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First phase results are those arising from the cluster construction and the second phase results correspond to those of the actual unique localization.
HHY participated in hierarchical cluster construction and preferential expression analysis.
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In this section, we present our multi-mobile agent itinerary planning-based energy and fault aware data aggregation in wireless sensor networks MAEF that consists of three phases: (1) CH selection and cluster construction, (2) CH-based itinerary planning, (3) MA migration and data collection.
Fig. 2 Phase 1. Cluster head selection and cluster construction phase.
Lin et al. proposed a clustering hierarchy based on cellular topology (CHCT), in which the remaining energy and position of sensor nodes are simultaneously considered during the cluster structure construction, and the desired cluster structure is generated even in the case of nodes without locating device [19].
This advantage of the average CH change for the proposed scheme is because of the lower link formations and failures in the cluster construction.
There is then a cluster construction stage, which is the heart of the mechanism and consists of structuring the network into a set of areas, i.e. clusters, in which there are master nodes (CHs) that guarantee coordination of all member nodes (MNs) and processing.
However, the cluster construction is performed in parallel to the PKI functionalities and the cluster formation rounds should be less.
The reasons for this are many, but a primary one is the tradeoff between completeness of a data set and lack of homology that eventually limits cluster construction.
For the cluster construction process, we selected a subset of 8,709 cases, analysed between 1.1.1986 and 31.12.1997, for which a complete description of post-mortem findings was available.
Fig. 5 Hexagonal cluster construction.
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