Conference Paper

Design and analysis of a dynamic scheduling strategy with resource estimation for large-scale Grid systems

Department of Electrical & Computer Engineering , National University of Singapore, Tumasik, 00, Singapore
DOI: 10.1109/GRID.2004.19 Conference: Grid Computing, 2004. Proceedings. Fifth IEEE/ACM International Workshop on
Source: DBLP


In this paper, we present a resource conscious dynamic scheduling strategy for handling large volume computationally intensive loads in a grid system involving multiple sources and sinks/processing nodes. We consider a "pull-based" strategy, wherein the processing nodes request load from the sources. We employ the Incremental Balancing Strategy (IBS) algorithm proposed in the literature and propose a buffer estimation strategy to derive optimal load distribution. We consider nontime critical loads that arrive at arbitrary times with time varying buffer availability at sinks and utilize buffer reclamation techniques so as to schedule the loads. We demonstrate detailed workings of the proposed algorithm with illustrative examples using real-life parameters derived from STAR experiments in BNL for scheduling large volume loads.

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Available from: Thomas Robertazzi, Mar 10, 2014
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    • "A few Grid scheduling algorithms can be considered as ondemand scheduling since they make scheduling decisions based on the current status of the Grid. Examples include a pullbased scheduler proposed by Viswanathan et al. [30] and theoretical work by Rosenberg et al. [27] [28] "
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    ABSTRACT: In a large-scale distributed infrastructure, users and administrators typically desire to perform on-demand operations that act upon the most up-to-date state of the infrastructure. These on-demand operations range from monitoring the up-to-date machine properties in the infrastructure, to making Grid scheduling decisions for different tasks based on the current status of the infrastructure. However, the scale and dynamism present in the operating environment make it challenging to support these operations efficiently. This paper discusses several on-demand operations that we have been studying, challenges associated with them, and how to meet the challenges. Specifically, we build techniques for 1) on-demand group monitoring that allows users and administrators of an infrastructure to query and aggregate the up-to-date state of the machines (e.g., CPU utilization) in a group or multiple groups, 2) an on-demand Grid scheduling strategy that makes scheduling decisions based on the current availability of compute nodes, 3) another on-demand Grid scheduling strategy that chooses the best algorithm for the current input data set among multiple algorithms available. We also present our ongoing work.
    Preview · Article · Sep 2008
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    • "Another similar work is [18], it develops several DLT scheduling algorithms on a Grid deploying middware named APST-DV. A new kind of approaches considering multi sources are developed recently[19] [20] [21], but It is usually hard to handle the complex source-sink relations between processing nodes. Yet all these works suppose that the topology of the Grid environment is determined before develop scheduling and won't change or only change little. "
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    ABSTRACT: Abstract According to the special features of the dynamic heterogeneous grid environment, a loose-coupled and scalable resource model is described by a ,hybrid multi-level tree reflecting actual networks ,for organizing distributed resources. The resource model ismaintained in a distributed way, making it loose- coupled and scalable, which ispractical for many grid applications, especially for sequence analysis in Bioinformatics. Algorithms of resource location and job scheduling are discussed. The divisible load theory (DLT) is introduced ,to grid ,computing through applying divisible load scheduling on the model, an algorithm called recursively equivalence is presented to overcome difficulties in developing DLT analysis on the dynamic heterogeneous tree. Experiment result is presented to evaluate the model.
    Full-text · Conference Paper · Jan 2006
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    • "We will show a significant impact on the load scheduling strategies due to these buffer constraints. Since the origination of DLT, the research has spanned from addressing the general optimal scheduling problem on different network architectures to various scenarios with different practical constraints, such as time-varying channels [32], minimizing cost factors [33], resource management in Grid environments [29] [35], and distributed image processing [27]. Thorough surveys of DLT can be found in [4] [10] [17] [31]. "
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    ABSTRACT: This chapter investigates scheduling a divisible task in distributed memory systems with finite-size buffer constraints. Two types of network topologies are considered: a single-level tree network and a m-dimensional hypercube network. First, this chapter presents the closed-form solutions for the case with infinite-size buffers. Based on these solutions, an iterative strategy, referred to as Incremental Balancing Strategy (IBS), is proposed towards optimal performance. Algorithm IBS adopts a strategy to feed the divisible load in a step-by-step incremental balancing fashion by taking advantage of the available closed-form solutions of the optimal scheduling for the case without buffer size constraints. Based on the rigorous mathematical analysis, a number of interesting and useful properties exhibited by the algorithm is proved. Numerical examples are presented to ease the understanding.
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