# Data Exchange in Cluster Structure for Longevity of IoT
## 3 Proposed Property-Based Data Transfer
### System Architecture  
In this paper, the cluster configuration method and data transfer method are proposed for efficient information-sharing in IoT networks. The proposed method is based on the cluster property of data transfer. It is abbreviated as CPDT (cluster property of data transfer). In the CPDT method, each thing has a property that represents its characteristic. A group of things becomes a cluster. The header node of a cluster has the property information of the member nodes. When a request for specific data arises, the header node queries only the things with the property corresponding to the specific data. Since only the relevant things participate in the process of querying, the network traffic and energy consumption in IoT networks are significantly reduced.  
Figure 1 shows an example of a cluster configuration in the IoT environment with five clusters. The clusters are composed of several things with various functions, such as distance measurement, detection of human appearance, and monitoring of surrounding air state. Each cluster is based on the surrounding local things. As shown in this figure, several kinds of things are involved. The thick circular node represents the header of a cluster. The sensor node for monitoring the surrounding air state is titled as A.  
Owing to the characteristics of the cluster structure, the member nodes involved in a cluster can communicate with each other via only the elected header. The header configures the cluster and broadcasts the property information of the member nodes to other cluster headers. Moreover, it receives messages from the headers of other clusters. These messages include information on things in other clusters. Consequently, a header gathers the property information possessed in other clusters. Based on this knowledge, when data exchange is required for information-sharing, the header queries only the relevant cluster headers regarding the corresponding information. This information includes the property of things. Through a query to selective things, the network traffic decreases and hence, the energy consumption of the things also reduces.  
For example, in Figure 1, when a member thing with question(?)mark in the cluster 1 requests the air condition state, it sends a query message to the header node. Subsequently, the header node of cluster 1 transfers the query message to only the corresponding cluster headers that include member nodes capable of obtaining information about the air condition state. In the previous cluster configuring stage, each header node becomes aware of the properties of the member nodes that can obtain the property information about the air condition state. In Figure 1, clusters 1, 2, and 4 include the things possessing information about the air condition state. The corresponding things are marked as A.  
Owing to the selective query message, the cluster headers irrelevant to the air state information do not receive the query message. However, the cluster headers relevant to the air state information receive the query message. The headers send it to their member nodes that can obtain the air state information. In Figure 1, the headers of cluster 2 and cluster 4 are relevant. After receiving the messages from the header, the member nodes of clusters 2 and 4 obtain the information on the air condition state and send it to their header node. The header nodes of clusters 2 and 4, in turn, send the information of air condition state to the header node of cluster 1. This header node sends it to its member node that issued the query of air condition state initially.  
As the data exchange between the cluster headers is processed according to these selective query messages, the total network traffic can be reduced significantly.