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On the role of application and resource characterizations in heterogeneous distributed computing systems

CLUSTER computing-THE JOURNAL OF NETWORKS SOFTWARE TOOLS AND APPLICATIONS 2016年第4期19卷 2225-2240页

作者： Hwang, Eunji Kim, Seontae Kim, Jik-Soo Hwang, Soonwook Choi, Young-ri Ulsan Natl Inst Sci & Technol Ulsan South Korea KISTI Daejeon South Korea

Loosely coupled applications composed of a potentially very large number (from tens of thousands to even billions) of tasks are commonly used in high-throughput computing and many-task computing paradigms. To efficiently execute large-scale computations which can exceed the capability in a single type of computing resources within expected time, we should be able to effectively integrate resources from heterogeneous distributed computing (HDC) systems such as clusters, grids, and clouds. In this paper, we quantitatively analyze the performance of three different real scientific applications consisting of many tasks on top of HDC systems based on a partnership of distributed computing clusters, grids, and clouds to understand the application and resource characteristics, and show practical issues that normal scientific users can face during the course of leveraging these systems. Our experimental study shows that the performance of a loosely coupled application can be significantly affected by the characteristics of a HDC system, along with hardware specification of a node, and their impacts on the performance can vary widely depending on the resource usage pattern of each application. We then devise a preference-based scheduling algorithm that can reflect characteristics and resource usage patterns of various loosely coupled applications running on top of HDC systems from our experimental study. Our preference-based scheduling algorithm can allocate the resources from different HDC systems to loosely coupled applications based on the preferences of the applications for the HDC systems. We evaluate the overall system performance over various preference types, using trace-based simulations, which can be determined based on different factors such as CPU specifications and application throughputs. Our simulation results demonstrate the importance of understanding the application and resource characteristics on effective scheduling of loosely coupled applications on the

关键词： Loosely coupled applications High-throughput computing Many-task computing Performance evaluation heterogeneous distributed computing systems Scheduling algorithm

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Optimization procedure for algorithms of task scheduling in high performance heterogeneous distributed computing systems

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EGYPTIAN INFORMATICS JOURNAL 2011年第3期12卷 219-229页

作者： Bahnasawy, Nirmeen A. Omara, Fatma Koutb, Magdy A. Mosa, Mervat Cairo Univ Fac Comp & Sci Cairo Egypt Menoufia Univ Fac Engn Shibin Al Kawm Egypt

In distributed computing, the schedule by which tasks are assigned to processors is critical to minimizing the execution time of the application. However, the problem of discovering the schedule that gives the minimum execution time is NP-complete. In this paper, a new task scheduling algorithm called Sorted Nodes in Leveled DAG Division (SNLDD) is introduced and developed for HeDCSs with consider a bounded number of processors. The main principle of the developed algorithm is to divide the Directed Acyclic Graph (DAG) into levels and sort the tasks in each level according to their computation size in descending order. To evaluate the performance of the developed SNLDD algorithm, a comparative study has been done between the developed SNLDD algorithm and the Longest Dynamic Critical Path (LDCP) algorithm which is considered the most efficient existing algorithm. According to the comparative results, it is found that the performance of the developed algorithm provides better performance than the LDCP algorithm in terms of speedup, efficiency, complexity, and quality. Also, a new procedure called Superior Performance Optimization Procedure (SPOP) has been introduced and implemented in the developed SNLDD algorithm and the LDCP algorithm to minimize the sleek time of the processors in the system. Again, the performance of the SNLDD algorithm outperforms the existing LDCP algorithm after adding the SPOP procedure. (C) 2011 Faculty of Computers and Information, Cairo University. Production and hosting by Elsevier B. V. All rights reserved.

关键词： Task scheduling Directed acyclic graph Parallel processing heterogeneous distributed computing systems Sleek time

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CPTF-a new heuristic based branch and bound algorithm for workflow scheduling in heterogeneous distributed computing systems

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CCF TRANSACTIONS ON HIGH PERFORMANCE computing 2024年第5期6卷 472-487页

作者： Sirisha, D. Prasad, S. Sambhu Nadimpalli Satyanarayana Raju Inst Technol Visakhapatnam Andhra Pradesh India

