CN110234143B - Reliable routing oriented to IWSN based on sealed first price auction game - Google Patents

Reliable routing oriented to IWSN based on sealed first price auction game Download PDF

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CN110234143B
CN110234143B CN201910496337.9A CN201910496337A CN110234143B CN 110234143 B CN110234143 B CN 110234143B CN 201910496337 A CN201910496337 A CN 201910496337A CN 110234143 B CN110234143 B CN 110234143B
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张文波
冯永新
刘越
谭小波
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Shenyang Ligong University
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L45/00—Routing or path finding of packets in data switching networks
    • H04L45/12—Shortest path evaluation
    • H04L45/126—Shortest path evaluation minimising geographical or physical path length
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L45/00—Routing or path finding of packets in data switching networks
    • H04L45/24—Multipath
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W40/00—Communication routing or communication path finding
    • H04W40/02—Communication route or path selection, e.g. power-based or shortest path routing
    • H04W40/023—Limited or focused flooding to selected areas of a network
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W40/00—Communication routing or communication path finding
    • H04W40/02—Communication route or path selection, e.g. power-based or shortest path routing
    • H04W40/04—Communication route or path selection, e.g. power-based or shortest path routing based on wireless node resources
    • H04W40/10—Communication route or path selection, e.g. power-based or shortest path routing based on wireless node resources based on available power or energy
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W40/00—Communication routing or communication path finding
    • H04W40/24—Connectivity information management, e.g. connectivity discovery or connectivity update
    • H04W40/246—Connectivity information discovery
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W40/00—Communication routing or communication path finding
    • H04W40/24—Connectivity information management, e.g. connectivity discovery or connectivity update
    • H04W40/248—Connectivity information update
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L45/00—Routing or path finding of packets in data switching networks
    • H04L45/12—Shortest path evaluation
    • H04L45/122—Shortest path evaluation by minimising distances, e.g. by selecting a route with minimum of number of hops
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
    • H04W4/30—Services specially adapted for particular environments, situations or purposes
    • H04W4/38—Services specially adapted for particular environments, situations or purposes for collecting sensor information
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
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    • Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
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Abstract

The reliable routing oriented to IWSN based on sealed first price auction game is a technology for ensuring reliable data transmission in large-scale IWSNs. By applying the routing algorithm, the success rate of data transmission can be effectively ensured, so that the industrial control system has higher reliability and safety. Firstly, documents related to a reliable routing algorithm are carefully researched and analyzed, and the actual requirements of a large-scale IWSNs routing algorithm are basically mastered theoretically; secondly, analyzing and comparing the existing related technologies in the aspect of reliable data transmission, and providing a sealed first price auction game model based on standard normal distribution; on the basis of the model, the characteristic of large-scale IWSNs data transmission is combined, bayesian Nash equilibrium of the fact that the bidding nodes participate in the sealed first price auction game based on the standard normal distribution is given, and theoretical basis and support are provided for reliable data transmission. Finally, in order to promote the cooperation among the sensor nodes, a dynamic profit control method is provided, and the design and the implementation of a reliable routing algorithm based on the sealed first price auction game are completed.

Description

Reliable routing oriented to IWSN (Internet Web service) game based on sealed first price auction
Technical Field
The invention belongs to a routing algorithm of a large-scale industrial wireless sensor network.
Background
With the increasing technical and market demands of the traditional industrial field, the wireless sensor network becomes one of the important development directions of the industrial field. The Industrial field environment is complex, especially large-scale Industrial Wireless Sensor Networks (IWSNs) with a large number of nodes and data volume, and the reliability of data transmission is directly related to the quality of Industrial tasks and even the safety of Industrial control systems. Therefore, it is of great significance to research a routing algorithm capable of ensuring reliable transmission of large-scale IWSNs data.
Disclosure of Invention
The invention aims to provide a reliable route oriented to IWSN (Internet web service) based on sealed first price auction game, and the success rate of data transmission can be effectively ensured by applying the routing algorithm, so that an industrial control system has higher reliability and safety.
