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
Delay composition in preemptive and non-preemptive real-time pipelines
TL;DR: This paper bound the end-to-end delay of a job in a multistage pipeline as a function of job execution times on different stages under preemptive as well as non-preemptive scheduling.
On quality of event localization from social network feeds
Prasanna Giridhar,Tarek Abdelzaher,Jemin George,Lance M. Kaplan +3 more
- 23 Mar 2015
TL;DR: An algorithm is presented that identifies distinct event signatures in the blogosphere, clusters microblogs based on events they describe, and analyzes the resulting clusters for fine-grained location indicators, and derives an exact event location by fusing these indicators.
A utilization bound for aperiodic tasks and priority driven scheduling
TL;DR: It is proved that the synthetic utilization bound for deadline-monotonic scheduling of aperiodic tasks is 1/1+/spl radic/1/2, and it is shown that no other time-independent scheduling policy can have a higher schedulability bound.
Datalink streaming in wireless sensor networks
Raghu K. Ganti,Praveen Jayachandran,Haiyun Luo,Tarek Abdelzaher +3 more
- 31 Oct 2006
TL;DR: Seda is described: a streaming datalink layer that resolves the above dilemma by decoupling framing from error recovery by increasing the TinyOS frame size from the default 29 bytes to 100 bytes, which improves the throughput around 25% under typical wireless channel conditions.
Privacy-aware regression modeling of participatory sensing data
Hossein Ahmadi,Nam Pham,Raghu K. Ganti,Tarek Abdelzaher,Suman Nath,Jiawei Han +5 more
- 03 Nov 2010
TL;DR: The main contribution of the paper is to show a certain data transformation at the client side that helps keeping the client data private while not introducing any additional error to model construction.