Wireless sensor network (WSN) in the Internet of Things consists of a large number of nodes. The proposal of compressive sensing technology provides a novel way for data aggregation in WSN. Based on the clustering structure of WSN, a kind of effective data aggregating method based on compressive sensing is proposed in this paper. The aggregating process is divided into two parts: in the cluster, the sink node sets the corresponding seed vector based on the distribution of network and then sends it to each cluster head. Cluster head can generate corresponding own random spacing sparse matrix based on its received seed vector and collect data through compressive sensing technology. Among clusters, clusters forward measurement values to the sink node along multi-hop routing tree. Performance analysis and comparison with the relative methods show that our method is effective and superior to other methods regardless of intra-cluster or inter-cluster on the total energy consumption of network.
In this paper, we present a trust-based message propagation and evaluation framework in vehicular ad-hoc networks where peers share information regarding road condition or safety and others provide opinions about whether the information can be trusted. More specifically, our trustbased message propagation model collects and propagates peers' opinions in an efficient, secure and scalable way by dynamically controlling information dissemination. The trust-based message evaluation model allows peers to evaluate the information in a distributed and collaborative fashion by taking into account others' opinions. Experimental results demonstrate that our proposed framework promotes network scalability and system effectiveness in information evaluation under the pervasive presence of false information, which are the two essentially important factors for the popularization of vehicular networks.
During mobile edge computing, due to the movement of nodes and the exhaustion of node energy, link failure occurs thus reducing the network lifetime in the mobile ad-hoc network. When the route fails, because the single-path protocols need to restart the route discovery process, the delay of the network is greatly increased. Therefore, the multi-path routing protocol is proposed, saving the cost of route discovery. In this paper, we propose an ad hoc on-demand multi-path distance vector (AOMDV) routing protocol based on link lifetime and energy consumption prediction (named LLECP-AOMDV) for mobile edge computing. In the route discovery phase, the energy grading strategy is adopted. When the node energy is lower than the threshold, it no longer participates in the route discovery. In the routing selected phase, the path is selected based on the lifetime of the route link and the minimum energy consumption of the route. According to energy consumption, packet delivery rate, end-to-end delay performance indicators, we evaluate the comparison results. The result shows that under most network performance indicators and parameters, the proposed LLECP-AOMDV is superior to the other three protocols, which improves the network lifetime, reduces the node's energy consumption and the average end-to-end delay. The protocol is very useful for mobile edge computing. INDEX TERMS Mobile edge computing, MANET, AOMDV, energy threshold, link lifetime, energy consumption.
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