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Mobile Agent Based Distributed Network Architecture with Map Reduce Programming Model

机译:带有Map Reduce编程模型的基于移动代理的分布式网络架构

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In the recent years, the demand for data processing has been on the rise prompting researchers to investigate new ways of managing data. Our research delves into the emerging trends of data management methods, one of which is the agent based techniques and the active disk technology and also the use of Map-reduce functions in unstructured data management. Motivated by this new trend, our architecture employs mobile agents technology to develop an open source framework called SPADE to implement a simulation platform called SABSA. The architecture in this research compares the performance of four network storage architectures: Store and forward processes(SAF), Object Storage Devices(OSD), Mobile agent with a Domain Controller (DMC) enhanced with map-reduce function and Mobile agent with a Domain Controller and child DMC enhanced with Map-reduce (ABMR): both handling sorted and unsorted metadata. In order to accurately establish the performance improvements in the new hybrid agent based models and map-reduce functions, an analytic simulation model on which experiments based on the identified storage architectures were performed was developed and then analytical data and graphs were generated. The results indicated that all the agents based storage architectures minimize latencies by up to 45 % and reduce access time by up to 21% compared to SAF and OSD.
机译:近年来,对数据处理的需求一直在上升,促使研究人员研究新的数据管理方式。我们的研究深入研究了数据管理方法的新兴趋势,其中之一是基于代理的技术和活动磁盘技术,以及在非结构化数据管理中使用Map-reduce功能的方法。受这一新趋势的启发,我们的体系结构采用了移动代理技术来开发一个名为SPADE的开源框架,以实现一个名为SABSA的仿真平台。本研究中的体系结构比较了四种网络存储体系结构的性能:存储和转发进程(SAF),对象存储设备(OSD),具有域控制器(DMC)的移动代理(具有映射减少功能)和具有域的移动代理控制器和子DMC借助Map-reduce(ABMR)进行了增强:处理已排序和未排序的元数据。为了准确地建立新的基于混合代理的模型和map-reduce函数的性能改进,开发了一个解析模拟模型,在该模型上进行了基于已确定存储结构的实验,然后生成了分析数据和图形。结果表明,与SAF和OSD相比,所有基于代理的存储体系结构都将延迟降低了多达45%,并将访问时间减少了多达21%。

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