Robust scheduler for grid networks under uncertainties of both application demands and resource availability

Batista, Daniel Macêdo; Fonseca, Nelson L. S. da

doi:10.1016/j.comnet.2010.07.009

Cited by 20 publications

(30 citation statements)

References 17 publications

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“…Scheduling with uncertainly have been also extensively studed in grid networks with the relation to application demands and resource availability [44], and uncertainty of communication demands [45,46].…”

Section: Uncertainty In Data Sizementioning

confidence: 99%

CA-DAG: Modeling Communication-Aware Applications for Scheduling in Cloud Computing

Kliazovich¹,

Pecero²,

Tchernykh

et al. 2015

J Grid Computing

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This paper addresses performance issues of resource allocation in cloud computing. We review requirements of different cloud applications and identify the need of considering communication processes explicitly and equally to the computing tasks. Following this observation, we propose a new communication-aware model of cloud computing applications, called CA-DAG. This model is based on Directed Acyclic Graphs that in addition to computing vertices include separate vertices to represent communications. Such a representation allows making separate resource allocation decisions: assigning processors to handle computing jobs, and network resources for information transmissions. The proposed CA-DAG model creates space for optimization of a number of existing solutions to resource allocation and for developing novel scheduling schemes of improved efficiency.

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Section: Uncertainty In Data Sizementioning

confidence: 99%

CA-DAG: Modeling Communication-Aware Applications for Scheduling in Cloud Computing

Kliazovich¹,

Pecero²,

Tchernykh

et al. 2015

J Grid Computing

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“…Derbal presents in [31] an entropy-based quantification of input data uncertainty regarding resources performance. Batista and Fonseca deal with both application and resource availability uncertainties in [32]. Examples of studies in stochastic scheduling are Schopf [33] and earlier by Pinedo [34].…”

Section: Input Accuracymentioning

confidence: 99%

Scheduling in distributed systems: A cloud computing perspective

Bittencourt

Goldman

Madeira

et al. 2018

Computer Science Review

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Scheduling is essentially a decision-making process that enables resource sharing among a number of activities by determining their execution order on the set of available resources. The emergence of distributed systems brought new challenges on scheduling in computer systems, including clusters, grids, and more recently clouds. On the other hand, the plethora of research makes it hard for both newcomers researchers to understand the relationship among different scheduling problems and strategies proposed in the literature, which hampers the identification of new and relevant research avenues. In this paper we introduce a classification of the scheduling problem in distributed systems by presenting a taxonomy that incorporates recent developments, especially those in cloud computing. We review the scheduling literature to corroborate the taxonomy and analyze the interest in different branches of the proposed taxonomy. Finally, we identify relevant future directions in scheduling for distributed systems.1. α = P m : Identical machines in parallel. Execution environment is composed of m identical machines in parallel, as usually found in a cluster computing infrastructure.

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“…The HEFT (Heterogeneous Earliest-Finish-Time) scheduler [7] is a classical scheduler largely used to evaluate the performance of new grid scheduling approaches [8] [9]. It schedules tasks considering the criterium of the longest path leading to the final task in the DAG.…”

Section: Related Workmentioning

confidence: 99%

Embedding Software Requirements in Grid Scheduling

Batista

Chaves

Fonseca

2011

2011 IEEE International Conference on Communications (ICC)

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Both grid and cloud applications may require specific software for their execution. Introducing such requirements into the DAG describing the dependencies among the tasks of an application leads to a combinatorial problem with numerous possibilities of modified DAGs. This paper introduces an algorithm to obtain a single DAG with the minimum possible makespan by reducing the need for data transfer over the network.

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Robust scheduler for grid networks under uncertainties of both application demands and resource availability

Cited by 20 publications

References 17 publications

CA-DAG: Modeling Communication-Aware Applications for Scheduling in Cloud Computing

CA-DAG: Modeling Communication-Aware Applications for Scheduling in Cloud Computing

Scheduling in distributed systems: A cloud computing perspective

Embedding Software Requirements in Grid Scheduling

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