Minimize end-to-end delay through cross-layer optimization in multi-hop wireless sensor networks

End-to-end delay plays a very important role in wireless sensor networks. It refers to the total time taken for a single packet to be transmitted across a network from source to destination. There are many factors could affect the end-to-end delay, among them the routing path and the interference level along the path are the two basic elements that could have significant influence on the result of the end-to-end delay. This thesis presents a transmission scheduling scheme that minimizes the end-to-end delay when the node topology is given. The transmission scheduling scheme is designed based on integer linear programming and the interference modeling is involved. By using this scheme, we can guarantee that no conflicting transmission will appear at any time during the transmission. A method of assigning the time slot based on the given routing is presented. The simulation results show that the link scheduling scheme can significantly reduce the end-to-end delay. Further, this article also shows two methods which could directly addresses routing and slot assignment, one is MI+MinDelay algorithm and the other is called One-Phase algorithm. A comparison was made between the two and the simulation result shows the latter one leads to smaller latency while it takes much more time to be solved. Besides, due to the different routing policy, we also demonstrate that the shortest path routing does not necessarily result in minimum end-to-end delay --Abstract, page ii

Cross-layer design for network performance optimization in wireless networks

In this dissertation, I use mathematical optimization approach to solve the complex network problems. Paper l and paper 2 first show that ignoring the bandwidth constraint can lead to infeasible routing solutions. A sufficient condition on link bandwidth is proposed that makes a routing solution feasible, and then a mathematical optimization model based on this sufficient condition is provided. Simulation results show that joint optimization models can provide more feasible routing solutions and provide significant improvement on throughput and lifetime. In paper 3 and paper 4, an interference model is proposed and a transmission scheduling scheme is presented to minimize the end-to-end delay. This scheduling scheme is designed based on integer linear programming and involves interference modeling. Using this schedule, there are no conflicting transmissions at any time. Through simulation, it shows that the proposed link scheduling scheme can significantly reduce end-to-end latency. Since to compute the maximum throughput is an NP-hard problem, efficient heuristics are presented in Paper 5 that use sufficient conditions instead of the computationally-expensive-to-get optimal condition to capture the mutual conflict relation in a collision domain. Both one-way transmission and two-way transmission are considered. Simulation results show that the proposed algorithms improve network throughput and reduce energy consumption, with significant improvement over previous work on both aspects. Paper 6 studies the complicated tradeoff relation among multiple factors that affect the sensor network lifetime and proposes an adaptive multi-hop clustering algorithm. It realizes the best tradeoff among multiple factors and outperforms others that do not. It is adaptive in the sense the clustering topology changes over time in order to have the maximum lifetime --Abstract, page iv