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Article
Publication date: 7 November 2016

Junfei Chu, Jie Wu, Qingyuan Zhu and Jiasen Sun

Resource scheduling is the study of how to effectively measure, evaluate, analyze, and dispatch resources in order to meet the demands of corresponding tasks. Aiming at…

Abstract

Purpose

Resource scheduling is the study of how to effectively measure, evaluate, analyze, and dispatch resources in order to meet the demands of corresponding tasks. Aiming at the problem of resource scheduling in the private cloud environment, the purpose of this paper is to propose a resource scheduling approach from an efficiency priority point of view.

Design/methodology/approach

To measure the computational efficiencies for the resource nodes in a private cloud environment, the data envelopment analysis (DEA) approach is incorporated and a suitable DEA model is proposed. Then, based on the efficiency scores calculated by the proposed DEA model for the resource nodes, the 0-1 programming technique is introduced to build a simple resource scheduling model.

Findings

The proposed DEA model not only has the ability of ranking all the decision-making units into different positions but also can handle non-discretionary inputs and undesirable outputs when evaluating the resource nodes. Furthermore, the resource scheduling model can generate for the calculation tasks an optimal resource scheduling scheme that has the highest total computational efficiency.

Research limitations/implications

The proposed method may also be used in studies of resource scheduling studies in the environments of public clouds and hybrid clouds.

Practical implications

The proposed approach can achieve the goal of resource scheduling in private cloud computing platforms by attaining the highest total computational efficiency, which is very significant in practice.

Originality/value

This paper uses an efficiency priority point of view to solve the problem of resource scheduling in private cloud environments.

Details

Kybernetes, vol. 45 no. 10
Type: Research Article
ISSN: 0368-492X

Keywords

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Article
Publication date: 1 June 1988

R.P. Mohanty

Historically, scheduling of production activities has been one of the most important management problems. Scheduling involves the planning and the co‐ordination of the…

Abstract

Historically, scheduling of production activities has been one of the most important management problems. Scheduling involves the planning and the co‐ordination of the various activities to achieve the optimum utilisation of resources over a given time period. Production scheduling differs with the typology of the production systems. Various production systems that are encountered in practice are: continuous production, mass production, batch production, job shop production and projects. In this article, we attempt only to discuss the project scheduling problems.

Details

Management Research News, vol. 11 no. 6
Type: Research Article
ISSN: 0140-9174

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Article
Publication date: 19 October 2012

Premaratne Samaranayake and Senevi Kiridena

The purpose of this paper is to examine how certain limitations of the current approaches to planning and scheduling of aircraft heavy maintenance can be addressed using a…

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3032

Abstract

Purpose

The purpose of this paper is to examine how certain limitations of the current approaches to planning and scheduling of aircraft heavy maintenance can be addressed using a single integrated framework supported by unified data structures.

Design/methodology/approach

The “unitary structuring technique”, originally developed within the context of manufacturing planning and control, is further enhanced for aircraft heavy maintenance applications, taking into account the uncertainty associated with condition‐based maintenance. The proposed framework delivers the advanced functionalities required for simultaneous and dynamic forward planning of maintenance operations, as well as finite loading of resources, towards optimising the overall maintenance performance.

Findings

Execution of maintenance operations under uncertainty involves materials changes, rectification and re‐assembly. It is shown that re‐scheduling of materials (spare‐parts), resources and operations can be taken care of by simultaneous and dynamic forward planning of materials and operations with finite loading of resources, using the integrated framework.

Research limitations/implications

As part of adopting the proposed framework in practice, it needs to be guided by an overall methodology appropriate for application‐specific contexts.

Practical implications

The potential direct benefits of adopting the proposed framework include on‐time project completion, reduced inventory levels of spare‐parts and reduced overtime costs.

Originality/value

Existing approaches to aircraft maintenance planning and scheduling are limited in their capacity to deal with contingencies arising out of inspections carried out during the execution phase of large maintenance projects. The proposed integrated approach is, capable of handling uncertainty associated with condition‐based maintenance, due to the added functionalities referred to above.

