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首页> 外文期刊>Sensors Journal, IEEE >A Two-Tier Adaptive Data Aggregation Approach for M2M Group-Communication
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A Two-Tier Adaptive Data Aggregation Approach for M2M Group-Communication

机译：一种用于M2M组通信的两层自适应数据聚合方法

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摘要

Network lifetime is the time interval in which the nodes are operational. Considering that machine-to-machine (M2M) devices have limited energy resources, an important challenge in M2M communications is to prolong the network lifetime. The constrained application protocol (CoAP) supports multi-target monitoring applications in M2M communications, allowing the creation and maintenance of groups, as well as their periodic communication. It is essential to aggregate the CoAP group-communication over the paths to increase the network lifetime of low-power M2M devices, since data aggregation reduces the use of energy-consuming hardware (e.g., central processing unit and wireless interface). However, the current data aggregation solutions do not specify how to support data aggregation with multiple CoAP-based groups in multi-target monitoring applications. In this paper, the proposed approach, called two-tier aggregation for multi-target applications (TTAMAs), aggregates the data originated from nodes belonging to either the same or different CoAP groups. Furthermore, TTAMA is an adaptive solution because it performs the data aggregation in accordance with the CoAP configurations, such as communication periodicity and data aggregation functions. We compare TTAMA with current data aggregation approaches that use minimum spanning tree and shortest path tree. The results show that TTAMA outperforms the related works in terms of network lifetime and energy consumption.
机译：网络生存期是节点可操作的时间间隔。考虑到机器对机器（M2M）设备的能源有限，M2M通信中的一个重要挑战是延长网络寿命。受约束的应用程序协议（CoAP）支持M2M通信中的多目标监视应用程序，从而允许组的创建和维护以及它们的定期通信。由于数据聚合会减少对能耗较高的硬件（例如，中央处理器和无线接口）的使用，因此必须在路径上聚合CoAP组通信以延长低功耗M2M设备的网络寿命。但是，当前的数据聚合解决方案未指定如何在多目标监视应用程序中支持多个基于CoAP的组的数据聚合。在本文中，所提出的方法称为多目标应用程序（TTAMA）的两层聚合，它聚合源自属于相同或不同CoAP组的节点的数据。此外，TTAMA是一种自适应解决方案，因为它根据CoAP配置（例如，通信周期性和数据聚合功能）执行数据聚合。我们将TTAMA与使用最小生成树和最短路径树的当前数据聚合方法进行比较。结果表明，在网络寿命和能耗方面，TTAMA优于相关工作。

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