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Sampled-Data Approach to State Estimation Performance for heterogeneous distributed system with Fault

ASIAN JOURNAL OF CONTROL 2015年第5期17卷 1498-1508页

作者： Chen, Shun Ho, Daniel W. C. City Univ Hong Kong Dept Math Hong Kong Hong Kong Peoples R China

This paper considers the state estimation performance for heterogeneous distributed system with fault based on sampled-data measurement. Firstly, a performance index for distributed state estimation is proposed. Based on the sampled-data measurement of the heterogeneous distributed system, distributed state estimators are constructed. It is proved that by analyzing the distributed state estimation error systems, the required performance index for overall state estimation can be obtained using linear matrix inequality method. Finally, a simulation example is used to illustrate the effectiveness of the proposed theoretical scheme.

关键词： State estimation heterogeneous distributed system sampled-data measurement fault

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Maximizing Reliability of heterogeneous distributed system Using Bio-Inspired Technique for Task Allocation Problem 2017

Maximizing Reliability of Heterogeneous Distributed System U...

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International Conference on Computer Science and Artificial Intelligence (CSAI)

作者： Abbache, Farid Kalla, Hamoudi Univ MSila Dept Comp Sci Msila Algeria Univ Batna 2 Dept Comp Sci Batna Algeria

ISBN: (纸本)9781450353922

Task allocation process plays great role in either enhancing the reliability of the system or degrading it, especially, in a heterogeneous distributed environment. Therefore, the exact algorithms for task allocation are not recommended as they consume a lot of amount of time which is reflected on the age of system's components, consequently their reliability. For that, an approximate approach based bio-inspired is used. This approach is a modified version of the classical cuckoo search algorithm (CS). This approach is called, Modified Discrete Cuckoo Search algorithm (MDCS). In this version, all cuckoo parameters are modified dynamically according to their fitness which allows a speed convergence toward the optimal solution. To confirm the efficiency and effectiveness of MDCS, its results are tested and compared with those of Hybrid Particle Swarm Optimization (HPSO) and Discrete Cuckoo Search (DCS) which is the same as MDCS but with static parameters. The effectiveness of MDCS over HPSO and DCS are reported.

关键词： Discrete cuckoo algorithm heterogeneous distributed system Reliability Task allocation

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Maximizing Reliability of heterogeneous distributed system Using an Adapted Discrete Flower Pollination Algorithm for Task Allocation Problem 21

Maximizing Reliability of Heterogeneous Distributed System U...

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21st Saudi-Computer-Society National Computer Conference (NCC)

作者： Abbache, Farid Kalla, Hamoudi Univ Mohamed Boudiaf Msila Dept Comp Sci Msila Algeria Univ Batna 2 LaSTIC Lab Batna Algeria Univ Batna 2 Dept Comp Sci Batna Algeria

ISBN: (纸本)9781538641101

Finding task allocation that maximizes reliability of a heterogeneous distributed system is an NP-hard problem. For that, meta-heuristic is used to get a sub optimal solution in reasonable time. The Flower Pollination algorithm is new meta-heuristic used successfully for solving different problems in different fields. The original Flower Pollination algorithm is designed to deal with continuous problem. Thus, applying this algorithm to discrete problems in its original form seems to be very hard or useless. In this paper, we propose an adapted discrete version of the Flower Pollination algorithm to deal with the problem of maximizing reliability of a heterogeneous distributed system under task allocation problem. This algorithm is called Adapted Discrete Flower Pollination algorithm (ADFP). To confirm the effectiveness of our algorithm, we have tested and compared its results with that of Hybrid Particle Swarm Optimization (HPSO). The Experiments results show the effectiveness and superiority of ADFP over HPSO in all tested cases.

关键词： Discrete Flower Pollination algorithm heterogeneous distributed system Reliability Task allocation

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Task allocation-based modified bacterial foraging algorithm for maximising reliability of a heterogeneous distributed system

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INTERNATIONAL JOURNAL OF COMMUNICATION NETWORKS AND distributed systemS 2019年第2期23卷 252-273页

作者： Abbache, Farid Kalla, Hamoudi Univ Batna 2 LaSTIC Lab Comp Sci Dept Batna 05000 Algeria

modified bacterial foraging algorithm for allocation and scheduling tasks on processors and links with high reliability is proposed (MBFA). MBFA ensure high reliability without redundancy of processors or links by using an efficient and simple structure. MBFA is improved by adding an efficient model to deal with the weak solution (i.e., allocation with low reliability). Also a simulated annealing technique is integrated into MBFA in order to strengthen the search of best solution. The efficiency and effectiveness of MBFA are tested using random generated problems. MBFA is tested over the published approaches HPSO and GAA using density parameter (DS), number of nodes (N) and the communication to computation ratio parameter (CCR). The results show the superiority of MBFA over the published approaches in all test cases.

