While constructing the hierarchical multicast tree, the system often chooses the geographical central node as the cluster core or near the core. Hence it can save the transmission distance [8]. However, in sensor grid, the data quantities of different nodes are much different [10]. Usually 80% of the data often is centralized in 20% nodes; naturally these important nodes should be paid more attention to. Generally speaking, the more data the nodes have, the more data transmission will happen from the nodes [11]. If the data scale is the only factor we consider, to choose the node with larger data quantity as root or near the root would undoubtedly improve the efficiency of the data transmission.

As a result, the system should consider not only the space factor, but also the data quantity as the factor [9].

The two factors are independent with each other and related with each other. In other words, their relationship is game and balance. We try to set a group of functions in order to draw an elaborate balance between them in our to-be-presented algorithm. The basic idea goes through the whole process of constructing the hierarchical multicast tree. The space factor and data factor are two factors independent with each other, which have meaning and formation respectively; both of them tend to maximize their result. Namely the two factors game with each other. On the other hand, the two factors also co-exist in a system, common working, mutual interaction and constraint.

Namely they balance with each other. We must synthetically consider the space and data factors while constructing the multicast tree.

The specific implementation of the algorithmsAfter summarizing the context of the algorithms, this subsection discusses the concrete implementation of the Dacomitinib algorithms [12]. The motivation of this paper is to design a multicast scheme in m-D Sensor grid that can achieve not only shorter multicast delay and less resource consumption, but also the efficient data transmission.The network Site URL List 1|]# is partitioned into clusters in terms of some regular Sensor grid area. After group members are initially scattered into different clusters, a tree is built to connect the cluster members within each other. The connection among different clusters is done through hooking the tree roots [13].