Probability route improving method in delay-tolerance mobile sensor network based on node activeness

Abstract

The invention relates to a probability route improving method in a delay-tolerance mobile sensor network based on the node activeness. The method adds node activeness factors into prediction of the transmission probability to provide a calculating formula of the self node activeness NA, the NA and a transmission prediction probability value of an original PROPHET algorithm are weighed through a weight alpha, a new transmission prediction probability value is calculated according to node meeting history information and node activeness in the network, whether information is transmitted is decided by comparing transmission prediction probability values of nodes, and buffer memory is managed through a time to live TTL discarding strategy. Simulation results show that a probability estimating method of an NAPR algorithm is more comprehensive than a PROPHET algorithm, fewer copies are generated, the NAPR algorithm reduces the node overhead rate even though the average delay of the information is slightly increased, and the delivery rate of message is improved. In future work, the probability route improving method can be further used for solving the jam problem in the network.

Description

technical field [0001] The invention is an improved probabilistic routing method based on node activity in a delay tolerant mobile sensor network (Delay Tolerant Mobile Sensor Networks, DTMSN), belonging to the field of probabilistic routing algorithms for delay tolerant sensor networks. Background technique [0002] DTMSN belongs to the category of Delay Tolerant Networks (DTN), which is used to transmit data in intermittently connected networks. DTN technology has been introduced into wireless sensor networks in recent years, and according to the difference of node mobility, delay tolerant sensor networks (Delay Tolerant Sensor Networks, DTSN) can be divided into networks with stationary sensor nodes and sensor networks with moving nodes. The sensor network of node motion is Delay Tolerant Mobile Sensor Networks (DTMSN). DTMSN has the characteristics of high latency, low data rate, no stable end-to-end connection, and limited node resources. It is used for extensive data ...

AI Technical Summary

Problems solved by technology

However, the PROPHET algorithm only determines the forwarding of the message by the transmission probability of the destination node, which has a certain degree of blindness, and the estimation of the probability is not reasonable, and does not consider the activity of each node itself and the timing of forwarding.

There are also some improvement measures for the PROPHET algorithm, but these improved algorithms do not take into account the influence of the activity of the node itself on the transmission prediction value, and the estimated value of the probability obtained is not reasonable.

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