Y
Yang Bai
Researcher at Hunan University
Publications - 10
Citations - 381
Yang Bai is an academic researcher from Hunan University. The author has contributed to research in topics: Scheduling (computing) & Directed acyclic graph. The author has an hindex of 4, co-authored 10 publications receiving 195 citations.
Papers
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A Survey of Intrusion Detection for In-Vehicle Networks
TL;DR: An IVN environment is introduced, and the constraints and characteristics of an intrusion detection system (IDS) design for IVNs are presented, and a survey of the proposed IDS designs for the IVNs is conducted.
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Efficient task scheduling for budget constrained parallel applications on heterogeneous cloud computing systems
TL;DR: Experimental results on several real parallel applications validate that the proposed MSLBL algorithm can obtain shorter schedule lengths while satisfying the budget constraint of an application than existing methods in various situations.
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Minimizing Redundancy to Satisfy Reliability Requirement for a Parallel Application on Heterogeneous Service-Oriented Systems
TL;DR: This study solves the problem of minimizing redundancy to satisfy reliability requirement for a directed acyclic graph (DAG)-based parallel application on heterogeneous service-oriented systems and proposes heuristic replication for redundancy minimization (HRRM) to satisfy application's reliability requirement with low time complexity.
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ASDYS: Dynamic Scheduling Using Active Strategies for Multifunctional Mixed-Criticality Cyber–Physical Systems
TL;DR: This article investigates dynamic scheduling of such mixed-criticality functions, where each function is modeled by a directed acyclic graph with no assumption on its period or minimum interarrival time and proposes a novel dynamic scheduling approach using active strategies (ASDYS in short).
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Quantitative Modeling and Analytical Calculation of Anelasticity for a Cyber-Physical System
TL;DR: This paper investigates resource provisioning in cyber-physical systems (CPSs) by developing a new definition of anelasticity and shows that the system can maintain elastic invariance in adaptive adjustment parameters.