Privacy-preserving WSN topology control method for QoS guarantee

Abstract

The present invention discloses a privacy protection WSN topology control method MQBP for QoS guarantee. The method provides a more fine-grained data aggregation result at the partition level through node area division, improves the balanced performance of data slicing and fusion process in energy efficiency, privacy and accuracy; further improves the degree of privacy protection by optimizing the node role division mechanism and combining blue-green aggregation routing; ensures network service quality and data aggregation integrity by constructing two non-intersecting blue-green aggregation routes and combining base station pre-selected routes and route quality detection mechanism; optimizes network energy efficiency and extends network life cycle through the route selection scheme uniformly planned by the base station. Finally, the wireless sensor network has better comprehensive performance in terms of privacy, data integrity and energy efficiency, and has higher service quality.

Description

Technical Field

[0001] The invention belongs to the field of computer software development, and in particular relates to a privacy protection topology control method oriented to QoS guarantee in a wireless sensor network environment. Background Art

[0002] Wireless Sensor Networks (WSN), as an important communication technology in the Internet of Things, are widely used in many scenarios such as intrusion detection, weather monitoring, security and tactical reconnaissance. According to the current development trend, the scale of WSN is getting larger and larger, and the integration of sensor devices is getting higher and higher. This puts high demands on the design of routing protocols, which require routing protocols to efficiently coordinate the data forwarding and data fusion of sensor nodes, ensure the quality of data transmission, reduce network energy consumption, and improve the life cycle of stable network operation.

[0003] However, in the actual deployment and operation of WSN, the network communication may be unstable and the information transmission between nodes may be blocked due to harsh and unstable external environment or various attacks. Therefore, ensuring the service quality of wireless sensor networks and improving service stability are of great significance to the performance of routing protocols. In current research, the research work on improving network service quality can be mainly divided into three directions, including swarm intelligence, multi-path optimization and cross-layer joint optimization, but the existing methods have more or less deficiencies in energy efficiency and QoS comprehensive performance.

[0004] In summary, QoS is an important performance indicator in WSN. How to integrate energy efficiency, privacy and service quality while ensuring the service quality and reliability of the network has become an urgent problem to be solved in this field. Summary of the invention

[0005] In order to solve the technical problems mentioned in the above background technology, the present invention proposes a privacy protection WSN topology control method oriented to QoS guarantee.

[0006] In order to achieve the above technical objectives, the technical solution of the present invention is: to achieve regional fine-grained data aggregation by partitioning the network, and improve the adaptability of data slicing and aggregation methods; to improve privacy protection performance through node role division mechanism and multi-path scheme; to provide data aggregation integrity verification by constructing non-intersecting blue-green slice routing, and to improve network link reliability by path quality detection. Ultimately, the network has better comprehensive performance in terms of privacy, data integrity and energy efficiency, and has higher service quality.

[0007] The privacy-preserving WSN topology control method for QoS guarantee includes the following steps:

[0008] (1) The base station uses the improved DPC-MND method based on communication energy density to perform clustering, elect cluster heads, and use the reverse planning mechanism to construct inter-cluster routing for each cluster head node;

[0009] (2) The base station divides the node roles for each cluster, selects 50% of the aggregation nodes and 50% of the slice nodes, and randomly divides the aggregation nodes into blue and green nodes in a 1:1 ratio;

[0010] (3) The base station pre-selects slice multi-routes for slice nodes and broadcasts the network's clustering, cluster heads, inter-cluster routes, and slice routes to the network;

[0011] (4) The slice node sends a detection packet to detect the path quality according to the candidate slice multi-routes planned by the base station, and constructs a QoS metric to select the best route;

[0012] (5) The slicing node distributes the data to two slicing results along the constructed blue-green route. The blue-green aggregation node aggregates the data to the cluster head. The cluster head node aggregates the data to the base station along the inter-cluster route.

[0013] (6) After data aggregation, the base station obtains the partition aggregation results and provides them to the application layer to complete the corresponding tasks. It also executes the corresponding malicious node detection mechanism to eliminate malicious nodes and prepare for the next round of network operation.

[0014] Furthermore, in step (2), the specific process of dividing the nodes is as follows:

[0015] (201) The base station uniformly divides the nodes in the cluster into slicing nodes and aggregation nodes. The slicing nodes are used to undertake all data slicing and distribution tasks, and the aggregation nodes are used to undertake all data reorganization, fusion and aggregation tasks. The metric standard for selecting the aggregation node is as follows:

[0016]

[0017] Where λ+β=1, and the parameters λ and β can be adjusted freely. res represents the remaining energy of the node, D toHead represents the distance from the node to the cluster head, and They represent the average value of the residual energy of all nodes and the distance to the cluster head respectively, and the remaining nodes become slice nodes.

