Abstract
The quality-of-service (QoS) routing in a wireless sensor network is difficult because the network topology may change constantly, and the available state information for routing is inherently imprecise. In this paper, we propose a distributed QoS routing that selects a network path with sufficient resources to satisfy a certain delay requirement in a dynamic environment. Multiple paths are searched in parallel to find the most qualified one. Fault tolerance techniques are brought in for the maintenance of the routing. Our algorithms consider not only the QoS requirement, but also the cost optimality of the routing path to improve the overall network performance based on reinforcement learning techniques. In this paper we are to interest particularly in some metric of QoS in particular. the delay, packets losses and also the overhead.
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