Jian Wu

TL;DR: The proposed node social features relationship evaluation algorithm (NSFRE) establishes a fuzzy similarity matrix based on various features of nodes that can effectively improve the transmission success rate, reduce transmission delay, ensure the safe and reliable transmission of information in the network, and require low buffer space and computing capacity.

TL;DR: This paper proposes a predict the probability method of encounter and forwarding cooperation with node (PNECP), the method predicting mobility probabilities based on the social relationship and forwarding collaboration relationship between mobile users, which has a better performance on the delivery rate and average delay performance compared with other probabilistic transmission methods.

TL;DR: The theoretical analysis and experimental results demonstrate that the performance of DMADC is better than that proposed in previous studies and can reduce the end-to-end data transmission delay by 10.25%–26.37% while maintaining the network lifetime, and increase the energy utilization rate by more than 25%.

TL;DR: This work quantifies the social and cooperative relationships symmetrically between the mobile devices themselves and the nodes, and proposes a routing algorithm based on an improved probability model to predict the probability of encounters between nodes (PEBN).

TL;DR: In this paper, an efficient data transmission method for a low-duty-ratio wireless sensor network, which comprises the following steps: firstly, constructing a WSN transmission model by using a basketball network topology, and then analyzing the energy consumption and data transmission delay of sensor nodes in the network; selecting a path with minimum transmission delay for each node in the WSN; and adjusting the duty ratio of the nodes in WSN, enabling the nodes the distance between which and the Sink is different to consume energy uniformly.