Phan, Linh T.X.

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Now showing 1 - 10 of 35
  • Publication
    An Empirical Analysis of Scheduling Techniques for Real-Time Cloud-Based Data Processing
    (2011-12-01) Phan, Linh T.X.; Loo, Boon Thau; Zhang, Zhuoyao; Lee, Insup; Zheng, Qi
    In this paper, we explore the challenges and needs of current cloud infrastructures, to better support cloud-based data-intensive applications that are not only latency-sensitive but also require strong timing guarantees. These applications have strict deadlines (e.g., to perform time-dependent mission critical tasks or to complete real-time control decisions using a human-in-the-loop), and deadline misses are undesirable. To highlight the challenges in this space, we provide a case study of the online scheduling of MapReduce jobs executed by Hadoop. Our evaluations on Amazon EC2 show that the existing Hadoop scheduler is ill-equipped to handle jobs with deadlines. However, by adapting existing multiprocessor scheduling techniques for the cloud environment, we observe significant performance improvements in minimizing missed deadlines and tardiness. Based on our case study, we discuss a range of challenges in this domain posed by virtualization and scale, and propose our research agenda centered around the application of advanced real-time scheduling techniques in the cloud environment.
  • Publication
    MC-ADAPT: Adaptive Task Dropping in Mixed-Criticality Scheduling
    (2017-10-01) Lee, Jaewoo; Phan, Linh T.X.; Chwa, Hoon Sung; Lee, Insup; Shin, Insik
    Recent embedded systems are becoming integrated systems with components of different criticality. To tackle this, mixed-criticality systems aim to provide different levels of timing assurance to components of different criticality levels while achieving efficient resource utilization. Many approaches have been proposed to execute more lower-criticality tasks without affecting the timeliness of higher-criticality tasks. Those previous approaches however have at least one of the two limitations; i) they penalize all lower-criticality tasks at once upon a certain situation, or ii) they make the decision how to penalize lowercriticality tasks at design time. As a consequence, they underutilize resources by imposing an excessive penalty on lowcriticality tasks. Unlike those existing studies, we present a novel framework, called MC-ADAPT, that aims to minimally penalize lower-criticality tasks by fully reflecting the dynamically changing system behavior into adaptive decision making. Towards this, we propose a new scheduling algorithm and develop its runtime schedulability analysis capable of capturing the dynamic system state. Our proposed algorithm adaptively determines which task to drop based on the runtime analysis. To determine the quality of task dropping solution, we propose the speedup factor for task dropping while the conventional use of the speedup factor only evaluates MC scheduling algorithms in terms of the worst-case schedulability. We apply the speedup factor for a newly-defined task dropping problem that evaluates task dropping solution under different runtime scheduling scenarios. We derive that MC-ADAPT has a speedup factor of 1.619 for task drop. This implies that MC-ADAPT can behave the same as the optimal scheduling algorithm with optimal task dropping strategy does under any runtime scenario if the system is sped up by a factor of 1.619.
  • Publication
    Multi-Mode Virtualization for Soft Real-Time Systems
    (2018-04-01) Xu, Meng; Li, Haoran; Phan, Linh T.X.; Li, Chong; Lee, Insup; Lu, Chenyang; Sokolsky, Oleg; Gill, Christopher
    Real-time virtualization is an emerging technology for embedded systems integration and latency-sensitive cloud applications. Earlier real-time virtualization platforms require offline configuration of the scheduling parameters of virtual machines (VMs) based on their worst-case workloads, but this static approach results in pessimistic resource allocation when the workloads in the VMs change dynamically. Here, we present Multi-Mode-Xen (M2-Xen), a real-time virtualization platform for dynamic real-time systems where VMs can operate in modes with different CPU resource requirements at run-time. M2-Xen has three salient capabilities: (1) dynamic allocation of CPU resources among VMs in response to their mode changes, (2) overload avoidance at both the VM and host levels during mode transitions, and (3) fast mode transitions between different modes. M2-Xen has been implemented within Xen 4.8 using the real-time deferrable server (RTDS) scheduler. Experimental results show that M2-Xen maintains real-time performance in different modes, avoids overload during mode changes, and performs fast mode transitions.
  • Publication
    Compositional Analysis of Multi-Mode Systems
    (2009-01-01) Phan, Linh T.X.; Lee, Insup; Sokolsky, Oleg
    The paper presents a model for multi-mode realtime applications and develops new techniques for the compositional analysis of systems that contain multiple such applications. An algorithm for constructing an interface for a single multimode application is presented. Then, a method for computing an interface of a composite application is presented, which uses only the interfaces of constituent applications. A case study of an adaptive streaming system demonstrates that multi-mode analysis offers more precise results compared to a unimodal worst-case analysis.