关键词： task allocation heterogeneous distributed system reliability bacterial foraging algorithm simulated annealing algorithm

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A Fault-Tolerant Scheduling Algorithm Based on a Multi-Objective Genetic Algorithm for Precedence-Constrained Tasks in Real-Time heterogeneous distributed systems

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JOURNAL OF COMPUTATIONAL AND THEORETICAL NANOSCIENCE 2013年第5期10卷 1091-1096页

作者： Chen Yuanlong Ma Peijun Li Dong Harbin Inst Technol Sch Comp Sci & Technol Harbin 150001 Peoples R China

In this paper, we investigate an efficient off-line fault-tolerant scheduling algorithm that generates schedules in which real-time tasks with precedence constraints can tolerate more than one fault at a time in a heterogeneous system with a fully connected network. We assume tasks to be non-preemptable, and each task has two copies scheduled on different processors and mutually excluded. Our fault-tolerant scheduling algorithm based on non-domination sort genetic algorithm (NSGA) employs performance improving techniques, including (1) a dynamic distance concept that decides the relative position of two task copies in the task graph, (2) a multi objectives genetic algorithm to optimise multiple targets. We performed experiments using synthetic workloads and a real-world application. Simulation results show that compared with existing scheduling algorithms, our scheduling algorithm improves guarantee ratio, reliability and overhead.

关键词： heterogeneous distributed system Dynamical Distance Fault Tolerant Scheduling Multi-Objective Genetic Algorithm

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Dynamic Multiworkflow Deadline and Budget Constrained Scheduling in heterogeneous distributed systems

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IEEE systemS JOURNAL 2021年第4期15卷 4939-4949页

作者： Wang, Guan Wang, Yuxin Obaidat, Mohammad S. Lin, Chi Guo, He Dalian Univ Technol Sch Software Technol Dalian 116024 Peoples R China Liaoning Police Coll Dalian 116036 Peoples R China Dalian Univ Technol Sch Comp Sci & Technol Dalian 116024 Peoples R China Univ Sharjah Coll Comp & Informat Sharjah 27272 U Arab Emirates Univ Jordan King Abdullah 2 Sch Informat Technol Amman 11942 Jordan Univ Sci & Technol Beijing Beijing 100083 Peoples R China Dalian Univ Technol Sch Software Engn Dalian 116024 Peoples R China

Dynamic scheduling of multiworkflow in a heterogeneous distributed system has become a crucial issue in recent days due to user-defined deadlines and budget constraints. In order to settle down this problem, we present a dynamic multiworkflow deadline and budget constrained heterogeneous scheduling (DMW-HDBS) algorithm. DMW-HDBS owns some unique features: in the task selection phase, an optimized priority selection strategy is applied to determine the priority scheduling tasks;in the stage of resource allocation, the cost and budget ratio is utilized to better balance therelationship between deadline and budget constraint;and the discard judgment mechanism is used to improve the success rate of multiworkflow scheduling. Real-world application experiments are conducted to verify that our algorithm has better scheduling performance than other competing algorithms.

关键词： Task analysis Dynamic scheduling Heuristic algorithms Quality of service Standards Resource management Scheduling algorithms Budget constrained concurrent workflows deadline constrained dynamic scheduling systems heterogeneous distributed system

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An efficient fault-tolerant scheduling algorithm for precedence constrained tasks in heterogeneous distributed systems

An efficient fault-tolerant scheduling algorithm for precede...

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International Conference on systems, Computing Science and Software Engineering

作者： Nakechbandi, M. Colin, J. -Y. Gashumba, J. B. Univ Havre LITIS F-76058 Le Havre France

ISBN: (纸本)9781402062674

In this paper, we propose an efficient scheduling algorithm for problems in which tasks with precedence constraints and communication delays have to be scheduled on an heterogeneous distributed system with one fault hypothesis. Our algorithm combines the DSS_OPT algorithm and the eFRCD algorithm. To provide a fault-tolerant capability, we employ primary and backup copies. In this scheme, backup copies can overlap other backup copies, and backup copies are not established for tasks that have more than one primary copy. The result is a schedule in polynomial time that is optimal when there is no failure, and is a good resilient schedule in the case of one failure.