Details

Journal of Quality in Maintenance Engineering, vol. 18 no. 4
Type: Research Article
ISSN: 1355-2511

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Article
Publication date: 31 January 2020

Guan-hong Zhang, Odbal and Karlo Abnoosian

Today, with the rapid growth of cloud computing (CC), there exist several users that require to execute their tasks by the available resources to obtain the best…

Abstract

Purpose

Today, with the rapid growth of cloud computing (CC), there exist several users that require to execute their tasks by the available resources to obtain the best performance, reduce response time and use resources. However, despite the significance of the scheduling issue in CC, as far as the authors know, there is not any systematic and inclusive paper about studying and analyzing the recent methods. This paper aims to review the current mechanisms and techniques, which can be addressed in this area.

Design/methodology/approach

The central purpose of this paper refers to offering a complete study of the state-of-the-art planning algorithms in the cloud and also instructions for future research. Besides, this paper offers a methodological analysis of the scheduling mechanisms in the cloud environment.

Findings

The central role of this paper is to present a summary of the present issues related to scheduling in the cloud environment, providing a structure of some popular techniques in cloud scheduling scope and defining key areas for the development of cloud scheduling techniques in the future research.

Research limitations/implications

In this paper, scheduling mechanisms are classified into two main categories include deterministic and non-deterministic algorithms; however, it can also be classified into different categories. In addition, the selection of all related papers could not be ensured. It is possible that some appropriate and related papers were removed in the search process.

Practical implications

According to the results of this paper, the requirement for more suitable algorithms exists to allocate tasks for resources in cloud environments. In addition, some principal rules in cloud scheduling should be re-evaluated to achieve maximum productivity and minimize wasted expense and effort. In this direction, to stay away from overloading and under loading of components and resources, the proposed method should execute workloads in an adaptable and scalable way. As the number of users increased in cloud environments, the number of tasks in the cloud that needed to be scheduled proportionally increased. Thus, an efficient mechanism is needed for scheduling tasks in these environments.

Originality/value

The general information gathered in this study makes the researchers acquainted with the state-of-the-art scheduling area of the cloud. Entirely, the answers to the research questions summarized the main objective of scheduling, current challenges, mechanisms and methods in the cloud systems. The authors hope that the results of this paper lead researchers to present more efficient scheduling techniques in cloud systems.

Details

Kybernetes, vol. 49 no. 12
Type: Research Article
ISSN: 0368-492X

Keywords

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Article
Publication date: 18 July 2019

Rok Cajzek and Uroš Klanšek

The purpose of this paper is cost optimization of project schedules under constrained resources and alternative production processes (APPs).

Abstract

Purpose

The purpose of this paper is cost optimization of project schedules under constrained resources and alternative production processes (APPs).

Design/methodology/approach

The model contains a cost objective function, generalized precedence relationship constraints, activity duration and start time constraints, lag/lead time constraints, execution mode (EM) constraints, project duration constraints, working time unit assignment constraints and resource constraints. The mixed-integer nonlinear programming (MINLP) superstructure of discrete solutions covers time–cost–resource options related to various EMs for project activities as well as variants for production process implementation.

Findings

The proposed model provides the exact optimal output data for project management, such as network diagrams, Gantt charts, histograms and S-curves. In contrast to classic scheduling approaches, here the optimal project structure is obtained as a model-endogenous decision. The project planner is thus enabled to achieve optimization of the production process simultaneously with resource-constrained scheduling of activities in discrete time units and at a minimum total cost.

Practical implications

A set of application examples are addressed on an actual construction project to display the advantages of proposed model.

Originality/value

The unique value this paper contributes to the body of knowledge reflects through the proposed MINLP model, which is capable of performing the exact cost optimization of production process (where presence and number of activities including their mutual relations are dealt as feasible alternatives, meaning not as fixed parameters) simultaneously with the associated resource-constrained project scheduling, whereby that is achieved within a uniform procedure.

