CN115103351A - Wireless sensor network distributed positioning method under privacy protection - Google Patents
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Abstract
本发明公开了一种隐私保护下的无线传感器网络分布式定位方法,假定场景中所有传感器节点都位于锚节点的凸包内,每个传感器节点可以找到三个相邻的节点作为一个三角剖分集,使其位于这些相邻节点形成的凸包中;传感器节点和相邻节点可以成对通信,同时考虑节点位置的私密性;当传感器在进行通信交互时,基于隐私保护策略对节点位置信息加入时变增量噪声,使攻击者无法窃取到节点的私有位置,从而能够在保护节点位置私密的情况下对无线传感器网络进行精确定位。
The invention discloses a distributed positioning method for a wireless sensor network under privacy protection. Assuming that all sensor nodes in the scene are located in the convex hull of the anchor node, each sensor node can find three adjacent nodes as a triangulation set , so that it is located in the convex hull formed by these adjacent nodes; sensor nodes and adjacent nodes can communicate in pairs, while considering the privacy of node locations; when sensors communicate and interact, add node location information based on privacy protection policies. The time-varying incremental noise makes it impossible for attackers to steal the private location of the node, so that the wireless sensor network can be precisely located while keeping the location of the node private.
Description
技术领域technical field
本发明涉及无线传感器网络定位技术领域,更为具体地讲,涉及一种隐私保护下的无线传感器网络分布式定位方法。The invention relates to the technical field of wireless sensor network positioning, and more particularly, to a distributed positioning method for wireless sensor networks under privacy protection.
背景技术Background technique
定位是无线传感器网络的一个基本问题,近年来引起了研究人员的广泛关注,激发出许多潜在的应用,如位置支持服务,智能家居系统和目标跟踪。传感器位置信息是准确处理传感器测量的关键,但在随机部署传感器的应用中,传感器的准确位置是未知的。因此,如何设计合适的定位算法是实现传感器高效准确工作的关键。Localization, a fundamental problem in wireless sensor networks, has attracted extensive attention of researchers in recent years, inspiring many potential applications, such as location support services, smart home systems, and object tracking. Sensor location information is key to accurately processing sensor measurements, but in applications where sensors are deployed randomly, the exact location of the sensor is unknown. Therefore, how to design a suitable localization algorithm is the key to realize the efficient and accurate work of the sensor.
目前基于重心坐标的分布式迭代定位算法已成为一种广泛应用的高精度分布式定位算法,该算法通过测量传感器节点之间的相对距离,将定位过程表示为一个矩阵向量形式的迭代过程,能够全局收敛到传感器的精确位置。值得注意的是,虽然已有基于分布式框架的传感器定位算法被提出,但大多数算法并未考虑到传感器之间的信息交互会引起严重的隐私问题。At present, the distributed iterative positioning algorithm based on barycentric coordinates has become a widely used high-precision distributed positioning algorithm. By measuring the relative distance between sensor nodes, the algorithm expresses the positioning process as an iterative process in the form of a matrix vector, which can Globally converge to the precise location of the sensor. It is worth noting that although sensor localization algorithms based on distributed frameworks have been proposed, most of them do not consider that the information interaction between sensors will cause serious privacy issues.
以未加密的明文形式进行的信息交互很容易受到外部攻击者的攻击,攻击者可以通过入侵节点间的通信链路窃取信息,从而侵犯传感器节点的隐私信息,破坏整个定位系统。此外,攻击者还可以通过将距离测量值与监控区域相关联,推断出其他非锚节点的位置。因此,制定相应的策略来保护传感器节点的私有位置是一个值得关注的话题。The information exchange in the form of unencrypted plaintext is easily attacked by external attackers. The attacker can steal information through the communication link between intrusion nodes, thereby infringing the privacy information of sensor nodes and destroying the entire positioning system. Additionally, attackers can also infer the location of other non-anchor nodes by correlating distance measurements with the monitored area. Therefore, formulating corresponding strategies to protect the private locations of sensor nodes is a topic worthy of attention.
发明内容SUMMARY OF THE INVENTION
本发明的目的在于克服现有技术的不足,提供一种隐私保护下的无线传感器网络分布式定位方法,在无线传感器网络实现精确定位过程中,通过对各节点增加时变增量噪声方式来保护传感器节点的私有位置。The purpose of the present invention is to overcome the deficiencies of the prior art and provide a distributed positioning method for wireless sensor networks under privacy protection. The private location of the sensor node.