关键词： scheduling heterogeneous distributed system fault-tolerance precedence constraints communication delays critical-path method

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A security-oriented task scheduler for heterogeneous distributed systems

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13th International Conference on High Performance Computing (HiPC 2006)

作者： Xie, Tao Qin, Xiao San Diego State Univ Dept Comp Sci San Diego CA 92182 USA New Mexico Inst Min & Technol Dept Comp Sci Socorro NM 87801 USA

ISBN: (纸本)9783540680390

High quality of security is increasingly critical for applications running on heterogeneous distributed systems, where processors operate at different speeds and communication channels have different bandwidths. Although there are a few scheduling algorithms in the literature for heterogeneous distributed systems, they generally do not take into account of security requirements of applications. In this paper, we propose a novel heuristic scheduling algorithm, or SATS, which is conducive to improving security of heterogeneous distributed systems. First, we formalize a concept of security heterogeneity for our scheduling model in the context of distributed systems. Next, we devise the SATS algorithm aiming at scheduling tasks to maximize the probability that all tasks are executed without any risk of being attacked. Empirical results demonstrate that with respect to security and performance, the proposed scheduling algorithm outperforms existing approaches for heterogeneous distributed systems.

关键词： security heterogeneity heterogeneous distributed system scheduling degree of security deficiency risk-free probability

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Scheduling-Efficient Framework for Neural Network on heterogeneous distributed systems and Mobile Edge Computing systems

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IEEE ACCESS 2019年 7卷 171853-171863页

作者： Zhou, Xiang Zhang, Jilin Wan, Jian Zhou, Li Wei, Zhenguo Zhang, Juncong Hangzhou Dianzi Univ Sch Comp Hangzhou 310018 Peoples R China Minist Educ Key Lab Complex Syst Modeling & Simulat Hangzhou 310018 Peoples R China Zhejiang Univ Sci & Technol Sch Comp Sci & Technol Hangzhou 310023 Peoples R China Chinese Acad Sci Inst Comp Technol State Key Lab Comp Architecture Beijing 100190 Peoples R China Zhejiang Dawning Informat Technol Co Ltd Hangzhou 310051 Peoples R China

As the volume of machine learning training data sets and the quantity of model parameters continue to grow, the pattern in which machine learning models are trained alone can no longer accommodate large-scale data environments. However, distributed systems and mobile edge computing systems are unpredictable and have heterogeneous nodes, resulting in interruptions in training or low convergence rate. In addition, existing distributed machine learning frameworks cannot guarantee a good convergence rate and speedup ratio in a variety of operating environments. Considering the above shortcomings, this paper proposes an adaptive scheduling framework for machine learning based on a heterogeneous distributed system and mobile edge computing system for machine learning model optimization. The framework detects and analyzes the dynamic changes of resources in the distributed system and mobile edge computing system through the resource detection system;then, the task scheduling system adaptively modifies the environmental parameters and schedules calculations. Relevant experiments conducted with the public data set show that the robustness and scalability of the framework are significantly better than the traditional distributed machine learning framework under the premise of ensuring high convergence rate.

关键词： heterogeneous distributed system mobile edge computing system adaptive scheduling large-scale machine learning

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Time-constrained and reliability aware energy minimization scheduling algorithm for heterogeneous multiprocessor environments

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CONCURRENCY AND COMPUTATION-PRACTICE & EXPERIENCE 2022年第26期34卷

作者： Wang, Zhaorui Fan, Guisheng Yu, Huiqun East China Univ Sci & Technol Dept Comp Sci & Engn Shanghai Peoples R China Shenergy Grp Co Ltd Shanghai Engn Res Ctr Smart Energy Shanghai Peoples R China Shanghai Comp Software Tech Dev Ctr Shanghai Key Lab Comp Software Evaluating & Testi Shanghai Peoples R China

heterogeneous multiprocessor systems are now widely used in industry by providing high performance and high concurrency. However, with the increasing number of computational nodes, it leads to a dramatic increase in energy consumption of heterogeneous multiprocessor systems. Most of the current research has been conducted to reduce the energy consumption by reducing the processor frequency and extending the task execution time, but these measures often lead to a significant decrease in system reliability. This article addresses the problem of energy-aware task scheduling in the case of distributed computing systems with deadline and reliability constraints. First, a time and reliability allocation model is built to assign the deadline and reliability constraints to each task, which ensures fairness among tasks. Then, a three-stage scheduling algorithm is proposed to minimize the system energy consumption. The static energy consumption is minimized by shutting down the inefficient processors. The dynamic energy consumption of the system is reduced by distributing tasks as evenly as possible on each processor through a task redistribution strategy. Finally, experimental results on real scientific workflows and randomly generated graphs show that the proposed algorithm outperforms other algorithms in terms of energy reduction.

关键词： energy consumption heterogeneous distributed system reliability workflow

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