26,833 research outputs found

    Secure and robust multi-constrained QoS aware routing algorithm for VANETs

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    Secure QoS routing algorithms are a fundamental part of wireless networks that aim to provide services with QoS and security guarantees. In Vehicular Ad hoc Networks (VANETs), vehicles perform routing functions, and at the same time act as end-systems thus routing control messages are transmitted unprotected over wireless channels. The QoS of the entire network could be degraded by an attack on the routing process, and manipulation of the routing control messages. In this paper, we propose a novel secure and reliable multi-constrained QoS aware routing algorithm for VANETs. We employ the Ant Colony Optimisation (ACO) technique to compute feasible routes in VANETs subject to multiple QoS constraints determined by the data traffic type. Moreover, we extend the VANET-oriented Evolving Graph (VoEG) model to perform plausibility checks on the exchanged routing control messages among vehicles. Simulation results show that the QoS can be guaranteed while applying security mechanisms to ensure a reliable and robust routing service

    An ACO Algorithm for Effective Cluster Head Selection

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    This paper presents an effective algorithm for selecting cluster heads in mobile ad hoc networks using ant colony optimization. A cluster in an ad hoc network consists of a cluster head and cluster members which are at one hop away from the cluster head. The cluster head allocates the resources to its cluster members. Clustering in MANET is done to reduce the communication overhead and thereby increase the network performance. A MANET can have many clusters in it. This paper presents an algorithm which is a combination of the four main clustering schemes- the ID based clustering, connectivity based, probability based and the weighted approach. An Ant colony optimization based approach is used to minimize the number of clusters in MANET. This can also be considered as a minimum dominating set problem in graph theory. The algorithm considers various parameters like the number of nodes, the transmission range etc. Experimental results show that the proposed algorithm is an effective methodology for finding out the minimum number of cluster heads.Comment: 7 pages, 5 figures, International Journal of Advances in Information Technology (JAIT); ISSN: 1798-2340; Academy Publishers, Finlan

    Optimisation of Mobile Communication Networks - OMCO NET

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    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

    FastM: Design and Evaluation of a Fast Mobility Mechanism for Wireless Mesh Networks

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    Although there is a large volume of work in the literature in terms of mobility approaches for Wireless Mesh Networks, usually these approaches introduce high latency in the handover process and do not support realtime services and applications. Moreover, mobility is decoupled from routing, which leads to inefficiency to both mobility and routing approaches with respect to mobility. In this paper we present a new extension to proactive routing protocols using a fast mobility extension, FastM, with the purpose of increasing handover performance in Wireless Mesh Networks. With this new extension, a new concept is created to integrate information between neighbor wireless mesh routers, managing locations of clients associated to wireless mesh routers in a certain neighborhood, and avoiding packet loss during handover. The proposed mobility approach is able to optimize the handover process without imposing any modifications to the current IEE 802.11 MAC protocol and use unmodified clients. Results show the improved efficiency of the proposed scheme: metrics such as disconnection time, throughput, packet loss and control overhead are largely improved when compared to previous approaches. Moreover, these conclusions apply to mobility scenarios, although mobility decreases the performance of the handover approach, as expected

    Un modelo para resolver el problema dinĂĄmico de despacho de vehĂ­culos con incertidumbre de clientes y con tiempos de viaje en arcos

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    IndexaciĂłn: Web of Science; ScieloIn a real world case scenario, customer demands are requested at any time of the day requiring services that are not known in advance such as delivery or repairing equipment. This is called Dynamic Vehicle Routing (DVR) with customer uncertainty environment. The link travel time for the roadway network varies with time as traffic fluctuates adding an additional component to the dynamic environment. This paper presents a model for solving the DVR problem while combining these two dynamic aspects (customer uncertainty and link travel time). The proposed model employs Greedy, Insertion, and Ant Colony Optimization algorithms. The Greedy algorithm is utilized for constructing new routes with existing customers, and the remaining two algorithms are employed for rerouting as new customer demands appear. A real world application is presented to simulate vehicle routing in a dynamic environment for the city of Taipei, Taiwan. The simulation shows that the model can successfully plan vehicle routes to satisfy all customer demands and help managers in the decision making process.En un escenario real, los pedidos de los clientes son solicitados a cualquier hora del dĂ­a requiriendo servicios que no han sido planificados con antelaciĂłn tales como los despachos o la reparaciĂłn de equipos. Esto es llamado ruteo dinĂĄmico de vehĂ­culos (RDV) considerando un ambiente con incertidumbre de clientes. El tiempo de viaje en una red vial varĂ­a con el tiempo a medida que el trĂĄfico vehicular fluctĂșa agregando una componente adicional al ambiente dinĂĄmico. Este artĂ­culo propone un modelo para resolver el problema RDV combinando estos dos aspectos dinĂĄmicos. El modelo propuesto utiliza los algoritmos Greedy, InserciĂłn y optimizaciĂłn basada en colonias de hormigas. El algoritmo Greedy es utilizado para construir nuevas rutas con los clientes existentes y los otros dos algoritmos son usados para rutear vehĂ­culos a medida que surjan nuevos clientes con sus respectivos pedidos. AdemĂĄs, se presenta una aplicaciĂłn real para simular el ruteo vehicular en un ambiente dinĂĄmico para la ciudad de Taipei, TaiwĂĄn. Esta simulaciĂłn muestra que el modelo es capaz de planificar exitosamente las rutas vehiculares satisfaciendo los pedidos de los clientes y de ayudar los gerentes en el proceso de toma de decisiones.http://ref.scielo.org/3ryfh

    FUNNet:a novel biologically-inspired routing algorithm based on fungi

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    Future data communication networks show three emerging trends: increasing size of networks, increasing traffic volumes and dynamic network topologies. Efficient network management solutions are required that are scalable, can cope with large, and increasing, traffic volumes and provide decentralised and adaptive routing strategies that cope with the dynamics of the network topology. Routing strategies are an important aspect of network management as they have a significant influence on the overall network performance. This paper introduces the preliminary studies for FUNNet, a new routing algorithm inspired by the kingdom of Fungi. Fungi form robust, resilient and responsive networks and these networks change topology as a consequence of changes in local conditions. Fungi are capable of expanding in size as they self-regulate and optimise the balance between exploration and exploitation which is dependent on the transport of the internal resource, i.e. ‘traffic’, within the network. FUNNet exploits the biological processes that are responsible for simulating fungal networks in a bio-inspired routing protocol. The initial results are positive and suggest that fungal metaphors can improve network management, although further evaluation of more complex scenarios is required
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