A dynamic scheme for scheduling complex tasks in manufacturing systems based on collaboration of agents

Hsieh, Fu-Shiung; Lin, Jim-Bon

doi:10.1007/s10489-014-0521-5

Cited by 27 publications

(10 citation statements)

References 50 publications

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“…The issues pertaining to scheduling task on multiple workers has been widely studied in distributed, parallel, grid and cluster computing and in recent year the same kind of study is been carried out considering virtual workers on cloud environment. The techniques adopted by these models differ from characteristic of workload, resources, performance metric and scheduling in multiagent architecture [11]. All these methodologies are designed based on Heuristic Algorithm, Meta-Heuristic Algorithm, Scientific Workflows Execution, Deadline-aware Scheduling and Multi-tenant SaaS Applications, which is extensively researched in the presented work.…”

Section: Research Methodolodymentioning

confidence: 99%

An efficient resource sharing technique for multi-tenant databases

Pallavi¹,

Jayarekha²

2020

IJECE

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Multi-tenancy is one of the key components of cloud computing environment. Multi-tenant database system in SaaS (Software as a Service) has gained a lot of attention in academics, research and business arena. These database systems provide scalability and economic benefits for both cloud service providers and customers(organizations/companies referred as tenants) by sharing same resources and infrastructure in isolation of shared databases, network and computing resources with Service level agreement (SLA) compliances. In a multitenant scenario, active tenants compete for resources in order to access the database. If one tenant blocks up the resources, the performance of all the other tenants may be restricted and a fair sharing of the resources may be compromised. The performance of tenants must not be affected by resource-intensive activities and volatile workloads of other tenants. Moreover, the prime goal of providers is to accomplish low cost of operation, satisfying specific schemas/SLAs of each tenant. Consequently, there is a need to design and develop effective and dynamic resource sharing algorithms which can handle above mentioned issues. This work presents a model embracing a query classification and worker sorting technique to efficiently share I/O, CPU and Memory thus enhancing dynamic resource sharing and improvising the utilization of idle instances proficiently. The model is referred as Multi-Tenant Dynamic Resource Scheduling Model (MTDRSM) .The MTDRSM support workload execution of different benchmark such as TPC-C(Transaction Processing Performance Council), YCSB(The Yahoo! Cloud Serving Benchmark)etc. and on different database such as MySQL, Oracle, H2 database etc. Experiments are conducted for different benchmarks with and without SLA compliances to evaluate the performance of MTDRSM in terms of latency and throughput achieved. The experiments show significant performance improvement over existing Mute Bench model in terms of latency and throughput.

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Section: Research Methodolodymentioning

confidence: 99%

An efficient resource sharing technique for multi-tenant databases

Pallavi¹,

Jayarekha²

2020

IJECE

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“…Así por ejemplo Algarvio, Lopes, & Santana aportan con un modelo para ayudar a gestionar la complejidad de los mercados energéticos [5]. Hsieh & Lin proponen una metodología de solución para la programación de flujos de trabajo en sistemas multi-agente (MAS) [6]. Lopes, Algarvio, & Coelho proporcionan una herramienta orientada al uso de agentes de software en el comercio bilateral de la electricidad [7].…”

Section: Introductionunclassified

“…SIIPRIN-CITEGCEl documento[6] es una investigación donde se menciona que los sistemas MAS (Sistemas Multi Agente) proporcionan un paradigma para modelar estas características, las tareas de programación en MAS es un problema complejo debido a la arquitectura distribuida para programar tareas por agentes individuales y la dependencia de flujos de trabajo de diferentes agentes, este documento nos dice que se combina los sistema de arquitectura para descubrir dinámicamente servicios, flujo de trabajo y modelos de actividad para especificar las capacidades de los agentes, contratar protocolo de red para facilitar la negociación y coordinación de agentes y teorías de optimización.El trabajo[3] es de tipo observación, en este contexto, el uso de agentes inteligentes para automatizar el proceso surge como una herramienta importante para facilitar esta actividad, este documento presenta pautas para la elaboración de un modelo de negociación basado en agentes para abordar el problema de seleccionar proveedores en el campo de la industria minorista [52]. es un caso de estudio donde se describen en detalle los problemas de agregación, forrajeo, agrupamiento y clasificación de objetos, navegación, formación de trayectorias, despliegue, manipulación colaborativa y asignación de tareas, por lo que nos explica que los principios de inteligencia de enjambre se han estudiado ampliamente y se han aplicado a una serie de tareas diferentes en las que se utiliza un grupo de robots autónomos para resolver un problema con un enfoque distribuido, es decir, sin coordinación central.En los trabajos de tipo modelo se busca crear un tipo prototipo que permite ser referencia de procesos de la misma naturaleza creando un estándar mediante el uso de los sistemas multi-agente.5.…”

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Characterization of Multi-agent systems: A systematic mapping study

Espinosa

Palma

Caizabuano

2020

KEG

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Multi-agent systems have gained a lot of interest in articles, conferences and magazines. However, it is still a recent issue which is not understood or the scope of it is unknown. The objective of this work is to investigate in more detail the articles and to build a preliminary classification system to structure the field of Multi-agent systems. As a result, an overview of this area of research can be obtained through the response to the research questions posed. Resumen. Los sistemas multi-agente han ganado un interés muy grande en artículos, conferencias y revistas. Sin embargo sigue siendo un tema reciente el cual no se comprende ni se conoce los alcances del mismo. Este trabajo tiene como objetivo investigar con más detalle los artículos y construir un sistema de clasificación preliminar para estructurar el campo de los sistemas Multi-agente. Como resultado, se espera proporcionar una visión general de esta área de investigación a través de responder a las preguntas de investigación planteadas. Creemos que el presente trabajo será una herramienta que encontrará ámbitos todavía aun no investigados.

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“…Heuristic algorithms were broadly created keeping in mind the end goal to achieve an optimal configuration [9][10][11][12]. In any case, there is no specific asset administration structure for scheduling computational work flow in multi-tenant cloud computing situations [13][14][15].…”

Section: Introductionmentioning

confidence: 99%

Review of Advancements in Multi-tenant Framework in Cloud Computing

Suresh

Kannan

2018

IJEECS

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As the cloud computing is gaining more user base the problem of simultaneously catering computational resources to multitude of users or their application is on rise. It remains a critical problem and pose hindrance in scalability of cloud computing. Thus, in order to layout the proper solution for the mentioned problem; it is necessary to sum up a proper knowledge based of the existing solution, there drawbacks and a detail analysis of its performances. In this study we present a review of multi-tenant frameworks and approaches used in the industry which reaps advantages to facilitate multi-tenancy.

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A dynamic scheme for scheduling complex tasks in manufacturing systems based on collaboration of agents

Cited by 27 publications

References 50 publications

An efficient resource sharing technique for multi-tenant databases

An efficient resource sharing technique for multi-tenant databases

Characterization of Multi-agent systems: A systematic mapping study

Review of Advancements in Multi-tenant Framework in Cloud Computing

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