Computationally intensive applications embodied as workflows entail interdependent tasks that involve multifarious computation requirements and necessitate heterogeneous distributed computing systems (HDCS) to attain high performance. The scheduling of workflows on HDCS was demonstrated as an NP-Complete problem. In the current work, a new heuristic based Branch and Bound (BnB) technique namely Critical Path_finish Time First (CPTF) algorithm is proposed for workflow scheduling on HDCS to achieve the best solutions. The primary merits of CPTF algorithm are due to the bounding functions that are tight and of less complexity. The sharp bounding functions could precisely estimate the promise of each state and aid in pruning infeasible states. Thus, the search space size is reduced. The CPTF algorithm explores the most promising states in the search space and converges to the solution quickly. Therefore, high performance is achieved. The experimental results on random and scientific workflows reveal that CPTF algorithm could effectively exploit high potency of BnB technique in realizing better quality solutions against the widely referred heuristic scheduling algorithms. The results on the benchmark workflows show that CPTF algorithm has improved schedules for 89.36% of the cases.

关键词： Workflow scheduling Task scheduling Heuristics heterogeneous distributed computing systems Branch and bound technique Makespan

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OBJECT ORIENTATION IN heterogeneous distributed computing systems

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COMPUTER 1993年第6期26卷 57-67页

作者： NICOL, JR WILKES, CT MANOLA, FA GTE Lab. Inc. Waltham MA

The basic properties of object orientation and their application to heterogeneous, autonomous, and distributed system to increase interoperability ar examined. It is argued that object-oriented distributed computing is a natural step forward from client-server systems. To support this claim, the differing levels of object-oriented support already found in commercially available distributed systems-in particular, the distributed computing environment of the open software foundation and the Cronus system of Bolt Beranek, Newman (BBN)-are discussed. Emerging object-oriented systems and standards are described, focusing on the convergence toward a least-common-denominator approach to object-oriented distributed computing embodied by the object management group's common object request broker architecture

关键词： BBN Cronus system client-server systems common object request broker architecture heterogeneous distributed computing systems interoperability object orientation object-oriented programming open software foundation open systems standards

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Performance Analysis of Loosely Coupled Applications in heterogeneous distributed computing systems

Performance Analysis of Loosely Coupled Applications in Hete...

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International Conference on Cloud and Autonomic computing (ICCAC 2015)

作者： Hwang, Eunji Kim, Seontae Yoo, Tae-kyung Kim, Jik-Soo Hwang, Soonwook Choi, Young-ri UNIST Sch Elect & Comp Engn Ulsan South Korea KISTI Natl Inst Supercomp & Networking Daejeon South Korea

ISBN: (纸本)9781467395663

Loosely coupled applications composed of a potentially very large number (from tens of thousands to even billions) of tasks are commonly used in High-Throughput computing (HTC) and Many-Task computing (MTC) paradigms. To efficiently execute large-scale computations which can exceed the capability in a single type of computing resources within expected time, we should be able to effectively integrate resources from heterogeneous distributed computing (HDC) systems such as Clusters, Grids, and Clouds. In this paper, we quantitatively analyze the performance of three different real scientific applications consisting of many tasks on top of HDC systems based on a Partnership of distributed computing Clusters, Grids, and Clouds to show practical issues that normal scientific users can face during the course of leveraging these systems. Our experimental results show that the performance of a loosely coupled application can be significantly affected by the characteristics of a HDC system, along with hardware specification of a node, and their impacts on the performance can vary widely depending on the resource usage pattern of each application. Throughout our extensive performance study with representative HDC systems and real scientific applications, we aim to give an insight to the research community on design and implementation of a next generation middleware system that can intelligently support large-scale loosely coupled applications by considering both of resource and application perspectives.

关键词： heterogeneous distributed computing systems Loosely coupled applications Performance evaluation

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Achieving Fairness-Aware Two-Level Scheduling for heterogeneous distributed systems

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IEEE TRANSACTIONS ON SERVICES computing 2021年第3期14卷 639-653页

作者： Hwang, Eunji Kim, Jik-Soo Choi, Young- ri UNIST Sch Elect & Comp Engn Ulsan 44919 South Korea Myongji Univ Dept Comp Engn Seoul 03674 South Korea

In a heterogeneous distributed system composed of various types of computing platforms such as supercomputers, grids, and clouds, a two-level scheduling approach can be used to effectively distribute resources of the platforms to users in the first-level, and map tasks of the users in nodes for each platform in the second-level for executing many-task applications. When scheduling heterogeneous resources, service providers of the system should consider the fairness among multiple users as well as the system efficiency. However, the fairness cannot be achieved by simply distributing an equal amount of resources from each platform to every user. In this paper, we investigate how to address the fairness issue among multiple users in a heterogeneous distributed system. We present three first-level resource allocation policies of a provider affinity first policy, an application affinity first policy, and a platform affinity based round-robin policy, and two second-level task mapping policies of a most affected first policy and a co-runner affinity based round-robin policy. Using trace-based simulations, we evaluate the performance of various combinations of the first and second level scheduling policies. Our extensive simulation results demonstrate that the first-level policy plays a crucial role to achieve relatively good fairness.

