Jie Lian
University of Waterloo
15 Papers
85 Citations
Jie Lian is an academic researcher from University of Waterloo. The author has contributed to research in topics: Wireless sensor network & Policy-based routing. The author has an hindex of 8, co-authored 13 publications.
Chat about Author
Papers
A Weighted Moving Average-based Approach for Cleaning Sensor Data
Yongzhen Zhuangt,Lei Chen,X.S. Wang,Jie Lian +3 more
- 25 Jun 2007
TL;DR: The rationale behind the WMA algorithm is to draw more samples for a particular value that is of great importance to the moving average, and provide higher confidence weight for this value, such that this important value can be quickly reflected in theMoving average.
A framework for evaluating the performance of cluster algorithms for hierarchical networks
TL;DR: This paper provides a set of desired properties of clustering algorithms, which can be measured by the total routing table size and the variance of cluster size distribution, and shows how the variable degree clustering algorithm, which takes into account these desired properties, improves routing performance.
42
Virtual Surrounding Face Geocasting with Guaranteed Message Delivery for Ad Hoc and Sensor Networks
Jie Lian,Kshirasagar Naik,Yunhao Liu,Lei Chen +3 more
- 12 Nov 2006
TL;DR: The idea of a virtual surrounding face (VSF) is introduced, and a geocasting protocol based on VSF is presented that guarantees message delivery and has a significant lower transmission cost than the existing approaches.
Virtual surrounding face geocasting in wireless ad hoc and sensor networks
TL;DR: This study proposes the concept of Virtual Surrounding Face (VSF), and design a VSF-based geocasting protocol (VSFG), and designs a SKIP method and a local dominating set (DS) based restricted flooding technique to further reduce the cost of VSFG.
Surplus-based accelerated algorithms for distributed optimization over directed networks
Zhu Lin Wang,Jie Lian,Wei Wang +2 more
TL;DR: In this paper , a distributed optimization problem based on the framework of a multi-agent system over a directed communication network is investigated, where the global cost function is the sum of the local cost functions of agents.
24