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 iii
Cheng, Maggie Xiaoyan
M.S. in Computer Science
Missouri University of Science and Technology
viii, 47 pages
© 2010 Yibo Xu, All rights reserved.
Thesis - Open Access
Library of Congress Subject Headings
Data transmission systems
Wireless sensor networks -- Design
Print OCLC #
Electronic OCLC #
Link to Catalog Recordhttp://laurel.lso.missouri.edu/record=b8229273~S5
Xu, Yibo, "Minimize end-to-end delay through cross-layer optimization in multi-hop wireless sensor networks" (2010). Masters Theses. 4810.