Constraint-based Routing for Ad-hoc Networks
Yi Shang, Markus P.J. Fromherz, Ying Zhang, and Lara S. Crawford
Abstract
Future large-scale networks, such as sensor networks, will consist of
hundreds and even thousands of wirelessly connected sensor and
actuator nodes. The nodes are typically highly resource-constrained
(processor, memory, and power), have limited communication range, and
are prone to failure. Furthermore, there is no global information
about the exact location and connectivity of the nodes. Consequently,
the explicit consideration of network and task constraints and
objectives will be an important part of routing algorithms for these
networks. In this paper, we present a distributed constraint-based
routing approach that represents destination conditions as well as
routing constraints and objectives explicitly. We further present an
efficient routing algorithm, CB-LRTA*, that extends traditional
Learning Real-Time A* (LRTA*) with back-propagation. We evaluate
CB-LRTA* using simulation and demonstrate that it improves convergence
to the optimal route over LRTA*.
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