The technical scheme is as follows:
the reliable routing facing IWSN based on sealed first price auction game is a technology for ensuring reliable data transmission in large-scale IWSNs, and the main contents comprise: a network model is provided, and a network model with a plurality of Sink nodes is adopted so as to reduce data transmission distance and transmission time delay; in order to ensure the fault tolerance of the route, a data transmission mechanism of double-path transmission is adopted; in order to select a transmission link with high reliability, an optimal next hop node is selected by using a sealed first price auction game method based on standard normal distribution; in order to promote the cooperation among the sensor nodes, a dynamic gain control method is provided; the implementation process of the reliable routing algorithm is specifically described. The method specifically comprises the following steps:
design of network model
A reliable routing algorithm based on sealed first price auction game adopts a network model of multiple Sink nodes. In this model, IBy taking the existing multi-Sink node optimized deployment method as a reference, based on the grid network structure, the number N of Sink nodes which ensures the maximum network service life and simultaneously ensures the minimum network cost is obtained, and finally, uniform deployment in a monitoring area is determined
Figure BDA0002088724090000021
And (4) each Sink node. According to the network model, relevant definitions of Sink node numbers, neighbor Sink nodes, destination Sink nodes and the like are provided.
Reliable routing algorithm based on sealed first price auction game
In the route discovery process, each sensor node establishes a neighbor list to the neighbor Sink node, and stores neighbor node information of the sensor node and hop count to the neighbor Sink node. In the data transmission process, the source node determines two Sink nodes which are closest to the source node from the neighbor list as destination Sink nodes, and transmits data to the two destination Sink nodes. In the process of determining the transmission path, a mode of routing according to needs is adopted, the next hop node is selected by utilizing a sealed first price auction game based on standard normal distribution, and a dynamic profit control method is provided to promote the cooperation among the sensor nodes.
Performing algorithm
Step1: and constructing a route. And after the node deployment is completed, starting to construct an initial route. After the route construction is finished, each sensor node stores the hop count from the neighbor node to each destination Sink node and information such as a destination node set in a neighbor list of the sensor node;
step2: and selecting a destination Sink node. The source node selects two Sink nodes closest to the source node from the destination Sink node set as final destination nodes;
step3: a determination is made whether to initiate the game. The sensor node needing to send data checks the credibility of the next hop node determined by the last game, and directly sends data and transfers to Step7 if the credibility meets the requirement; the steering Step4 is not met;
step4: the auction node initiates the game. A sensor node needing to send data initiates an auction game to a neighbor node;
step5: the bidding node gives the optimal bid. The sensor nodes participating in the auction game respectively calculate the optimal bids of the sensor nodes and send the bids to the auction nodes;
step6: the next hop node is determined. The auction nodes compare the bids of all the bidding nodes and check the credibility of the sensor node with the highest bid. If the reliability meets the requirement, determining the sensor node as a next hop node; otherwise, discarding the node, and continuously checking the credibility of the node with the highest bid in the rest auction nodes until the node meeting the requirements is found;
step7: and the sensor node receiving the data checks whether a destination Sink node exists in the one-hop range of the sensor node. And if the data exist, sending the data to the destination Sink node, and if the data do not exist, repeating Step3-Step7 until the data are sent to the destination Sink node.
By adopting a network model with multiple Sink nodes, the method can avoid network holes, reduce the transmission distance and time delay of data and prolong the service life of the network; based on standard normal distribution, the classical sealed first price auction game is improved, and through the analysis of a balanced result, the method can enable an auctioneer to obtain higher income; in the route discovery process, the route establishment message sent by each Sink node is only diffused to the neighbor Sink node and is not required to be sent to the whole network, so that the time delay and the network energy consumption are reduced; in the data transmission process, two Sink nodes are selected as destination nodes, and data are transmitted to the two destination nodes from two paths respectively, so that the fault tolerance of the route and the reliability of the data can be improved; a data forwarding auction game model is provided, various factors influencing the reliability of data transmission are fully considered, and the successful sending rate of data is ensured; the dynamic gain control method dynamically updates the descending coefficient of the reliability of the sensor nodes, and promotes the cooperation among the sensor nodes.
Drawings
Fig. 1 is a schematic diagram of a multi-Sink node network structure according to the present invention.
Fig. 2 is a schematic diagram of the network model structure of the present invention.