[0018] (202) The blue-green division of the cluster nodes is also planned by the base station. 50% of the cluster nodes are selected as blue nodes and 50% of the cluster nodes are selected as green nodes in a completely random manner. The slice node constructs two non-intersecting paths to the cluster head through the blue and green cluster nodes respectively. The cluster head verifies the integrity of data aggregation by comparing the results of the blue and green routes.

[0019] Furthermore, in step (4), the specific process of selecting the best route is as follows:

[0020] (401) First, pre-select a better route. The base station pre-selection method is adopted to pre-select several better routes for the slice node according to the metric standard, and the better route information is sent to the node for further judgment and selection. The metric standard for the slice node to select the aggregation node as the route is defined as follows:

[0021]

[0022] Among them, D toNode Represents the distance between the aggregation node and the current slice node.

[0023] (402) Each slice node sends a detection data packet to the cluster head along multiple pre-selected aggregation routes. After receiving the data packet, the cluster head forwards it back to the slice node along the original route.

[0024] (403) The slice node calculates the corresponding indicators to measure QoS and select the optimal route. The measurement indicators include the overall energy consumption of the link E cost , packet transmission rate Tra and transmission delay Delay, the formula is as follows:

[0025] E cost (Path)=Cost i→head +Cost head→i

[0026]

[0027] (404) Calculate the QoS metric and based on the metric value Q:

[0028] Q(Path)=ω1E cost (Path)+ω2Tra(Path)+ω3Delay(Path)

[0029] Among them, ω1, ω2 and ω3 are weighting coefficients, satisfying ω1+ω2+ω3=1, and the weighting coefficient values ​​can be adjusted automatically.

[0030] (405) The slice node selects two nodes with the highest metric value Q from the blue and green candidate aggregation nodes respectively, and accumulates four routes as relay nodes for slice distribution and data aggregation.

[0031] The beneficial effects brought by adopting the above technical solution are:

[0032] (1) The privacy-preserving WSN topology control method MQBP designed by the present invention for QoS guarantee divides the nodes into 50% cluster nodes and 50% slice nodes by improving the node role division mechanism, and randomly divides the cluster nodes into blue and green nodes at a ratio of 1:1, thereby achieving finer-grained node differentiation and improving the degree of privacy protection.

[0033] (2) The privacy-preserving WSN topology control method MQBP designed by the present invention for QoS protection constructs blue-green disjoint aggregation routing and combines base station pre-selection and routing quality detection to ensure the quality of the link and the integrity of data aggregation, so that the network has a higher service quality, and ultimately makes the network have better comprehensive performance in terms of privacy, data integrity and energy efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] Figure 1 is a flow chart of the method of the present invention;

[0035] Figure 2 This is a schematic diagram of multi-path slicing routing in the present invention. DETAILED DESCRIPTION

[0036] The technical solution of the present invention will be described in detail below with reference to the accompanying drawings.

[0037] The basic idea of ​​the present invention is to achieve regional fine-grained data aggregation by partitioning the network, improve the adaptability of data slicing and aggregation methods; improve privacy protection performance through node role division mechanism and multi-path scheme; provide data aggregation integrity verification by building disjoint blue-green slice routing, and improve network link reliability by path quality detection. Ultimately, the network has better comprehensive performance in terms of privacy, data integrity and energy efficiency, and has higher service quality.

[0038] 1. If Figure 1 As shown, the privacy protection WSN topology control method for QoS guarantee proposed by the present invention has the following steps:

[0039] (1) The base station uses the improved DPC-MND method based on communication energy density to perform clustering, elect cluster heads, and use the reverse planning mechanism to construct inter-cluster routing for each cluster head node.

[0040] (2) The base station divides the node roles for each cluster, selects 50% of the aggregation nodes and 50% of the slice nodes, and randomly divides the aggregation nodes into blue and green nodes in a 1:1 ratio.

[0041] (3) The base station pre-selects slice multi-routes for the slice nodes and broadcasts the network's clustering, cluster heads, inter-cluster routes, and slice routes to the network.

[0042] (4) The slice node sends a detection packet to detect the path quality according to the candidate slice multi-routes planned by the base station, and constructs a QoS metric to select the best route.

[0043] (5) The slicing node distributes the data to two slicing results along the constructed blue-green route. The blue-green aggregation node aggregates the data to the cluster head, and the cluster head node aggregates the data to the base station along the inter-cluster route.

[0044] (6) After data aggregation, the base station obtains the partition aggregation results and provides them to the application layer to complete the corresponding tasks. It also executes the corresponding malicious node detection mechanism to eliminate malicious nodes and prepare for the next round of network operation.

[0045] In this embodiment, the above step (2) can be implemented by adopting the following preferred solution:

[0046] (201) The base station uniformly divides the nodes in the cluster into slicing nodes and aggregation nodes. The slicing nodes are used to undertake all data slicing and distribution tasks, and the aggregation nodes are used to undertake all data reorganization, fusion and aggregation tasks. In this embodiment, λ=0.5, β=0.5, the ratio of aggregation nodes is selected as α=0.5, and the remaining nodes become slicing nodes.

