals. Thus, no study reported on organic micro pollutants, namely, polycylic aromatic hydrocarbons (PAHs). Their recalcitrance and persistence make them problematic environmental contaminants. Microbial degradation is considered to be the primary mechanism of PAHs removal from the environment. Much has been reported on biodegradation of PAHs in several countries but there is a lack of information quantitative on this subject in Malaysia. This study is carried out to understand the nature of domestic sludge and to provide a better understanding on the biodegradation processes of PAHs. The methodology of this study comprised field activities, laboratory work and mathematical modelling. Field activities involved sampling of domestic sludge from Kolej Mawar, Universiti Teknologi MARA, Shah Alam, Selangor. Laboratory activities include seven phases of experimental works. First phase is characterization study of domestic sludge based on bulk parameters, heavy metals and PAHs. Second phase is enrichment and purification of bacteria isolated from domestic sludge using single PAHs and mixed PAHs as growth substrate. This was followed by identification of bacteria using BIOLOG system. The fourth phase focussed on turbidity test to monitor growth rate of the isolated bacteria. Preliminary degradation study involves optimization of the process at different substrate concentration, bacteria concentration, pH and temperature. The optimum conditions established from optimization study were used in degradation study. In biodegradation study, two experimental conditions were performed. These conditions include using bacteria isolated from single PAHs as substrate and bacteria isolated from mixed PAHs. Protein and pH tests were done during degradation study. Final activity is mathematical modelling of the biodegradation process. In general results on bulk parameters are comparable to previous studies. Zinc was the main compound with a mean concentration of 11 96.4 mglkg. PAHs were also detected in all of the samples, with total concentration between 0.72 to 5.36 mglkg dry weight for six PAHs. In the examined samples, phenanthrene was the main compound with a mean concentration of 1.0567 mglkg. The results fiom purification studies of bacteria strains sucessfull isolated 13 bacteria strains fiom single PAH substrate while three bacteria were isolated from the mixed PAHs substrate. Based on bacteria growth rates, only six strains grown on single PAHs and three strains grown on mixed PAHs were used for further studies. Results from the optimization study of biodegradation indicated that maximum rate of PAHs removal occurred at 100 mg~-' of PAHs, 10% bacteria concentration, pH 7.0 and 30°C. The results showed that bacteria grown on lower ring of PAHs are not able to grow on higher ring of PAHs. As for example Micrococcus diversus grown on napthalene as sole carbon source was unable to degrade other PAHs like acenapthylene, acenapthene, fluorene, phenanthrene and antlracene. In the case of bacteria isolated from mixed PAHs, the results showed that most of the napthalene was degraded by isolated strains with the highest average degradation rate followed by acenapthylene, acenapthene, fluorene, phenanthrene and anthracene. 377$3(53867$.$$1�781.8�781�$0,1$+ D4ff + c\,cpda~ition trends were observed in the study could be attributed to the different subsr , i,lo\~ir 'Led during isolation process. Interaction through cometabolism and synergistic ocolq bacteria strains isolated from single substrate. Thus, only synergistic interaction was oL, :a 77ed for bacteria isolated from mixed substrate. Corynebacterium urolyticum re\e;;ed I,, be the best strain in degrading PAHs. The experimental results have led to a model conccl~t desclibing I'AHs degradation

QoS multicast tree construction in IP/DWDM optical internet by bio-inspired algorithms

Copyright @ Elsevier Ltd. All rights reserved.In this paper, two bio-inspired Quality of Service (QoS) multicast algorithms are proposed in IP over dense wavelength division multiplexing (DWDM) optical Internet. Given a QoS multicast request and the delay interval required by the application, both algorithms are able to find a flexible QoS-based cost suboptimal routing tree. They first construct the multicast trees based on ant colony optimization and artificial immune algorithm, respectively. Then a dedicated wavelength assignment algorithm is proposed to assign wavelengths to the trees aiming to minimize the delay of the wavelength conversion. In both algorithms, multicast routing and wavelength assignment are integrated into a single process. Therefore, they can find the multicast trees on which the least wavelength conversion delay is achieved. Load balance is also considered in both algorithms. Simulation results show that these two bio-inspired algorithms can construct high performance QoS routing trees for multicast applications in IP/DWDM optical Internet.This work was supported in part ny the Program for New Century Excellent Talents in University, the Engineering and Physical Sciences Research Council (EPSRC) of UK under Grant EP/E060722/1, the National Natural Science Foundation of China under Grant no. 60673159 and 70671020, the National High-Tech Reasearch and Development Plan of China under Grant no. 2007AA041201, and the Specialized Research Fund for the Doctoral Program of Higher Education under Grant no. 20070145017

Natural computing for vehicular networks

La presente tesis aborda el diseño inteligente de soluciones para el despliegue de redes vehiculares ad-hoc (vehicular ad hoc networks, VANETs). Estas son redes de comunicación inalámbrica formada principalmente por vehículos y elementos de infraestructura vial. Las VANETs ofrecen la oportunidad para desarrollar aplicaciones revolucionarias en el ámbito de la seguridad y eficiencia vial. Al ser un dominio tan novedoso, existe una serie de cuestiones abiertas, como el diseño de la infraestructura de estaciones base necesaria y el encaminamiento (routing) y difusión (broadcasting) de paquetes de datos, que todavía no han podido resolverse empleando estrategias clásicas. Es por tanto necesario crear y estudiar nuevas técnicas que permitan de forma eficiente, eficaz, robusta y flexible resolver dichos problemas. Este trabajo de tesis doctoral propone el uso de computación inspirada en la naturaleza o Computación Natural (CN) para tratar algunos de los problemas más importantes en el ámbito de las VANETs, porque representan una serie de algoritmos versátiles, flexibles y eficientes para resolver problemas complejos. Además de resolver los problemas VANET en los que nos enfocamos, se han realizado avances en el uso de estas técnicas para que traten estos problemas de forma más eficiente y eficaz. Por último, se han llevado a cabo pruebas reales de concepto empleando vehículos y dispositivos de comunicación reales en la ciudad de Málaga (España). La tesis se ha estructurado en cuatro grandes fases. En la primera fase, se han estudiado los principales fundamentos en los que se basa esta tesis. Para ello se hizo un estudio exhaustivo sobre las tecnologías que emplean las redes vehiculares, para así, identificar sus principales debilidades. A su vez, se ha profundizado en el análisis de la CN como herramienta eficiente para resolver problemas de optimización complejos, y de cómo utilizarla en la resolución de los problemas en VANETs. En la segunda fase, se han abordado cuatro problemas de optimización en redes vehiculares: la transferencia de archivos, el encaminamiento (routing) de paquetes, la difusión (broadcasting) de mensajes y el diseño de la infraestructura de estaciones base necesaria para desplegar redes vehiculares. Para la resolución de dichos problemas se han propuesto diferentes algoritmos CN que se clasifican en algoritmos evolutivos (evolutionary algorithms, EAs), métodos de inteligencia de enjambre (swarm intelligence, SI) y enfriamiento simulado (simulated annealing, SA). Los resultados obtenidos han proporcionado protocolos de han mejorado de forma significativa las comunicaciones en VANETs. En la tercera y última fase, se han realizado experimentos empleando vehículos reales circulando por las carreteras de Málaga y que se comunicaban entre sí. El principal objetivo de estas pruebas ha sido el validar las mejoras que presentan los protocolos que se han optimizado empleando CN. Los resultados obtenidos de las fases segunda y tercera confirman la hipótesis de trabajo, que la CN es una herramienta eficiente para tratar el diseño inteligente en redes vehiculares