| Description |
ix, 73 leaves : illustrations ; 28 cm. |
| Summary |
"Ad-hoc networks are formed in several applications. Rescue operations and multiple unmanned air vehicle applications are examples. These networks are dynamic in nature and hence conventional routing and clustering schemes are not suited for them. Most of the routing and clustering algorithms are heuristics based. One main disadvantage of such algorithms is that any form of optimization cannot be achieved more over stability and convergence properties cannot be guaranteed. In this study, new Grossberg neural network (GNN) based algorithms are presented for routing and clustering in ad-hoc networks. These algorithms are implemented in a decentralized manner and have very low computation and storage requirements. GNNs are dynamic in nature and hence are well suited for applications in ad-hoc networks"--Abstract, leaf iii. |
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