Shulou(Shulou.com)06/02 Report--

When a large number of devices connect to the server and a large amount of data is uploaded to the server, how to improve the processing capacity of the server to deal with the data, the data source is the device data. Server processing data 56 cloud editor recommendations can be considered from the following aspects.

1. Queue processing mechanism.

. Data pours into the server, but it is still able to distinguish the order, queue the data summary according to the data transmission sequence, and then the server processes it according to the queue.

two。 Data classification mechanism.

Data classification and priority processing are used together to classify data according to different types. for example, equipment status can be divided into one type of data, monitoring data can be divided into one type of data, and operator normal operation of equipment data can be divided into one category. Operators illegally operate equipment into one category, and different types are put into different priority queues according to their importance, and processed in turn according to the priority queue.

3. Data shunting mechanism.

The data is divided into layers, shunt management, and multi-level servers, for example, equipment-school server-municipal server-provincial server-central server, so that the data of each layer is not accessed at the same time.

The server can be considered from the above aspects, the host computer equipment can also be optimized, do a good data definition, can share the pressure of the server, can be considered from the following aspects.

1. Leisure time mechanism.

The data of the upper computer does not use real-time data transmission when it is not necessary, so it can store the data locally and wait for upload when it is idle.

two。 Subcontracting mechanism. For example, the data source is split in two cases, one is the small data with the amount of data less than 1m, and the other is big data with the amount of data greater than 1m. Big data is sliced and subpackaged and transmitted. This operation requires the server to carry out corresponding processing. In fact, the server lowers big data's processing priority.

3. Abstract mechanism.

For big data's transmission, we can formulate appropriate summary data, before big data transmission, first transmit its summary, through the server to determine the summary, decide whether the data is transmitted or not, so as to improve its communication efficiency.

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