Fig. 3 is a schematic diagram of a data forwarding auction betting process of the present invention.
Detailed Description
The reliable routing oriented to the IWSN based on the sealed first price auction game adopts a network model with multiple Sink nodes to reduce the distance and time delay of data transmission in the network and prolong the service life of the network from the viewpoint of reliability of large-scale IWSNs data transmission process. The sealed first price auction game is researched and improved, and the reliability of data transmission is improved.
The algorithm has the advantages that: firstly, documents related to a reliable routing algorithm are carefully researched and read and analyzed, and the actual requirements of the large-scale IWSNs routing algorithm are basically mastered theoretically; secondly, analyzing and comparing the existing related technologies in the aspect of reliable data transmission, and providing a sealed first price auction game model based on standard normal distribution; on the basis of the model, the characteristic of large-scale IWSNs data transmission is combined, the bidding nodes participate in Bayesian Nash balance of the sealed first price auction game based on standard normal distribution, and theoretical basis and support are provided for reliable data transmission. Finally, in order to promote the cooperation among the sensor nodes, a dynamic profit control method is provided, and the design and the implementation of a reliable routing algorithm based on the sealed first price auction game are completed.
The reliable routing algorithm based on the sealed first price auction game is technically characterized by comprising the following parts:
1. network model assumption
The algorithm adopts a network structure of multiple Sink nodes, as shown in fig. 1. And the sensor node sends the sensed data to the Sink node, the Sink node processes the data, and finally the Sink node sends the data to the management center.
The network model used by the algorithm is shown in fig. 2. Supposing that a monitoring area is a square area, by taking the reference of the existing multi-Sink node optimal deployment method, providing a network life model and a cost model under the multi-Sink nodes based on a grid network structure, and obtaining the maximization of the service life of the guaranteed network by calculating the maximum network life cost Ratio (RLC)And the number N of Sink nodes which enables the network cost to be the lowest. Finally determining a uniform deployment in the monitored area
Figure BDA0002088724090000041
And (4) each Sink node.
According to the above model, a relevant definition is proposed:
definition 1 (Sink node number S) i ): numbering the Sink nodes in a row-priority ascending manner, wherein the Sink node matrix is as follows:
Figure BDA0002088724090000042
definition 2 (Sink node category): the Sink nodes are divided into three categories, which are respectively represented by the sets of Class _1, class _2and Class _3. Class _1 is a set of Sink nodes at four corners of a monitoring area, namely
Figure BDA0002088724090000043
Class _2 is a collection of nodes near four edges of a monitored area, i.e.
Figure BDA0002088724090000051
(ii) a Class _3 is the set of other Sink nodes.
Definition 3 (neighbor Sink node set NS) i ): sink node S i The set composed of adjacent Sink nodes in the horizontal and vertical directions is NS i (Neighbor nodes).
Therefore, each Sink node in Class _1 has 2 neighbor nodes, each Sink node in Class _2 has 3 neighbor nodes, and each Sink node in Class _3 has 4 neighbor nodes.
For Class _1: NS (server) 1 ＝{S 2 ,S 1+n }，NS n ＝{S n-1 ,S 2n }，
Figure BDA0002088724090000052
Figure BDA0002088724090000053
For Class _2: { S 1+n ,S 1+2n ,…,S 1+(n-2)n NS of } i ＝{S i-n ,S i+1 ,S i+n }，{S 2 ,S 3 ,…,S n-1 NS of } i ＝{S i-1 ,S i+1 ,S i+n }，{S 2n ,S 3n ,…,S n2-n NS of } i ＝{S i-n ,S i+n ,S i-1 }，
Figure BDA0002088724090000054
NS of i ＝{S i-n ,S i+1 ,S i-1 }；
For Class _3: s i NS of i ＝{S i-n ,S i+1 ,S i+n ,S i-1 }。
Definition 4 (destination Sink node set DS) i ): each sensor node exists and only exists in the grid range of a Sink node, and a set formed by the Sink node and the neighbor Sink nodes thereof is called a destination Sink node set of the sensor node and uses the DS i (Destination nodes).
