2,186 research outputs found

    QoS-Based Web Service Discovery in Mobile Ad Hoc Networks Using Swarm Strategies

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    Mobile ad hoc networks are noncentralised, multihop, wireless networks that lack a common infrastructure and hence require self-organisation. Their infrastructureless and dynamic nature entails the implementation of a new set of networking technologies in order to provide efficient end-to-end communication according to the principles of the standard TCP/IP suite. Routing, IP address autoconfiguration and Web service discovery are among the most challenging tasks in the ad hoc network domain. Swarm intelligence is a relatively new approach to problem solving that takes inspiration from the social behaviours of insects, such as ants and bees. Self-organization, decentralization, adaptivity, robustness, and scalability make swarm intelligence a successful design paradigm for the above-mentioned problems. In this paper we proposeBeeAdHocServiceDiscovery, a new service discovery algorithm based on the bee metaphor, which also takes into account quality metrics estimates. The protocol has been specifically designed to work in mobile ad hoc network scenarios operating withBeeadhoc, a well-known routing algorithm inspired by nature. We present both the protocol strategy and the formal evaluation of the discovery overhead and route optimality metrics showing thatBeeAdHocServiceDiscoveryguarantees valuable performances even in large scale ad hoc wireless networks. Eventually, future research suggestions are sketched

    Swarm intelligence and its applications to wireless ad hoc and sensor networks.

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    Swarm intelligence, as inspired by natural biological swarms, has numerous powerful properties for distributed problem solving in complex real world applications such as optimisation and control. Swarm intelligence properties can be found in natural systems such as ants, bees and birds, whereby the collective behaviour of unsophisticated agents interact locally with their environment to explore collective problem solving without centralised control. Recent advances in wireless communication and digital electronics have instigated important changes in distributed computing. Pervasive computing environments have emerged, such as large scale communication networks and wireless ad hoc and sensor networks that are extremely dynamic and unreliable. The network management and control must be based on distributed principles where centralised approaches may not be suitable for exploiting the enormous potential of these environments. In this thesis, we focus on applying swarm intelligence to the wireless ad hoc and sensor networks optimisation and control problems. Firstly, an analysis of the recently proposed particle swarm optimisation, which is based on the swarm intelligence techniques, is presented. Previous stability analysis of the particle swarm optimisation was restricted to the assumption that all of the parameters are non random since the theoretical analysis with the random parameters is difficult. We analyse the stability of the particle dynamics without these restrictive assumptions using Lyapunov stability and passive systems concepts. The particle swarm optimisation is then used to solve the sink node placement problem in sensor networks. Secondly, swarm intelligence based routing methods for mobile ad hoc networks are investigated. Two protocols have been proposed based on the foraging behaviour of biological ants and implemented in the NS2 network simulator. The first protocol allows each node in the network to choose the next node for packets to be forwarded on the basis of mobility influenced routing table. Since mobility is one of the most important factors for route changes in mobile ad hoc networks, the mobility of the neighbour node using HELLO packets is predicted and then translated into a pheromone decay as found in natural biological systems. The second protocol uses the same mechanism as the first, but instead of mobility the neighbour node remaining energy level and its drain rate are used. The thesis clearly shows that swarm intelligence methods have a very useful role to play in the management and control iv problems associated with wireless ad hoc and sensor networks. This thesis has given a number of example applications and has demonstrated its usefulness in improving performance over other existing methods

    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

    An ant colony optimization approach for maximizing the lifetime of heterogeneous wireless sensor networks

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    Maximizing the lifetime of wireless sensor networks (WSNs) is a challenging problem. Although some methods exist to address the problem in homogeneous WSNs, research on this problem in heterogeneous WSNs have progressed at a slow pace. Inspired by the promising performance of ant colony optimization (ACO) to solve combinatorial problems, this paper proposes an ACO-based approach that can maximize the lifetime of heterogeneous WSNs. The methodology is based on finding the maximum number of disjoint connected covers that satisfy both sensing coverage and network connectivity. A construction graph is designed with each vertex denoting the assignment of a device in a subset. Based on pheromone and heuristic information, the ants seek an optimal path on the construction graph to maximize the number of connected covers. The pheromone serves as a metaphor for the search experiences in building connected covers. The heuristic information is used to reflect the desirability of device assignments. A local search procedure is designed to further improve the search efficiency. The proposed approach has been applied to a variety of heterogeneous WSNs. The results show that the approach is effective and efficient in finding high-quality solutions for maximizing the lifetime of heterogeneous WSNs

    Ant-based Routing Schemes for Mobile Ad hoc Networks

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    An ad-hoc network is a collection of mobile nodes, which communicate over radio. These networks have an important advantage; they do not require any existing infrastructure or central administration. Therefore, mobile ad-hoc networks are suitable for temporary communication links. This flexibility, however, comes at a price: communication is difficult to organize due to frequent topology changes. Routing in such networks can be viewed as a distributed optimization problem. A new class of algorithms, inspired by swarm intelligence, is currently being developed that can potentially solve numerous problems of modern communications networks. These algorithms rely on the interaction of a multitude of simultaneously interacting agents. A survey of few such algorithms for ad hoc networks is presented here
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