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首页> 外文期刊>Parallel and Distributed Systems, IEEE Transactions on >Dynamic Aggregate: An Elastic Framework for QoS-Aware Distributed Processing of RFID Data on Enterprise Hierarchy
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Dynamic Aggregate: An Elastic Framework for QoS-Aware Distributed Processing of RFID Data on Enterprise Hierarchy

机译：动态聚合：用于企业层级上RFID数据的QoS感知分布式处理的弹性框架

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摘要

Enterprise RFID data management is highly challenging not only because of the huge volume of data from distributed sources, but particularly because of the dynamic nature of the reader inputs. With user-designated quality of service (QoS) requirements, the data management system must be able to dynamically detect the status changes of the RFID inputs and adjust the processing strategies for continuously maintaining the desired level of QoS. We propose a QoS-aware framework for modeling the enterprise data service problem, and for on-line adaptive processing of distributed RFID data streams. The data processing structure is modeled as a hierarchy of aggregation nodes in accordance with the structure of an organization. Leaf nodes correspond to the RFID streaming inputs. A set of aggregation/deaggregation operations is devised to adjust the processing granularity level based on QoS dynamics. A QoS constrained query issued at any aggregation node is parsed into an aggregation subtree rooted at that node. For QoS-aware processing of the query, several algorithms are designed to dynamically apply proper aggregation/deaggregation operations on selected nodes for raising or lowering the granularity levels or changing the aggregation methods. The goal is to continuously maintain the desired level of QoS under constant variation of the streaming data volume. Prototype development and extensive simulation show that our framework and techniques can handle highly varied RFID streaming inputs and continuously satisfy the QoS constraints.
机译：企业RFID数据管理非常具有挑战性，这不仅是因为来自分布式来源的大量数据，而且还因为读取器输入的动态性质。根据用户指定的服务质量（QoS）要求，数据管理系统必须能够动态检测RFID输入的状态变化并调整处理策略以连续保持所需的QoS水平。我们提出了一个QoS感知框架，用于对企业数据服务问题进行建模，以及对分布式RFID数据流进行在线自适应处理。根据组织的结构，将数据处理结构建模为聚合节点的层次结构。叶节点对应于RFID流输入。设计了一组聚合/解聚合操作，以基于QoS动态调整处理粒度级别。在任何聚合节点发出的QoS约束查询都被解析为以该节点为根的聚合子树。对于查询的QoS感知处理，设计了几种算法来动态地在选定的节点上动态应用适当的聚合/聚合操作，以提高或降低粒度级别或更改聚合方法。目标是在流数据量不断变化的情况下，持续保持所需的QoS级别。原型开发和广泛的仿真表明，我们的框架和技术可以处理各种RFID流输入，并不断满足QoS约束。

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