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Nan Guan

Researcher at Hong Kong Polytechnic University

Publications -  212
Citations -  3858

Nan Guan is an academic researcher from Hong Kong Polytechnic University. The author has contributed to research in topics: Scheduling (computing) & Metrical task system. The author has an hindex of 26, co-authored 198 publications receiving 2883 citations. Previous affiliations of Nan Guan include Northeastern University & City University of Hong Kong.

Papers
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Proceedings ArticleDOI

New Response Time Bounds for Fixed Priority Multiprocessor Scheduling

TL;DR: This paper applies Baruah's window analysis framework to response time analysis for poradic tasks on multiprocessor systems where the deadlines of tasks are within their periods and extends the proposed technique to task systems with arbitrary deadlines, allowing tasks to have deadlines beyond the end of their periods.
Proceedings ArticleDOI

The Digraph Real-Time Task Model

TL;DR: This paper proposes a task model based on arbitrary directed graphs (digraphs) for job releases that is free from recurrent constraints and shows that the feasibility problem on preemptive uniprocessors for the model remains tractable.
Proceedings ArticleDOI

Effective and Efficient Scheduling of Certifiable Mixed-Criticality Sporadic Task Systems

TL;DR: An algorithm called PLRS is presented to schedule certifiable mixed-criticality sporadic tasks systems, and uses fixed-job-priority scheduling, and assigns job priorities by exploring and balancing the asymmetric effects between the workload on different criticality levels.
Proceedings ArticleDOI

Cache-aware scheduling and analysis for multicores

TL;DR: A scheduling strategy for real-time tasks with both timing and cache space constraints is presented, which allows each task to use a fixed number of cache partitions, and makes sure that at any time a cache partition is occupied by at most one running task.
Journal ArticleDOI

Building timing predictable embedded systems

TL;DR: The intention of this article is to summarize the current state of the art in research concerning how to build predictable yet performant systems, and suggest precise definitions for the concept of “predictability”, and present predictability concerns at different abstraction levels in embedded system design.