  • Publication
    Towards a Compositional Multi-Modal Framework for Adaptive Cyber-Physical Systems
    (2011-08-01) Phan, Linh T.X.; Lee, Insup
    Among the key characteristics of cyber-physical systems are the ability to adapt to changes during operation, the multidimensional complexity of multi-functionality and the underlying heterogeneous distributed architecture, as well as resource use efficiency. In this paper, we propose a compositional multi-modal approach to modeling, analyzing, and designing such systems. We introduce a general framework for modeling and compositional analysis of multi-mode systems on a distributed architecture that facilitates adaptivity, efficient use of resources, and incremental integration. We present some preliminary results, and we describe some of the remaining challenges and future directions.
  • Publication
    Mixed-Criticality Scheduling on Multiprocessors using Task Grouping
    (2015-07-01) Ren, Jiankang; Phan, Linh T.X.
    Real-time systems are increasingly running a mix of tasks with different criticality levels: for instance, unmanned aerial vehicle has multiple software functions with different safety criticality levels, but runs them on a single, shared computational platform. In addition, these systems are increasingly deployed on multiprocessor platforms because this can help to reduce their cost, space, weight, and power consumption. To assure the safety of such systems, several mixed-criticality scheduling algorithms have been developed that can provide mixed-criticality timing guarantees. However, most existing algorithms have two important limitations: they do not guarantee strong isolation among the high-criticality tasks, and they offer poor real-time performance for the low-criticality tasks.
  • Publication
    Cache-aware Interfaces for Compositional Real-Time Systems
    (2015-12-01) Phan, Linh T.X.; Xu, Meng; Lee, Insup
    Interface-based compositional analysis is by now a fairly established area of research in real-time systems. However, current research has not yet fully considered practical aspects, such as the effects of cache interferences on multicore platforms. This position paper discusses the analysis challenges and motivates the need for cache scheduling in this setting, and it highlights several research questions towards cache-aware interfaces for compositional systems on multicore platforms.
  • Publication
    Generic Formal Framework for Compositional Analysis of Hierarchical Scheduling Systems
    (2018-05-01) Boudjadar, Jalil; Kim, Jin Hyun; Phan, Linh Thi Xuan; Lee, Insup; Nyman, Ulrik; Larsen, Kim G.
    We present a compositional framework for the specification and analysis of hierarchical scheduling systems (HSS). Firstly we provide a generic formal model, which can be used to describe any type of scheduling system. The concept of Job automata is introduced in order to model job instantiation patterns. We model the interaction between different levels in the hierarchy through the use of state-based resource models. Our notion of resource model is general enough to capture multi-core architectures, preemptiveness and non-determinism.
  • Publication
    LogSafe: Secure and Scalable Data Logger for IoT Devices
    (2018-04-01) Nguyen, Hung; Ivanov, Radoslav; Phan, Linh T.X.; Sokolsky, Oleg; Weimer, James; Lee, Insup
    As devices in the Internet of Things (IoT) increase in number and integrate with everyday lives, large amounts of personal information will be generated. With multiple discovered vulnerabilities in current IoT networks, a malicious attacker might be able to get access to and misuse this personal data. Thus, a logger that stores this information securely would make it possible to perform forensic analysis in case of such attacks that target valuable data. In this paper, we propose LogSafe, a scalable, fault-tolerant logger that leverages the use of Intel Software Guard Extensions (SGX) to store logs from IoT devices efficiently and securely. Using the security guarantees of SGX, LogSafe is designed to run on an untrusted cloud infrastructure and satisfies Confidentiality, Integrity, and Availability (CIA) security properties. Finally, we provide an exhaustive evaluation of LogSafe in order to demonstrate that it is capable of handling logs from a large number of IoT devices and at a very high data transmission rate.
  • Publication
    Removing Abstraction Overhead in the Composition of Hierarchical Real-Time System
    (2011-04-01) Chen, Sanjian; Phan, Linh T.X.; Lee, Jaewoo; Lee, Insup; Sokolsky, Oleg
    The hierarchical real-time scheduling framework is a widely accepted model to facilitate the design and analysis of the increasingly complex real-time systems. Interface abstraction and composition are the key issues in the hierarchical scheduling framework analysis. Schedulability is essential to guarantee that the timing requirements of all components are satisfied. In order for the design to be resource efficient, the composition must be bandwidth optimal. Associativity is desirable for open systems in which components may be added or deleted at run time. Previous techniques on compositional scheduling are either not resource efficient in some aspects, or cannot achieve optimality and associativity at the same time. In this paper, several important properties regarding the periodic resource model are identified. Based on those properties, we propose a novel interface abstraction and composition framework which achieves schedulability, optimality, and associativity. Our approach eliminates abstraction overhead in the composition.