时间：2014年6月17日(周二)下午15：30
地点：仓山校区 成功楼603教室
主讲：美国Montclair State University 王大进教授
主办：数学与计算机科学学院
福建省网络安全与密码技术重点实验室
专家简介：Dajin Wang received the B.Eng. degree in computer engineering from Shanghai University of Science and Technology in 1982, and the Ph.D. degree in computer science from Stevens Institute of Technology in 1990. Since then, he has been with the Department of Computer Science at Montclair State University, Montclair, New Jersey. He became a full professor of computer science in 2002. He received several university awards for his scholarly accomplishments. He has held visiting positions in other universities, and has consulted in industry. His main research interests include interconnection networks, fault tolerant computing, algorithmic robotics, parallel processing, and wireless ad hoc and sensor networks. He has published over sixty papers in these areas. His works appeared in major journals including IEEE Transactions on Computers, IEEE TPDS, IEEE Transactions on Systems, Man and Cybernetics, IEEE Transactions on Reliability, J. of Parallel and Distributed Computing, and Parallel Computing. He has served on the program committees of influential conferences and is an Associate Editor of IEEE Transactions on Parallel and Distributed Systems.
报告摘要:
The talk will report two recent works in the research of wireless networks.
The first work discusses several proposed protocols for obtaining Spectrum Information efficiently for Cognitive Radio Networks (CRNs). For database-driven CRNs, master devices obtain spectrum information by direct connection to a spectrum database, while slave devices can only access spectrum information indirectly via masters. Out-of-band connections can be used for the communication of spectrum information among masters and slaves. Alternatively, the in-band approach completely based on primary spectrum channels can be used, eliminating the need for out-of-band connections and making it easier to adopt the database-driven spectrum. In this work, we study the in-band bootstrapping process for database-driven, multi-hop CRNs. We propose several protocols to reduce the bootstrapping time and protocol overhead.
The second work is an analysis on optimal compression ratio for power preservation in Wireless Multimedia Sensor Networks. The use of Wireless Multimedia Sensor Networks (WMSNs) has been rapidly increasing in many applications. One major difference between WMSNs and conventional WSNs is that the amount of data collected by WMSN sensors is much larger. Transferring raw multimedia data (such as videos) to base without any compression will incur vast power consumption in sensors. On the other hand, the compression operation also consumes power in sensors. Reducing transmission power means increasing in-sensor processing power. How to achieve an optimal compression ratio so that the overall power consumption for all sensors is minimized is the problem we try to tackle. We proposed an analytical model that describes the power consumption for data compression and transmission. We then use the proposed model to derive a theoretically optimal compression ratio that minimizes the overall power consumption in the underlying WMSN.