时间：2012年6月19日(星期二) 下午16:00
地点：成功楼603教室
主讲：美国Montclair State University大学 王大进教授
主办：数计学院
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 about 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 on-going works in WSN research. The first work concerns the issue of reducing the overall transmission power in a hexagonally clustered WSN. Assuming a spatial Poisson distribution of sensor nodes in the cluster, we discuss a process of finding the optimal cluster size by subdividing the cluster, performing an analytical estimate of power saving as the cluster subdivides. The simulation results will be presented and their implication discussed. The second work describes a heuristic, cost-effective algorithm to calculate locations for deploying sensor nodes to partially recover WSN’s lost connectivity due to the loss of nodes. The main feature of the proposed algorithm is that it tries to use very few nodes to recover the network’s connectivity to a noticeable level. The simulation results show that by using the greedy strategy, the proposed algorithm can restore the network’s connectivity to a good level with few restoration nodes. Time permitting, the talk will also briefly introduce the research performed by other Montclair CS faculty.