2. Reliable routing algorithm based on sealed first price auction game
And (3) route discovery process:
(1) All Sink nodes broadcast route establishment RC (Routing Creation) messages to the neighbor nodes, wherein the format of the RC messages is (Sink node number, hop number to the Sink node, last hop node number and neighbor Sink node set), namely (S) i ,0,S i ,NS i )；
(2) Sensor node C i When the RC message is received:
a. checking whether NS exists in nodes within one-hop range of self i If the Sink node exists, the RC message is stopped being broadcasted, and the RC message is directly sent to the Sink node;
b. checking whether S exists in the neighbor Sink node set of the Sink node to which the self belongs i If not, the RC message is discarded;
c. remove RCThe information content is stored in the neighbor list of the self, the hop count value to the Sink node is added with 1 and updated, and then the RC information is continuously broadcasted (S) i To S i Hop count of (C) i ,NS i )；
(3) When no RC message in the network needs to be forwarded or the set time is exceeded, each node stores the own neighbor node and hop values to a plurality of Sink nodes.
And (3) data transmission process:
(1) The source node takes two Sink nodes closest to the source node in the destination Sink node set as destination Sink nodes;
(2) The source node respectively determines two sensor nodes of two destination Sink nodes as next hop nodes by an auction game method according to the neighbor list of the source node, and sends data to be sent to the two next hop nodes;
(3) The relay node determines a next hop node in the same way, and finally the data are respectively transmitted to two destination Sink nodes;
(4) And the Sink nodes share data, verify the accuracy of the data, correspondingly process the inspection result and finally send the processed data to a management center.
Sealing the first price auction game:
(1) Classic sealed first price auction game
Suppose there are n bidders, i.e., i =1,2, \8230;, n. Each bidder bids unpublished simultaneously and the auctioneer determines that the bidder with the highest price obtains the auction item. The yields for any two bidders i, j participating in the auction are:
Figure BDA0002088724090000061
wherein, b i Represents a bid of bidder i;
v i representing the value of the auction item to bidder i, subject to (0, 1) uniform distribution.
Suppose a bid b of bidder i i (v i ) Is v i Is then the expected yield of bidder i is:
Figure BDA0002088724090000071
the goal of bidder i is to maximize his expected revenue, namely:
Figure BDA0002088724090000072
the optimized first order condition of this equation is:
Figure BDA0002088724090000073
when in use
Figure BDA0002088724090000074
And (3) the optimal strategy for bidder i, namely:
Figure BDA0002088724090000075
solving the above differential equation yields:
Figure BDA0002088724090000076
this result is a bayesian nash balance where n bidders are participating in the classic sealed first price auction game.
The above process is a classic sealed first price auction gaming process with an even distribution of values of the auctioneer to bidders of (0,1). However, in an actual auction process, bidders may have a certain ability to judge the value of an auction item, and the probability distribution in the valuation process is approximately normal. Thus, a sealed first price auction game based on a standard normal distribution is proposed.
(2) Sealed first price auction game based on standard normal distribution
Suppose that the value of an auction for bidders is a standard normal distribution N (0, 1) of (— infinity, + ∞).
Introduction 1: bidders bid of
Figure BDA0002088724090000077
N bidders participate in bayesian nash equilibrium for a sealed first price auction game based on a standard normal distribution.
And (3) proving that: suppose there are n bidders, i =1,2, \8230, and n, the desired benefit of bidder i is:
Figure BDA0002088724090000078
the goal of bidder i is to maximize his expected revenue, namely:
Figure BDA0002088724090000079
the optimized first order condition of this equation is:
Figure BDA0002088724090000081
substituting this into equation (8) can result in:
Figure BDA0002088724090000082
the optimized first order conditioning of this formula is:
Figure BDA0002088724090000083
obtaining by solution:
Figure BDA0002088724090000084
and (3) analysis of equalization results: and the auctioneer has poor profit under the conditions that the Delta b is set as standard normal distribution and even distribution. The results of bayesian nash equalization for two auction games were analyzed:
Figure BDA0002088724090000085
therefore, the value of the auction items to the bidders is represented by adopting the standard normal distribution instead of the uniform distribution, so that the auctioneers can obtain higher profits and better meet the actual situation.
