A Multiagent-Based Approach to the Grid-Scheduling Problem

Solar, Mauricio; Rojas, Jorge; Mendoza, Marcelo; Monge, Raúl; Parada, Víctor

doi:10.19153/15.2.5

Cited by 6 publications

(4 citation statements)

References 9 publications

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“…We argue that because of these characteristics, agents are a natural metaphor to understand complex and distributed systems [16]. Similarly, other related work that describes the involvements of MAS in Grid scheduling are well known [17][18][19][20][21].…”

Section: Related Workmentioning

confidence: 86%

“…Their work is similar to the one proposed in this paper, as it does not also require human intervention in workflow generation and in finding and allocating optimal resource for task execution. Similarly, other related work that describes the involvements of MAS in Grid scheduling are well known [17][18][19][20][21]. It, however, differs from the proposed approach because it does not rely on MAS and MPGP and does not shift the resource scheduling logic to autonomous multi-agents.…”

Section: Related Workmentioning

confidence: 99%

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Neural network‐based multi‐agent approach for scheduling in distributed systems

Ezugwu

Frîncu

Adediran

et al. 2016

Concurrency and Computation

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A distributed system consists of a collection of autonomous heterogeneous resources that provide resource sharing and a common platform for running parallel compute-intensive applications. The different application characteristics combined with the heterogeneity and performance variations of the distributed system make it difficult to find the optimal set of needed resources. When deployed, user applications are usually handled by application domain experts or system administrators who depending on the infrastructure provide a scheduling strategy for selecting the best candidate resource over a set of available resources. However, the provided strategy is usually generic, aimed at handling a wide array of applications and does not take into consideration specific application resource requirements. As such, an intelligent method for selecting the best resources based on expert knowledge is needed. In this paper, we propose a neural network-based multi-agent resource selection technique capable of mimicking the services of an expert user. In addition, to cope with the geographical distribution of the underlying system, we employ a multi-agent coordination mechanism. The proposed neural network-based scheduling framework combined with the multi-agent intelligence is a unique approach to efficiently deal with the resource selection problem. Results run on a simulated environment show the efficiency of our proposed method. Several scheduling simulations were conducted to compare the performance of some conventional resource selection methods against the proposed agent-based neural network technique. The results obtained indicate that the agent-based approach outperformed the classical algorithms by reducing the amount of time required to search for suitable resources irrespective of the resource size.Our system relies on both ANN and MPGP to train and coordinate team of agents on how to discover and select best candidate resource that matches users' application resource needs.

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Section: Related Workmentioning

confidence: 86%

Section: Related Workmentioning

confidence: 99%

Neural network‐based multi‐agent approach for scheduling in distributed systems

Ezugwu

Frîncu

Adediran

et al. 2016

Concurrency and Computation

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“…Applications include manufacturing shop scheduling, transportation scheduling, construction scheduling [5], power distribution scheduling, Grid-scheduling [6], meeting and course timetable scheduling [7], medical test scheduling, and project management. Agentbased approaches have several potential advantages for distributed manufacturing scheduling [8].…”

Section: A Transportation Scheduling Methodologiesmentioning

confidence: 99%

An environment friendly method to generate dynamic transportation routing in a distributed context

Archimède

Memon

2015

2015 International Conference on Industrial Engineering and Systems Management (IESM)

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Due to the globalization, today's manufacturing industry has to mobilize as many as resources in order to satisfy needs of every customer. At the same time, the production resources are more often geographically distributed. In this context, the necessary shifting of intermediate products as well as the final delivery requires transportation among different manufacturing sites, warehouses, consumers, etc. As the business of enterprises grows, transportation demands also grow with that, resulting problems of increasing transportation cost, environmental pollution and coordination between production and transportation operations. In order to address these problems, a possible solution is to better define the routing for transportation requests. This paper proposes an environment friendly method based on a reduced weighted graph with transportation resources competencies to generate dynamic routing between pickup and delivery locations according to shortest distance and time in order to facilitate consolidation and consequently cost and pollution reduction

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“…MAs represent a class of agents whose main functions are their transmission capabilities between nodes on the same network or different networks, in addition to the inherited capabilities of the well‐known classical static agents . A mobile agent (MA) is not bound to the system where it begins execution.…”

Section: Introductionmentioning

confidence: 99%

Scheduling multi‐component applications with mobile agents in heterogeneous distributed systems

Ezugwu

Junaidu

Frîncu

et al. 2015

Concurrency and Computation

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Summary In grid computing environment, several classes of multi‐component applications exist. These types of applications may often require additional resources of different types that go beyond what is available in any of the sites making up the grid resource composition. The heterogeneity nature of both the user application and the computing environment makes this a challenging problem. However, the current off‐the‐shelf scheduling software can hardly cope with these diversities in distributed computing application frameworks. Therefore, there is the need for an adequate scheduling system that would grant simultaneous or coordinated access to application of multi‐component nature that requires resources of possibly multiple types, in multiple locations, managed by different resource providers. The main focus of this paper is to develop a mobile agent scheduling model that addresses the aforementioned challenge. A scheduling policy that pertains to job scheduling and resource allocation is proposed. The scheduling policy treats different multi‐component applications requiring diverse heterogeneous resources fairly. The policy is used by mobile agents to schedule user applications and to also find available and suitable distributed resource that are capable of executing user application at a very minimal time. Copyright © 2015 John Wiley & Sons, Ltd.

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A Multiagent-Based Approach to the Grid-Scheduling Problem

Cited by 6 publications

References 9 publications

Neural network‐based multi‐agent approach for scheduling in distributed systems

Neural network‐based multi‐agent approach for scheduling in distributed systems

An environment friendly method to generate dynamic transportation routing in a distributed context

Scheduling multi‐component applications with mobile agents in heterogeneous distributed systems

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