Tarek Abdelzaher
University of Illinois at Urbana–Champaign
546 Papers
7.3K Citations
Tarek Abdelzaher is an academic researcher from University of Illinois at Urbana–Champaign. The author has contributed to research in topics: Computer science & Wireless sensor network. The author has an hindex of 88, co-authored 517 publications. Previous affiliations of Tarek Abdelzaher include Urbana University & Hewlett-Packard.
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Papers
Understanding the social network
Dong Wang,Tarek Abdelzaher,Lance Kaplan +2 more
- 01 Jan 2015
TL;DR: This chapter reviews a model that considers the impact of information sharing on the analytical foundations of social-aware reliable sensing and generalizes the MLE model the authors reviewed before to explicitly address the source dependency problem.
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On Exploiting Structured Human Interactions to Enhance Sensing Accuracy in Cyber-physical Systems
Hongwei Wang,Yunlong Gao,Shaohan Hu,Shiguang Wang,Renato Mancuso,Minje Kim,Po-Liang Wu,Lu Su,Lui Sha,Tarek Abdelzaher +9 more
TL;DR: A novel workflow-aware sensing model is proposed to jointly correct unreliable sensor data and keep track of states in a workflow and a new inference algorithm to handle cases with partially known states and objects as supervision is proposed.
3
An interactive UNIX shell for low-end sensor nodes with LiteOS
Qing Cao,Tarek Abdelzaher,John A. Stankovic,Tian He +3 more
- 06 Nov 2007
TL;DR: This demonstration highlights an interactive Unix-like shell for operating wireless sensor networks, where the user uses familiar Unix commands to complete tasks ranging from wireless installation of user applications to retrieval of data reports with the help of a built-inUnix-like file system.
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Real-time task scheduling with image resizing for criticality-based machine perception
TL;DR: A real-time task scheduling framework for criticality-based machine perception is proposed, leveraging image resizing as the tool to control the accuracy and execution time trade-off, and the use of real LiDAR measurements for quick-and-dirty image segmentation ahead of AI-based processing is investigated.
3
Simulation Evaluation of Fuel-Saving Systems in the City of Chicago
Yiran Zhao,Shuochao Yao,Dongxin Liu,Huajie Shao,Shengzhong Liu,Tarek Abdelzaher +5 more
- 01 Jul 2019
TL;DR: This paper presents realistic traffic simulations in four representative regions in Chicago, using real map data and historical traffic statistics, to estimate the amount of fuel that can be saved by two types of systems, namely, a Green Light Optimal Speed Advisory (GLOSA) system and an Eco-Routing system.
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