Conference Paper

Ant-Based Topology Convergence Algorithms for Resource Management in VANETs.

DOI: 10.1007/978-3-540-75867-9_124 Conference: Computer Aided Systems Theory - EUROCAST 2007, 11th International Conference on Computer Aided Systems Theory, Las Palmas de Gran Canaria, Spain, February 12-16, 2007, Revised Selected Papers
Source: DBLP

ABSTRACT

Frequent changes caused by IP-connectivity and user-oriented services in Inter-Vehicular Communication Networks (VCNs) set
great challenges to construct reliable, secure and fast converged topology formed by trusted mobile nodes and links. In this
paper, based on a new metric for network performance called topology convergence and a new Object-Oriented Management Information
Base - active MIB (O:MIB), we propose an ant-based topology convergence algorithm that applies the swarm intelligence metaphor
to find the near-optimal converged topology in VCNs which maximizes system performance and guarantee a further sustainable
and maintainable system topology to achieve Quality of Service (QoS) and system throughput. This algorithm is essentially
a distributed approach in that each node collects information from local neighbor nodes by invoking the methods from each
localized O:MIB, through the sending and receiving of ant packets from each active node, to find the appropriate nodes to
construct a routing path. Simulation results show this approach can lead to a fast converged topology with regards to multiple
optimization objectives, as well as scale to network sizes and service demands.

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    • "This way, in Dorronsoro et al. [13], six versions of GAs (panmictic and descentralized ) were evaluated and successfully used in the design of ad hoc Injection Networks. From a different point of view, and due to its specific design, Ant Colony Optimization (ACO) has been successfully adapted for implementing new routing protocols for MANETs (Di Caro et al. [16]), as well as for resource management (Chiang et al. [11]). Nevertheless, in these two last cases, the routing load provoked by the internal operations of ACOs makes these approaches unfeasible for large networks . "
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    ABSTRACT: The emerging field of vehicular ad hoc networks (VANETs) deals with a set of communicating vehicles which are able to spontaneously interconnect without any pre-existing infrastructure. In such kind of networks, it is crucial to make an optimal configuration of the communication protocols previously to the final network deployment. This way, a human designer can obtain an optimal QoS of the network beforehand. The problem we consider in this work lies in configuring the File Transfer protocol Configuration (FTC) with the aim of optimizing the transmission time, the number of lost packets, and the amount of data transferred in realistic VANET scenarios. We face the FTC with five representative state-of-the-art optimization techniques and compare their performance. These algorithms are: Particle Swarm Optimization (PSO), Differential Evolution (DE), Genetic Algorithm (GA), Evolutionary Strategy (ES), and Simulated Annealing (SA). For our tests, two typical environment instances of VANETs for Urban and Highway scenarios have been defined. The experiments using ns- 2 (a well-known realistic VANET simulator) reveal that PSO outperforms all the compared algorithms for both studied VANET instances.
    Full-text · Article · Aug 2010 · Engineering Applications of Artificial Intelligence
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    • "This way, in Dorronsoro et al. [13], six versions of GAs (panmictic and descentralized ) were evaluated and successfully used in the design of ad hoc Injection Networks. From a different point of view, and due to its specific design, Ant Colony Optimization (ACO) has been successfully adapted for implementing new routing protocols for MANETs (Di Caro et al. [16]), as well as for resource management (Chiang et al. [11]). Nevertheless, in these two last cases, the routing load provoked by the internal operations of ACOs makes these approaches unfeasible for large networks . "

    Full-text · Article · Jan 2010
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    ABSTRACT: Information modeling plays a central role in managing complexity of the distributed electronic systems. This paper proposes a nature-inspired distributed active information model (DAIM) to enable the local decision-making process, that will fundamentally contribute to a number of complex distributed electronic environments. The consequences from multiple distributed decision-makers give rise to the global goals exhibited by emergent properties. Details of the DAIM model are described in this paper. The validation for this model is also be given via the experimental tests in the discrete event simulator. Performance comparisons show the DAIM model outperforms the conventional information model.
    Full-text · Conference Paper · Jan 2008
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