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Observing Network Performance and Congestion on Managing Assets with RFID and Cloud Computing

Journal of Computer and Communications 2017年第9期5卷 43-66页

作者： Leandro Andrioli Rodrigo da Rosa Righi Cristiano André da Costa lucas graebin Applied Computing Graduate Program Universidade do Vale do Rio dos Sinos (Unisinos) S&#227 o Leopoldo RS Brazil

Today, we observe that more and more, radio frequency identification (RFID) technology has been used to identify and track objects in enterprises and institutions. In addition, we also perceive the growing adoption of cloud computing, either public or private, to process and store data from the objects. In this context, the literature does not present an initiative that looks into the network on enterprise-cloud interactions, so neglecting network performance and congestion information when transmitting data to the cloud. Thus, we are presenting a model named ACMA—Automatic Control and Management of Assets. ACMA employs context awareness to control and monitor corporate assets in companies with multiple units. ACMA provides a centralized point of access in the cloud in which interested actors can get online data about each corporate asset. In particular, our scientific contribution consists in considering network congestion to control dynamically the data updating interval from sensors to the cloud. The idea is to search for reliability and integrity of operations, without losing or corrupting data when updating the information to cloud. Thus, this article describes the ACMA model, its architecture, algorithms and features. In addition, we describe the evaluation methodology and the results obtained through experiments and simulations based on the developed prototype.

关键词： Internet of Things RFID Cloud Computing Network Congestion Adaptivity Assets

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Adaptively and Efficiency： Key Features for Getting Performance on Process Migration

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通讯和计算机（中英文版） 2012年第5期9卷 495-506页

作者： Rodrigo da Rosa Righi lucas graebin Programa Interdisciplinar de Pos-Graduacao em Computacao Aplieada(PIPCA) Universidade do Vale do Rio dos SinosSaoLeopoldo 93.022-000Brazil

In this paper we will describe a model for BSP (Bulk Synchronous Parallel) processes rescheduling called MigBSP. Considering the scope of BSP applications, its differential approach is the combination of three metrics - Memory, Computation and Communication-in order to measure the Potential of Migration of each BSP process. In this context, this paper addresses both the efficiency and the adaptively perspectives of this model over our multi-cluster architecture. MigBSP presents significant gains of performance as well as a low overhead on application execution. Model"s adaptation is expressed through the self-management control of rescheduling calls based on system state: if processes are balanced or not and if a pattern without migrations is found on the rescheduling calls. Finally, the results indicate that MigBSP is a viable solution to manage BSP processes migration on multi-cluster architectures.

关键词：迁移性能自适应进程流程模型应用程序管理控制 BSP 效率比

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