A Routing Method for Sensor Networks Based on Hilbert Filling Curve

Abstract

The invention discloses a sensor network routing method based on the Hilbert filling curve, which includes a network initialization stage and an information sending stage. In the network initialization stage: each base station in the deployment domain divides the deployment domain into several sub-domains and sorts them; each base station respectively Broadcast with itself as the center, the sensor receives the broadcast information and marks it in the corresponding status bit; each sensor perceives whether there is a sensor in its coverage area that is marked as a "line sequence" sensor; the information sending stage: the source node G(h )-hop limited flooding; (k,p)-routing; G(h)-hop base station masquerading. The invention adopts the Thiessen polygon division rule to deploy each base station in the wireless sensor network, and enhances the strength of privacy protection through data wraparound routing; the sensor generates and sends false messages irregularly to disturb the attacker, and improves the privacy resistance of the source node location. ability to attack.

Description

technical field [0001] The invention relates to the technical field of communication, in particular to a sensor network routing method based on Hilbert filling curves. Background technique [0002] With the increasing frequency of maritime activities, marine wireless sensor networks (Marine Wireless Sensor Networks, MWSNs) are widely used in national defense and military, environmental monitoring, marine disaster warning, offshore oil and gas due to their fast deployment, flexible methods, and low cost. exploration and other fields. Most maritime wireless sensor networks use wireless multi-hop communication methods. Due to the limitations of sensor energy, storage and communication capabilities, MWSNs are vulnerable to various location attacks. Furthermore, MWSNs often involve the collection and transmission of large amounts of sensitive data, which concerns national information security. Once the node location (including the source node and base station) is leaked or capt...

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Problems solved by technology

[0006] Furthermore, the traditional single and fixed source node location privacy protection mode is difficult to resist knowledge association attacks under large samples, such as path camouflage schemes based on random walks or multi-paths, trap induction strategies, etc. In marine environments, attackers can It is easy to use monitoring equipment with excellent resources to monitor large-scale data sample data sets in sensor networks. Through big data mining and analysis technologies such as correlation analysis and neural networks, relatively accurate location privacy protection patterns can be identified with a high probability, and then Security that threatens the location privacy of nodes

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