关键词： heterogeneous distributed computing systems two-level scheduling fairness high-throughput computing many-task computing

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Control and coordination of heterogeneous transaction processing systems

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INFORMATION AND SOFTWARE TECHNOLOGY 1997年第3期39卷 171-184页

作者： Bose, R Burd, SD Univ of New Mexico Albuquerque NM USA

Transaction processing systems (TPS) applications are a large component of most business organizations' investment in computer technology. heterogeneous and distributed computing environments have become essential and beneficial to most corporations. Thus, there is a need for tools to support the development of new distributed TPSs and the migration of existing TPSs to distributed environments. This paper presents the design and construction of a software tool that provides the functionalities necessary for the construction, operation and management of heterogenous distributed TPS applications. The tool design is based on object-orientation and real-time control and is implemented using Prolog and C. We anticipate that the tool will provide practical and significant benefits to the operators and maintainers of large-scale TPSs.

关键词： heterogeneous distributed computing systems transaction processing systems real-time control and coordination object-oriented computing logic programming

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HSGA: a hybrid heuristic algorithm for workflow scheduling in cloud systems

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CLUSTER computing-THE JOURNAL OF NETWORKS SOFTWARE TOOLS AND APPLICATIONS 2014年第1期17卷 129-137页

作者： Delavar, Arash Ghorbannia Aryan, Yalda Payame Noor Univ Dept Comp Tehran Iran

In heterogeneous distributed computing systems like cloud computing, the problem of mapping tasks to resources is a major issue which can have much impact on system performance. For some reasons such as heterogeneous and dynamic features and the dependencies among requests, task scheduling is known to be a NP-complete problem. In this paper, we proposed a hybrid heuristic method (HSGA) to find a suitable scheduling for workflow graph, based on genetic algorithm in order to obtain the response quickly moreover optimizes makespan, load balancing on resources and speedup ratio. At first, the HSGA algorithm makes tasks prioritization in complex graph considering their impact on others, based on graph topology. This technique is efficient to reduction of completion time of application. Then, it merges Best-Fit and Round Robin methods to make an optimal initial population to obtain a good solution quickly, and apply some suitable operations such as mutation to control and lead the algorithm to optimized solution. This algorithm evaluates the solutions by considering efficient parameters in cloud environment. Finally, the proposed algorithm presents the better results with increasing number of tasks in application graph in contrast with other studied algorithms.

关键词： heterogeneous distributed computing systems Cloud computing Workflow scheduling Heuristic Genetic Algorithm

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Parallel Task Graphs Scheduling Based on the Internal Structure 18th

Parallel Task Graphs Scheduling Based on the Internal Struct...

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18th Mexican International Conference on Artificial Intelligence (MICAI)

作者： Velarde Martinez, Apolinar Inst Tecnol El Llano Aguascalientes Carretera Aguascalientes San Luis Potosi Km 18 Aguascalientes Aguascalientes Mexico

ISBN: (纸本)9783030337490;9783030337483

It is well known that Parallel Task Graphs (PTG) are modeled with Directed Acyclic Graphs (DAG Tasks). DAG tasks are scheduled in heterogeneous distributed computing systems (HDCS) for execution with different techniques which seek to reduce completion of each PTG. Proposed planning techniques generally only make use of the critical path in planning as an internal characteristic of the DAG Task, helping to optimize scheduling. In this study it is shown that analyzing other internal characteristics, such as layering and graph density aside from the critical path of DAG workflow tasks, before being scheduled in execution locations, can improve computer system performance, as well as optimize the use of their resources. For the above, the internal characteristics considered in this study of each DAG task are: the critical path, layering as well as graph density. The analyzed DAG tasks are synthetic loads produced with a graph generation algorithm as well as real application graphs. The findings obtained with the experiments performed show that the distribution estimation algorithm obtains better response times than the genetic algorithm.

关键词： Directed Acyclic Graph Parallel Task Graphs heterogeneous distributed computing systems

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