Data forwarding auction game:
(1) Auction gaming process
And establishing a sealed first price auction game model of the data forwarding process according to the process and the characteristics of large-scale IWSNs data forwarding. The game process is as shown in fig. 3, a node needing to send data is used as an auctioneer to initiate a game for selling, a neighbor node is used as a bidder to participate in the game, and an auction article is qualified for forwarding data. And each bidder gives an optimal bid according to the information such as the residual energy, the hop count to the destination Sink node and the like, the bidders compare the bids of all bidders, and the bidder with the highest bid obtains the qualification of forwarding data. And the sensor node which receives the data is used as an auctioneer of the next stage game, and the game is continuously initiated to the neighbor node. And finally, transmitting the data to a destination Sink node through multiple auction games.
In the auction game process, the sensor node can calculate the optimal quotation of the sensor node by combining the residual energy of the sensor node and the hop count to the destination Sink node. Therefore, the more reliable the node, the higher the price, and finally a transmission path with higher reliability can be determined.
(2) Auctioning avails for nodes
The auction node successfully sends the data to the next hop node of winning the bid, will receive the reward of winning the bid node payment, self will consume the cost of sending the data at the same time. Energy consumption for transmitting data E Tx (auc) depends on the length of the packet, l, and the distance d the packet travels:
Figure BDA0002088724090000091
wherein, E elec Represents the energy consumption required for transmitting 1bit data;
ε fs represents the power consumption of the wireless antenna amplifier;
d 0 representing a distance threshold between two sensor nodes.
When the data packet is successfully sent to the next hop node, the auction node obtains corresponding reward, and the successful forwarding rate theta of the data packet of the auction node auc Comprises the following steps:
Figure BDA0002088724090000092
wherein N is send (auc) represents the amount of data that the auction node has successfully transmitted in the past;
N rec (auc) represents the amount of data that the auction node has received in the past.
Thus, auctioning the avails u of a node auc Comprises the following steps:
Figure BDA0002088724090000093
wherein b represents the price paid by the winning node;
(3) Revenue of bidding node
If the bidding node wins the bid, the bidding node will be qualified to forward the data, and the sensor node receives the data, the energy consumption E is generated Rx (ten)：
E Rx (ten)＝l·E elec (17)
Thus, the revenue u of the bidding node ten Comprises the following steps:
u ten ＝η·(v ten -b ten -E Rx (ten)+θ ten ·u auc (ten)) (18)
wherein, eta value is 1 or 0,1 represents bid winning of the bidding node, and 0 represents uncommitted bid;
v ten represents the value of the auction item to the bidding node, this value obeying a standard normal distribution N (0, 1) on (- ∞, + ∞);
θ ten indicating the successful forwarding rate of the data packet of the bidding node;
u auc (ten) indicates the profit obtained by the bidding node as the auction node for the next game.
(4) Bayesian Nash equilibrium computation
2, leading: bidders bid as
Figure BDA0002088724090000101
The bidding nodes participate in Bayesian Nash equalization of the auction game.
And (3) proving that: assuming that the auction node has n neighbor nodes as bidding nodes to participate in the game, the expected profit of the bidding node i is as follows:
u i ＝η·(v i -b i -l·E elec +θ i ·u auc (i))Π j≠i p(b j ＜b i ) (19)
the goal of bidding node i is to maximize his expected revenue, namely:
Figure BDA0002088724090000102
the optimized first order condition of this equation is:
Figure BDA0002088724090000103
Figure BDA0002088724090000111
substituting this into equation (20) can result in:
Figure BDA0002088724090000112
the optimized first order conditioning of this formula is:
Figure BDA0002088724090000113
obtaining by solution:
Figure BDA0002088724090000114
(5) Bidding node optimal bidding
Considering that the reliability of the sensor node is related to the residual energy of the sensor node and the hop count to the Sink node, assume the value v of the auction object to the bidding node i i The calculation method comprises the following steps:
Figure BDA0002088724090000115
wherein E is i Representing the remaining energy of the bidding node i;
h i represents the average hop count h from the bidding node i to the destination Sink node i ≥1。
Therefore, the more the remaining energy of the bidding node is, the smaller the hop count to the Sink node is, the higher the value of the auction object to the node is, and the more reliable the transmission link from the bidding node to the bidding node is.
