In this dissertation, we propose using and analytically evaluate the predictive multicast polling scheme and the tree splitting algorithm for medium access control in interference dominating wireless access networks with random traffic and finite nodes. In an interference dominating wireless network, a receiver could simultaneously receive multiple packets from a variety of transmitters, as long as the signal-to-interference-plus-noise ratio exceeds a predetermined threshold. We concentrate on the case of in which the maximum queue size in a node is finite. We use discrete-time Markov chains, reward processes and regenerative processes to derive the throughput, the packet blocking probability, the average packet delay, and the average system size. We show that the system performance of the predictive multicast polling scheme can be significantly improved with a few additional buffers in the queues. Our study also shows that exact performance of the splitting algorithm depends on the total number of nodes in the networks. We verify our numerical results by rigorous mathematical proof and computer simulations.

In this thesis, we propose a power saving strategy based on tree splitting algorithm in wireless sensor network with multiple packet reception. We concentrate on the case that maximum queue size is 1. We derive both analytical results and simulation results. We use theory of Markov chain to analyze the evolution of the system state. In addition, we propose to use Renewal theory to calculate the throughput. Furthermore, we obtain the average system size, the packet blocking probability, and the average packet delay. Because the network model is distributed, we can¡¦t understand the state of network all the time. So we use the length of last collision resolution cycle to predict the length of next cycle, and determine the sleeping time by the predicted length of next cycle to implement power saving. At last we will use the simulation result to show the performance of our power saving strategy.