[0047] (202) The blue-green division of the cluster nodes is also planned by the base station. 50% of the cluster nodes are selected as blue nodes and 50% of the cluster nodes are selected as green nodes in a completely random manner. The slice node constructs two non-intersecting paths to the cluster head through the blue and green cluster nodes respectively. The cluster head verifies the integrity of data aggregation by comparing the results of the blue and green routes.

[0048] In this embodiment, the above step (4) can be implemented by adopting the following preferred solution:

[0049] (401) First, a better route is pre-selected. A base station pre-selection method is adopted to pre-select several better routes for the slice node according to the metric standard, and the better route information is sent to the node for further judgment and selection.

[0050] (402) Each slice node sends a detection data packet to the cluster head along multiple pre-selected aggregation routes. After receiving the data packet, the cluster head forwards it back to the slice node along the original route.

[0051] (403) The slice node calculates the corresponding index to measure QoS to select the optimal route.

[0052] (404) Calculate the QoS metric and use the metric value Q. In this embodiment, ω1=0.5, ω2=0.25, and ω3=0.25 are selected.

[0053] (405) The slice node selects two nodes with the highest metric value Q from the blue and green candidate aggregation nodes respectively, and accumulates four routes as relay nodes for slice distribution and data aggregation.

[0054] The embodiments are only for illustrating the technical idea of ​​the present invention and cannot be used to limit the protection scope of the present invention. Any changes made on the basis of the technical solution in accordance with the technical idea proposed by the present invention shall fall within the protection scope of the present invention.

Claims

1. A privacy-preserving WSN topology control method for QoS guarantee, characterized by: (1) The base station uses the improved DPC-MND method based on communication energy density to perform clustering, elect cluster heads, and use the reverse planning mechanism to construct inter-cluster routing for each cluster head node; (2) The base station divides the node roles for each cluster, selects 50% of the aggregation nodes and 50% of the slice nodes, and randomly divides the aggregation nodes into blue and green nodes in a 1:1 ratio. The specific process is as follows: (201) The base station uniformly divides the nodes in the cluster into slicing nodes and aggregation nodes. The slicing nodes are used to undertake all data slicing and distribution tasks, and the aggregation nodes are used to undertake all data reorganization, fusion and aggregation tasks. The metric standard for selecting the aggregation node is as follows: Where λ+β=1, parameters λ and β can be adjusted freely, E res represents the remaining energy of the node, D toHead represents the distance from the node to the cluster head, and They represent the average values ​​of the remaining energy of all nodes and the distance to the cluster head, respectively, and the remaining nodes become slice nodes; (202) The blue-green division of cluster nodes is also planned by the base station. 50% of the cluster nodes are selected as blue nodes and 50% of the cluster nodes are selected as green nodes in a completely random manner. The slice nodes construct two non-intersecting paths to the cluster head through the blue and green cluster nodes respectively. The cluster head verifies the integrity of data aggregation by comparing the results of the blue and green routes. (3) The base station pre-selects slice multi-routes for slice nodes and broadcasts the network's clustering, cluster heads, inter-cluster routes, and slice routes to the network; (4) The slice node sends a detection packet to detect the path quality according to the candidate slice multi-routes planned by the base station, and constructs a QoS metric to select the best route. The specific steps are as follows: (401) First, a better route is pre-selected. A base station pre-selection method is adopted to pre-select several better routes for the slice node according to the metric standard. The better route information is sent to the node, and the node is further judged and selected. The metric standard for the slice node to select the aggregation node as the route is defined as follows: Among them, D toNode Represents the distance between the aggregation node and the current slice node; (402) Each slice node sends a detection data packet to the cluster head along multiple pre-selected aggregation routes, and the cluster head forwards the data packet back to the slice node along the original route after receiving the data packet; (403) The slice node calculates the corresponding indicators to measure QoS to select the optimal route. The measurement indicators include the overall energy consumption of the link E cost , packet transmission rate Tra and transmission delay Delay, the formula is as follows: E cost (Path)=Cost i→head +Cost head→i (404) Calculate the QoS metric and based on the metric value Q: Q(Path)=ω1E cost (Path)+ω2Tra(Path)+ω3Delay(Path) Among them, ω1, ω2 and ω3 are weighted coefficients, satisfying ω1+ω2+ω3=1, and the weighted coefficient values ​​can be adjusted by themselves; (405) The slice node selects two nodes with the highest metric value Q from the blue and green candidate aggregation nodes respectively, and accumulates four routes as relay nodes for slice distribution and data aggregation; (5) The slicing node distributes the data to two slicing results along the constructed blue-green route. The blue-green aggregation node aggregates the data to the cluster head. The cluster head node aggregates the data to the base station along the inter-cluster route. (6) After data aggregation, the base station obtains the partition aggregation results and provides them to the application layer to complete the corresponding tasks. It also executes the corresponding malicious node detection mechanism to eliminate malicious nodes and prepare for the next round of network operation.

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