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Kang G. Shin

Researcher at University of Michigan

Publications -  913
Citations -  40876

Kang G. Shin is an academic researcher from University of Michigan. The author has contributed to research in topics: Scheduling (computing) & Network packet. The author has an hindex of 98, co-authored 885 publications receiving 38572 citations. Previous affiliations of Kang G. Shin include IBM & Sungkyunkwan University.

Papers
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Proceedings ArticleDOI

Real-time dynamic voltage scaling for low-power embedded operating systems

Padmanabhan Pillai, +1 more
TL;DR: This paper presents a class of novel algorithms that modify the OS's real-time scheduler and task management service to provide significant energy savings while maintaining real- time deadline guarantees, and shows that these RT-DVS algorithms closely approach the theoretical lower bound on energy consumption.
Journal ArticleDOI

Minimum-time control of robotic manipulators with geometric path constraints

Kang G. Shin, +1 more
- 01 Jun 1985 - 
TL;DR: In this paper, the problem of moving a manipulator in minimum time along a specified geometric path subject to input torque/force constraints is considered, and the minimum-time solution is deduced in an algorithm form using phase-plane techniques.
Journal ArticleDOI

Efficient Discovery of Spectrum Opportunities with MAC-Layer Sensing in Cognitive Radio Networks

Hyoil Kim, +1 more
- 01 May 2008 - 
TL;DR: This work develops a sensing-period optimization mechanism and an optimal channel-sequencing algorithm, as well as an environment- adaptive channel-usage pattern estimation method that is shown to track time-varying channel-parameters accurately.
Proceedings ArticleDOI

Detecting SYN flooding attacks

Haining Wang, +2 more
TL;DR: A simple and robust mechanism that not only sets alarms upon detection of ongoing SYN flooding attacks, but also reveals the location of the flooding sources without resorting to expensive IP traceback.
Proceedings ArticleDOI

Adaptive control of virtualized resources in utility computing environments

Pradeep Padala, +7 more
TL;DR: An adaptive resource control system that dynamically adjusts the resource shares to individual tiers in order to meet application-level quality of service (QoS) goals while achieving high resource utilization in the data center is developed.