Hybrid mobile content delivery systems improve performance of wide-area networks by combining both wide-area and local-area communications. In hybrid content delivery, service providers send data packets first to a small number of selected users (e.g., those with good channel quality) and then these mobile users help forward the packets to others (e.g., those with poor channel quality). The central theme of our work is to identify the initial target set composed of influential mobile users (i.e., individuals with high centrality in their social-contact graphs) and thus improve the efficiency of hybrid mobile content distribution.
We first present two centralized algorithms for this target-set selection problem. The greedy algorithm has a provable performance guarantee, due to the submodularity of the underlying information dissemination function. The heuristic algorithm exploits the regularity of human mobility and is more practical than the greedy algorithm. We then propose a lightweight and distributed protocol to identify these influential users through random-walk sampling. This distributed protocol leverages random-walk probe messages to sample mobile users and estimates their centrality based on how many times they are visited by the probe messages. This protocol has low communication and computation overhead and lends itself well to mobile content delivery. We verify the effectiveness of these approaches through extensive trace-driven simulation studies using real-world mobility traces.
|Advisor:||Srinivasan, Aravind, Bhattacharjee, Bobby|
|Commitee:||Deshpande, Amol, Golbeck, Jennifer, La, Richard|
|School:||University of Maryland, College Park|
|School Location:||United States -- Maryland|
|Source:||DAI-B 74/03(E), Dissertation Abstracts International|
|Keywords:||Centrality, Hybrid delivery, Mobile content delivery, Random walks|
Copyright in each Dissertation and Thesis is retained by the author. All Rights Reserved
The supplemental file or files you are about to download were provided to ProQuest by the author as part of a
dissertation or thesis. The supplemental files are provided "AS IS" without warranty. ProQuest is not responsible for the
content, format or impact on the supplemental file(s) on our system. in some cases, the file type may be unknown or
may be a .exe file. We recommend caution as you open such files.
Copyright of the original materials contained in the supplemental file is retained by the author and your access to the
supplemental files is subject to the ProQuest Terms and Conditions of use.
Depending on the size of the file(s) you are downloading, the system may take some time to download them. Please be