Details

Engineering, Construction and Architectural Management, vol. 26 no. 10
Type: Research Article
ISSN: 0969-9988

Keywords

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Article
Publication date: 25 October 2021

Mandeep Kaur, Rajinder Sandhu and Rajni Mohana

The purpose of this study is to verify that if applications categories are segmented and resources are allocated based on their specific category, how effective scheduling

Abstract

Purpose

The purpose of this study is to verify that if applications categories are segmented and resources are allocated based on their specific category, how effective scheduling can be done?.

Design/methodology/approach

This paper proposes a scheduling framework for IoT application jobs, based upon the Quality of Service (QoS) parameters, which works at coarse grained level to select a fog environment and at fine grained level to select a fog node. Fog environment is chosen considering availability, physical distance, latency and throughput. At fine grained (node selection) level, a probability triad (C, M, G) is anticipated using Naïve Bayes algorithm which provides probability of newly submitted application job to fall in either of the categories Compute (C) intensive, Memory (M) intensive and GPU (G) intensive.

Findings

Experiment results showed that the proposed framework performed better than traditional cloud and fog computing paradigms.

Originality/value

The proposed framework combines types of applications and computation capabilities of Fog computing environment, which is not carried out to the best of knowledge of authors.

Details

International Journal of Pervasive Computing and Communications, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1742-7371

Keywords

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Article
Publication date: 1 November 1993

Oya Icmeli, S. Selcuk Erenguc and Christopher J. Zappe

A survey of project scheduling problems since 1973 limited to workdone specifically in the project scheduling area (although severaltechniques developed for assembly line…

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1834

Abstract

A survey of project scheduling problems since 1973 limited to work done specifically in the project scheduling area (although several techniques developed for assembly line balancing and job‐shop scheduling can be applicable to project scheduling): the survey includes the work done on fundamental problems such as the resource‐constrained project scheduling problem (RCPSP); time/cost trade‐off problem (TCTP); and payment scheduling problem (PSP). Also discusses some recent research that integrates RCPSP with either TCTP or PSP, and PSP with TCTP. In spite of their practical relevance, very little work has been done on these combined problems to date. The future of the project scheduling literature appears to be developing in the direction of combining the fundamental problems and developing efficient exact and heuristic methods for the resulting problems.

Details

International Journal of Operations & Production Management, vol. 13 no. 11
Type: Research Article
ISSN: 0144-3577

Keywords

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Article
Publication date: 1 May 1993

Ellen J. Dumond and John Dumond

Effective management of resources in a dynamic, multiprojectenvironment requires consideration of two key issues: the availabilityof each of the multiple resources and the…

Abstract

Effective management of resources in a dynamic, multiproject environment requires consideration of two key issues: the availability of each of the multiple resources and the method of scheduling these resources to complete activities and, subsequently, projects. Identifies the trade‐offs between performance and the availability of multiple resources, when some resources are more costly than others. Finds that there are significant effects when the level of either the costly resources or the cheaper resources are varied, that trade‐offs can be made by reducing the availability of the costly resources and increasing the availability of the cheaper resources and that the improvement in completion time performance is reasonably linear over the tested ranges and the rates of improvement differ over the ranges. Describes the resource allocation factors and treatments as well as the scheduling heuristics. Uses a finite scheduling algorithm along with the prioritization heuristics to schedule the constrained multiple resources simultaneously and a simulation to replicate the environment. Develops linear regressions to provide further insight.

