Research On Key Technologies Of The Internet Of Heat Meter

To improve the management level of heat metering, the Internet of heat meter is built.The underlying data is transferred by ZigBee and GPRS respectively. The ONS is built tostore the mapping information between EPC and EPCIS, and fast query response serviceis provided. The EPCIS system is built to store the information of EPC. Data capture andquery service is provided to monitor the supply chain. On the application layer, the dataset is clustered to get useful knowledge.The innovation can be divided into the following four aspects.Firstly, an energy-efficient routing algorithm of ZigBee network is proposed toprolong the network’s survival time. In the algorithm, the node’s boundary is defined.Firstly, all the information for node’s boundary is stored when zigbee network is built.Then, the packet between the nodes which are in the node’s boundary is transferreddirectly. The packet between the nodes whose boundaries are adjacent is transferredthrough the node with maximum energy. The exprimental results show that the newalgorithm can efficiently extend the lifetime of zigbee network.Secondly, the multi-servers ons system is proposed to improve the load capacity.Firstly, the CPU utilization rate and memory utilization of a single server is computed. Ifboth of them are less than a given threshold, the status of the server is set to available.Then the given threshold is changed according to the redundancy. The status of theunavailable server is updated periodically. Finally, the query is transferred to the availableserver by task scheduling policy. The exprimental results show that the new ons systemcan efficiently provide consulting services.Thirdly, the architecture of EPCIS with proxy server is proposed to reduce theresponse time. And a new cache replacement algorithm is proposed. Proxy servers arebuilt to store the information which is queried recently. Then attention rate is defined.When the replacement is needed in the proxy server, data object with low attention rate isselected to shift out the cache. The exprimental results show that the new EPCIS systemcan efficiently shorten the query time. Fourthly, a high dimensional data clustering algorithm based on hypergraph isproposed to obtain knowledge. Firstly, the records in the dataset are mapped to the verticesof hypergraph, the hyperedges of hypergraph are composed of the vertices which have thesame value on one of the attributes. Then a multilevel hypergraph partitioning algorithm isused to find k parts of the hypergraph. Finally, the clusters with good quality are choosedout by computing the value of cluster’s validity. The experimental results show that thenew algorithm can efficiently construct high quality clusters.