Biological based routing algorithm for mobile ad -hoc networks.
Item
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Title
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Biological based routing algorithm for mobile ad -hoc networks.
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Identifier
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AAI3159218
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identifier
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3159218
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Creator
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Hussein, Osama Hussein.
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Contributor
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Adviser: Tarek Saadawi
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Date
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2005
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Language
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English
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Publisher
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City University of New York.
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Subject
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Engineering, Electronics and Electrical
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Abstract
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This research introduces the application of a probabilistic-based Ant Routing Algorithm for Mobile Ad-hoc networks (ARAMA) that is inspired from the ant colony's life. Mobile Ad-Hoc networks (MANETs) are highly dynamic, self-configured and self-built networks. Hence, MANETs require a special type of routing algorithms to operate efficiently in such dynamic environment. These algorithms should be able to manage efficiently the usage of the limited network resources across the network nodes (i.e., node's energy, bandwidth, processing power, etc.).;The goal of this research is to present ARAMA ability to route data and manage the network resources while considering the dynamic characteristics of MANETs and the need for low control overheads. The description of the algorithm is provided, which uses a probabilistic search for the near best route in the entire network concentrating in the best routes region. The nodes' and links' parameters are measured and collected in the nodes' indices. A path index is used to measure the path parameters and serves to minimize the forward control packet (ant) size. The concept of negative backward ant is introduced to aid in avoiding unwanted behavior (i.e., looping and link failures, etc.), and to speed up the fault detection and recovery process. Further, the concept of destination trail ants is introduced to dramatically minimize the initialization (learning/optimization) time as well as the connection setup time. A methodology to update the link grade is presented.;The simulation results show the potential of the algorithm. The results show that ARAMA finds the best/near best path and responds well to node unavailability and the energy level changes in the network nodes. In addition, ARAMA achieves a fairness of node energy usage across the network nodes as an example of the network resource management, which helps in avoiding early node failure because of energy depletion. More, The results show the ability of the algorithm to optimize more than one parameter. In addition, a comparison between ARAMA and Ad hoc On Demand Distance Vector algorithm AODV is presented to show the potential of ARAMA.
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Type
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dissertation
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Source
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PQT Legacy Restricted.xlsx
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degree
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Ph.D.