Successful data packet forwarding rate theta of bidding node i i Comprises the following steps:
Figure BDA0002088724090000116
the bidding node i is used as an auction node of the next game, and the obtained income is as follows:
Figure BDA0002088724090000121
therefore, substituting equations (25), (26), and (27) into equation (24), each bidding node can calculate its own optimal bid.
(6) Dynamic profit control method
In consideration of large-scale IWSNs, some sensor nodes can generate selfish behaviors such as refusing to participate in a game process, giving up forwarding data packets, false quotation and the like due to limited resources, and the reliability of data transmission is seriously influenced. In order to promote cooperation among sensor nodes, a dynamic yield control method is proposed:
defining a trustworthiness Z of a sensor node i i The total earnings obtained for the node to participate in the game before the current time, assuming that the credibility of the sensor node decreases with increasing time:
Z i (t+1)＝(1-σ i (t))Z i (t) (28)
wherein: z is a linear or branched member i (t) represents the reliability of the sensor node i at time t;
σ i (t) represents a descent coefficient of the sensor node i at time t;
once the credibility of the sensor node is lower than a set threshold, the node is considered as an untrusted node. For a positively cooperating sensor node, a corresponding reward will be obtained: each time the sensor node successfully sends or forwards data, the decreasing coefficient of the credibility of the sensor node changes. The droop coefficient is related to the total amount of data sent by the sensor node:
Figure BDA0002088724090000122
therefore, in order to enable the credibility to meet the conditions, the sensor nodes can strive for the opportunity of forwarding data in a game-playing mode, and therefore the credibility of the sensor nodes is increased. The larger the total data amount forwarded by the sensor node, the slower the value of the reliability decreases.
(7) Selection of next hop node
After the auction node initiates the game, waiting for bidNode bidding, when the auction node receives the bids of all bidding nodes or exceeds a waiting time threshold value, checking the credibility Z of the bidding node i with the highest bid i ：
a.Z i ≥Z 0 Node i becomes the next hop node;
b.Z i ＜Z 0 removing the node i from the neighbor list, and continuously checking the credibility of the node with the highest bid in the rest bidding nodes;
c. and repeating the steps until the next hop node meeting the requirement is found.
In order to reduce the energy consumption of data transmission, each sensor node records the result of the last game, when data needs to be forwarded, the reliability of the recorded next-hop node is directly checked, and if the reliability meets the requirement, the data is directly sent to the node. And if the credibility does not meet the requirement, the game is initiated to the neighbor node again.
3 routing algorithm execution procedure
Step1: and constructing a route. And after the node deployment is completed, starting to construct an initial route. After the route construction is finished, each sensor node stores the hop count from the neighbor node to each destination Sink node and information such as a destination node set in a neighbor list of the sensor node;
step2: and selecting a destination Sink node. The source node selects two Sink nodes closest to the source node from the destination Sink node set as final destination nodes;
step3: it is determined whether to initiate a game. The sensor node needing to send data checks the credibility of the next hop node determined by the last game, and directly sends data and transfers to Step7 if the credibility meets the requirement; the steering Step4 is not met;
step4: the auction node initiates the game. A sensor node needing to send data initiates an auction game to a neighbor node;
step5: the bidding node gives the optimal bid. The sensor nodes participating in the auction game respectively calculate the optimal bids of the sensor nodes and send the bids to the auction nodes;
step6: the next hop node is determined. The auction nodes compare the bids of all the bidding nodes and check the credibility of the sensor node with the highest bid. If the reliability meets the requirement, determining the sensor node as a next hop node; otherwise, discarding the node, and continuously checking the credibility of the node with the highest bid in the rest auction nodes until the node meeting the requirements is found;
step7: and the sensor node receiving the data checks whether a destination Sink node exists in a one-hop range of the sensor node. And if the data exist, sending the data to the destination Sink node, and if the data do not exist, repeating Step3-Step7 until the data are sent to the destination Sink node.

