The Efficient Transmission Of Delay-sensitive Ervices Over Autonomic Wireless Networks

Emerging multi-hop wireless networks provide a low-cost and flexibleinfrastructure for a variety of applications, including delay-sensitive applications.However, this wireless infrastructure is often unreliable and provides dynamicallyvarying resources with only limited QoS support. To improve the performance of thedelay-sensitive applications，the multi-hop network needs to be composed of autonomicnodes, which can make and adapt their own transmission decisions to support timelyreaction to the network dynamics based on their available local information underautonomic decision making framework.First, this thesis studies the packet arrival rate to destination nodes maximizationproblem in a dynamic multi-hop wireless network. To consider both the spatial andtemporal dependency in the multi-hop network, we formulate the packet arrival ratemaximization problem using a distributed MDP. We propose an online model-basedlearning approach for solving the distributed MDP problem to make packets reachdestination nodes with the maximum rate. Then, we study the joint power-spectrumallocation problem for delay sensitive user over autonomic wireless network. The userstatistics and analyzes the transmission strategies of the other users under dynamicchannel states through interactive learning based on information feedback from theother users in the network and makes foresighted transmission action to get the optimaljoint power-spectrum allocation.