Performance Improvements of Batch Data Model for Machine-to-Machine Communications
Performance Improvements of Batch Data Model for Machine-to-Machine Communications
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DOI：
10.1109/lcomm.2014.2345656
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发表时间：
2014-08
期刊：
影响因子：
--
通讯作者：
Sok-Ian Sou;Shi Wang
中科院分区：
文献类型：
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作者：
Sok-Ian Sou;Shi Wang
近年来，机器对机器(M2M)应用的普及迅速增长，使得大量M2M设备得以部署。此外，3GPP建议在M2M设备之间使用更高层的连接来链接到先进的LTE核心网络。为了支持大量的设备连接，降低核心网络中不必要的数据传输带来的成本至关重要。研究了在M2M核心网中如何应用批量数据模型来降低数据更新频率。为了达到可接受的更新设备比率，同时避免从设备/网关到服务器的高数据更新率，对于M2M应用发布的每次数据访问，我们根据不同类型的应用需求从网关动态拉取尚未更新的数据。针对提出的带数据拉取的批量数据模型，建立了分析模型，以评估M2M网络中的传输成本和设备更新率。
In recent years, rapid growth in the popularity of machine-to-machine (M2M) applications has enabled the deployment of a large number of M2M devices. In addition, 3GPP proposes the use of higher layer connections among M2M devices to link to LTE-advanced core networks. To support the massive numbers of device connections, it is essential that the cost imposed by the unnecessary transmission of data in core networks be reduced. This paper investigates how to apply the batch data model to reduce the data update frequency in M2M core networks. To achieve an acceptable ratio of updated devices while avoiding a high data update rate from the devices/gateway to the server, for each data access issuing by an M2M application, we dynamically pull not-yet-updated data from the gateway in respect to different kinds of application requirements. An analytical model is developed for the proposed batch data model with data pulling to evaluate the transmission cost and updated device ratio in M2M networks.