Adaptive Data Transmission Method for Situation Awareness in Opportunistic Crowd Intelligence Sensing Network

Abstract

The invention relates to a situation awareness-based adaptive data transmission method applied to an opportunistic crowd sensing network and belongs to the wireless sensor network and mobile ad hoc network technical field. According to the method, nodes in the network estimate the node residual energy of the nodes themselves, the encounter probability of the nodes and a destination node and the hops of message transmission according to the conditions of the nodes themselves and the historical information of the network, judge a network environment where the nodes are located currently by using local topological information of positions where the nodes are located, and selects suitable data transmission mechanisms. With the method adopted, communicated MANET subnets in the network can be accurately identified, and are fully utilized in a data transmission process, and the communicated MANET subnets have little possibility of being affected by the mobility of the nodes and the time variance of network topology, and the success rate of data transmission can be improved, network overhead can be reduced, and the robustness of a data transmission strategy can be improved.

Description

Technical field [0001] The invention belongs to the technical field of wireless sensor networks and mobile self-organizing networks, and relates to an adaptive data transmission method for situational awareness in an opportunity group intelligence perception network. Background technique [0002] With the rapid development of information technology such as the Internet of Things and big data and the continuous deepening of application research, the trend of multi-network and multi-technology integration of communication network systems is increasing year by year. The development of information technology is about to produce major changes and new breakthroughs-using mobile terminals Various sensors provide human-centered perception and calculation. In this context, the application of group intelligence perception technology was born. Group intelligence perception is a new perception mode of the Internet of Things—“prosumer”, which is different from the traditional “consumer” mode...

AI Technical Summary

Problems solved by technology

That is, the network topology is based on the assumption that there is an end-to-end transmission path between any two nodes or that there is no communication link between any two nodes in the network. However, this assumption is rarely used in real large-scale crowd sensing network models. Existence, because due to the difference of node movement and sparse distribution of nodes, it will cause real-time dynamic changes in the network topology, so that the entire network topology will be segmented, that is, the network topology is composed of multiple connected subnets, and the terminal can be used in the connected subnet. End-to-end communication mode, but cannot communicate between different subnets

That is to say, in a large-scale crowd-sensing network environment, the end-to-end data transmission method alone will cause "routing holes", resulting in a low rate of successful data delivery; while the "store-carry-forward "Increasing the robustness of the network will increase the transmission delay and network overhead

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