Details

International Journal of Operations & Production Management, vol. 13 no. 5
Type: Research Article
ISSN: 0144-3577

Keywords

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Article
Publication date: 24 August 2020

Ambika Aggarwal, Priti Dimri, Amit Agarwal and Ashutosh Bhatt

In general, cloud computing is a model of on-demand business computing that grants a convenient access to shared configurable resources on the internet. With the increment…

Abstract

Purpose

In general, cloud computing is a model of on-demand business computing that grants a convenient access to shared configurable resources on the internet. With the increment of workload and difficulty of tasks that are submitted by cloud consumers; “how to complete these tasks effectively and rapidly with limited cloud resources?” is becoming a challenging question. The major point of a task scheduling approach is to identify a trade-off among user needs and resource utilization. However, tasks that are submitted by varied users might have diverse needs of computing time, memory space, data traffic, response time, etc. This paper aims to proposes a new way of task scheduling.

Design/methodology/approach

To make the workflow completion in an efficient way and to reduce the cost and flow time, this paper proposes a new way of task scheduling. Here, a self-adaptive fruit fly optimization algorithm (SA-FFOA) is used for scheduling the workflow. The proposed multiple workflow scheduling model compares its efficiency over conventional methods in terms of analysis such as performance analysis, convergence analysis and statistical analysis. From the outcome of the analysis, the betterment of the proposed approach is proven with effective workflow scheduling.

Findings

The proposed algorithm is more superior regarding flow time with the minimum value, and the proposed model is enhanced over FFOA by 0.23%, differential evolution by 2.48%, artificial bee colony (ABC) by 2.85%, particle swarm optimization (PSO) by 2.46%, genetic algorithm (GA) by 2.33% and expected time to compute (ETC) by 2.56%. While analyzing the make span case, the proposed algorithm is 0.28%, 0.15%, 0.38%, 0.20%, 0.21% and 0.29% better than the conventional methods such as FFOA, DE, ABC, PSO, GA and ETC, respectively. Moreover, the proposed model has attained less cost, which is 2.14% better than FFOA, 2.32% better than DE, 3.53% better than ABC, 2.43% better than PSO, 2.07% better than GA and 2.90% better than ETC, respectively.

Originality/value

This paper presents a new way of task scheduling for making the workflow completion in an efficient way and for reducing the cost and flow time. This is the first paper uses SA-FFOA for scheduling the workflow.

Details

Kybernetes, vol. 50 no. 6
Type: Research Article
ISSN: 0368-492X

Keywords

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Article
Publication date: 7 June 2011

Tarek Helmy and Zeehasham Rasheed

Grid computing is gaining more significance in the high‐performance computing world. This concept leads to the discovery of solutions for complicated problems regarding…

Abstract

Purpose

Grid computing is gaining more significance in the high‐performance computing world. This concept leads to the discovery of solutions for complicated problems regarding the diversity of available resources among different jobs in the grid. However, the major problem is the optimal job scheduling for heterogeneous resources, in which each job needs to be allocated to a proper grid's node with the appropriate resources. An important challenge is to solve optimally the scheduling problem, because the capability and availability of resources vary dynamically and the complexity of scheduling increases with the size of the grid. The purpose of this paper is to present a framework which combines the fuzzy C‐mean (FCM) clustering with an ant colony optimization (ACO) algorithm to improve the scheduling decision when the grid is heterogeneous.

Design/methodology/approach

In the proposed model, the FCM algorithm classifies the jobs into appropriate classes, and the ACO algorithm maps the jobs to the appropriate resources. The ACO is characterized by ant‐like mobile agents that cooperate and stochastically explore a network, iteratively building solutions based on their own memory and on the traces (pheromone levels) left by other agents.

Findings

The simulation is done by using historical information on jobs in a grid. The experimental results show that the proposed algorithm can allocate jobs more efficiently and more effectively than the traditional algorithms for scheduling policies.

Originality/value

The paper provides a scheduling model based on FCM clustering and ACO algorithm for grid scheduling. The authors compared the performance of the proposed algorithm with the performance of various job‐scheduling algorithms in the grid computing environment. The comparison results show that the proposed algorithm outperforms other algorithms and gives optimal results.

Details

International Journal of Intelligent Computing and Cybernetics, vol. 4 no. 2
Type: Research Article
ISSN: 1756-378X

Keywords

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