A QoS Scheduler Packets for Wireless Sensor Networks

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. Ever more complex sensors have become available to create and maintain situational awareness during missions. Choosing the most suited sensor for the execution of a sensor function is based on sensor capabilities and function attributes. To increase performance of the entire sensor network, the total set of sensors should be scheduled in a single system. This paper puts forward for scheduling prioritised tasks in sensor networks. Use a reinforcement learning formalism to optimise the set of schedules. In this paper, node actively infer the state of other nodes, using a reinforcement learning based more particularly Q-learning, thereby achieving high throughput by improving the delay for a wide range of traffic conditions.