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A multi-representative re-fusion (MRRF) approximate data collection approach is proposed in which multiple nodes with similar readings form a data coverage set (DCS). The reading value of the DCS is represented by an R-node. The set near the Sink is smaller, while the set far from the Sink is larger, which can reduce the energy consumption in hotspot areas. Then, a distributed data-aggregation strategy is proposed that can re-fuse the value of R-nodes that are far from each other but have similar readings. Both comprehensive theoretical and experimental results indicate that the MRRF approach increases lifetime and energy efficiency.

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In smart wireless software defined networks (WSDNs), sensor nodes are deployed in the monitored area to sense data. In order to increase the flexibility of WSDNs configuration, sensor nodes use programmable technology. Thus, programming and software engineering that integrate Internet of Things (IoT) lead to a smart world. Due to the large capacity of program codes and the limited energy of wireless network, only a subset of nodes is selected to spread program codes, and the remaining nodes are in sleep status to save energy. In this paper, a fast program codes dissemination (FPCD) scheme for smart wireless software defined networking is proposed; many nodes in the area far from the sink will be selected to spread program codes; those areas have much energy left, while the area near the sink chooses less number of active nodes to spread program codes to save energy. Thus, FPCD scheme can reduce delay for spreading program codes while retaining network lifetime. The theoretical analysis and experimental results show that our approach can reduce transmission delay by 10.76%–105.791% while retaining network lifetime compares with previous broadcast schemes.