Claims (1)

1. The reliable routing method facing IWSN based on sealed first price auction game is a technology for ensuring reliable data transmission in large-scale IWSNs, and the main contents comprise: a network model is provided, and a network model with a plurality of Sink nodes is adopted so as to reduce data transmission distance and transmission time delay; in order to ensure the fault tolerance of the route, a data transmission mechanism of dual-path transmission is adopted; in order to select a transmission link with high reliability, an optimal next hop node is selected by using a sealed first price auction game method based on standard normal distribution; in order to promote the cooperation among the sensor nodes, a dynamic gain control method is provided; specifically, the implementation process of the reliable routing method is described, which specifically includes:
design of network model
A reliable routing method based on a sealed first price auction game adopts a network model of multiple Sink nodes; in the model, the number N of Sink nodes which guarantee the service life of the network to be maximized and enable the network cost to be the lowest is obtained on the basis of a grid network structure by using the existing multi-Sink node optimized deployment method, and the uniform deployment in a monitoring area is finally determined
Figure FDA0004000260340000011
A Sink node; according to the network model, the serial number of the Sink node, the type of the Sink node, the set of the neighbor Sink nodes and the destination are providedDefining a Sink node set;
reliable routing method based on sealed first price auction game
In the route discovery process, each sensor node establishes a neighbor list to a neighbor Sink node, stores neighbor node information of the sensor node and hop count to the neighbor Sink node, and in the data transmission process, a source node determines two Sink nodes which are closest to the source node from the neighbor list as destination Sink nodes and transmits data to the two destination Sink nodes; in the process of determining a transmission path, selecting a next hop node by using a sealed first price auction game based on standard normal distribution in an on-demand routing mode, and providing a dynamic profit control method to promote the cooperation among sensor nodes;
the dynamic gain control method comprises the following steps:
defining a trustworthiness Z of a sensor node i i The total earnings obtained for the node to participate in the game before the current time, assuming that the credibility of the sensor node decreases with increasing time:
Z i (t+1)＝(1-σ i (t))Z i (t)
wherein: z i (t) represents the reliability of the sensor node i at time t;
σ i (t) represents a descent coefficient of the sensor node i at time t;
once the credibility of the sensor node is lower than a set threshold value, the node is considered as an untrusted node; for a positively cooperating sensor node, a corresponding reward will be obtained: the decreasing coefficient of the credibility of the sensor node changes every time the sensor node successfully sends or forwards data; the descent coefficient is related to the total amount of data sent by the sensor node:
Figure FDA0004000260340000021
therefore, in order to enable the credibility to meet the conditions, the sensor nodes can strive for the opportunity of forwarding data in a game participation mode, and therefore the credibility of the sensor nodes is increased; the more the total data quantity forwarded by the sensor node is, the slower the value of the reliability is reduced;
performing the process of reliable routing method
Step1: constructing a route; after the node deployment is finished, an initial route is built, and after the route building is finished, each sensor node stores the hop count from a neighbor node to each destination Sink node and destination node set information into a neighbor list of the sensor node;
step2: selecting a destination Sink node; the source node selects two Sink nodes closest to the source node from the destination Sink node set as final destination nodes;
step3: determining whether to initiate a game, checking the credibility of the next hop node determined by the last game by the sensor node needing to send data, and if the credibility Z of the bidding node i is high i ≥Z 0 Directly sending data and forwarding to Step7; otherwise, turning to Step4;
step4: the auction node initiates a game, and the sensor node needing to send data initiates an auction game to its neighbor node;
step5: the bidding nodes give out optimal bids, participate in sensor nodes in the auction game, respectively calculate the optimal bids of the sensor nodes, and send the bids to the auction nodes;
step6: determining a next hop node, comparing bids of all bidding nodes by the auction node, and checking the reliability of the sensor node with the highest bid; if confidence level Z of node i i ≥Z 0 Determining the sensor node as a next hop node; otherwise, discarding the node, and continuously checking the credibility of the node with the highest bid in the rest auction nodes until the node meeting the requirements is found;
step7: and the sensor node receiving the data checks whether the destination Sink node exists in a one-hop range of the sensor node, if so, the sensor node sends the data to the destination Sink node, and if not, the Step3-Step7 is repeated until the data is sent to the destination Sink node.
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