为实现上述发明目的,本发明一种隐私保护下的无线传感器网络分布式定位方法,其特征在于,包含以下步骤:In order to achieve the above purpose of the invention, a distributed positioning method for a wireless sensor network under privacy protection of the present invention is characterized in that, it includes the following steps:
(1)、设置无线传感器网络(1), set the wireless sensor network
设待定位的无线传感器网络由二维空间中的n个节点组成,每个节点代表一个无线传感器;Suppose the wireless sensor network to be located consists of n nodes in a two-dimensional space, each node represents a wireless sensor;
在待定位的无线传感器网络中将已知自身坐标位置的节点记为锚节点,而未知自身坐标位置的节点记为非锚节点,从而将无线传感器网络中的节点分为锚节点集和非锚节点集其中,记锚节点集由s个锚节点Xi组成,记为记非锚节点集由n-s个非锚节点Yj组成,记为 In the wireless sensor network to be located, the node whose coordinate position is known is recorded as the anchor node, and the node whose own coordinate position is unknown is recorded as the non-anchor node, so that the nodes in the wireless sensor network are divided into anchor node sets and non-anchor node sets Among them, the anchor node set is recorded It consists of s anchor nodes X i , denoted as set of non-anchor nodes It consists of ns non-anchor nodes Y j , denoted as
(2)、记录锚节点及非锚节点的坐标;(2), record the coordinates of anchor nodes and non-anchor nodes;
记录锚节点集中各锚节点的坐标,记为Pa=[p1,...,pi,...,ps]T,其中,pi为第i个锚节点Xi的坐标;record anchor node set The coordinates of each anchor node in , denoted as P a =[p 1 ,..., pi ,...,p s ] T , where p i is the coordinate of the ith anchor node Xi;
将非锚节点集中的非锚节点的坐标表示为Pb=[ps+1,...,ps+j,...,pn]T,ps+j表示第j个非锚节点Yj的坐标;set non-anchor nodes The coordinates of the non-anchor nodes in are expressed as P b =[ps +1 ,...,ps +j ,...,p n ] T , where ps +j represents the jth non-anchor node Y j coordinate;
(3)、设置非锚节点的相邻节点集;(3), set the adjacent node set of the non-anchor node;
定义非锚节点Yj的相邻节点集其中,Kj是由距离非锚节点Yj最近的3个节点dj1,dj2,dj3构成;Define the adjacent node set of non-anchor node Y j Among them, K j is composed of three nodes d j1 , d j2 , and d j3 that are closest to the non-anchor node Y j ;
(4)、建立非锚节点位置的分布式定位模型;(4) Establish a distributed positioning model for the location of non-anchor nodes;
假设非锚节点集中所有非锚节点都位于锚节点集的锚节点的凸包内,遍历非锚节点集在每个迭代时刻t,更新非锚节点Yj的位置;Assuming a non-anchor node set All non-anchor nodes in the anchor node set Within the convex hull of the anchor node, traverse the set of non-anchor nodes At each iteration time t, update the position of the non-anchor node Y j ;
其中,pj(t)表示第j个非锚节点Yj在时刻t时的坐标,γ为增益系数,pk为t时刻非锚节点Yj相邻节点djk的位置坐标,ajk为非锚节点Yj相对于其相邻节点djk的重心坐标;Among them, p j (t) represents the coordinate of the jth non-anchor node Y j at time t, γ is the gain coefficient, p k is the position coordinate of the adjacent node d jk of the non-anchor node Y j at time t, and a jk is The barycentric coordinates of the non-anchor node Y j relative to its adjacent node d jk ;
(5)、隐私保护下同步迭代定位非锚节点的位置;(5) Synchronously iteratively locate the location of non-anchor nodes under privacy protection;
(5.1)、设置的最大迭代时刻t*;随机设置锚节点Xi和非锚节点Yj的初始位置,其中,锚节点Xi的初始位置设置为pi(0)=pi,随机设置非锚节点Yj的初始位置为pj(0);(5.1), the set maximum iteration time t * ; the initial positions of the anchor node X i and the non-anchor node Y j are randomly set, wherein, the initial position of the anchor node X i is set to p i (0)=p i , set randomly The initial position of the non-anchor node Y j is p j (0);
设置无线传感器网络中各节点时变增量噪声其中锚节点Xi的噪声参数δi=1;非锚节点集Yj的噪声参数δj满足约束 Setting time-varying incremental noise of each node in wireless sensor network where the noise parameter δ i =1 of the anchor node X i ; the noise parameter δ j of the non-anchor node set Y j satisfies the constraint
(5.2)、在迭代时刻t,对每个节点的位置估计增加时变增量噪声σw(t),进而加强隐私保护;(5.2), at iterative time t, add time-varying incremental noise σ w (t) to the position estimation of each node, thereby enhancing privacy protection;
其中,0<ζ<1为常值参数;Among them, 0<ζ<1 is a constant value parameter;
(5.3)、在迭代时刻t,分别计算锚节点Xi和非锚节点集Yj在引入时变增量噪声后的位置估计为:(5.3) At iterative time t, calculate the position estimates of anchor node X i and non-anchor node set Y j after introducing time-varying incremental noise as:
其中, in,
(5.4)、通过公式(3)的隐私保护操作后,各节点将自身当前时刻的位置估计发送给相邻节点,进一步得到下一时刻各节点的位置估计;(5.4) After passing the privacy protection operation of formula (3), each node sends its current position estimate to adjacent nodes, and further obtains the position estimate of each node at the next moment;
(5.5)、将所有非锚节点相对于其相邻节点集Kj的重心坐标写成矩阵-向量形式为:(5.5), write the barycentric coordinates of all non-anchor nodes relative to their adjacent node set K j in matrix-vector form as:
其中,F、H均为次随机矩阵,[F H]为行随机矩阵,当相邻节点djk属于非锚节点Yj的三角剖分集时,[F H]jk=ajk,当相邻节点djk不属于非锚节点Yj的三角剖分集时,[F H]jk=0,Is和In-s为单位矩阵;Among them, F and H are sub-random matrices, [FH] is a row random matrix, when the adjacent node d jk belongs to the triangulation set of the non-anchor node Y j , [FH] jk =a jk , when the adjacent node d When jk does not belong to the triangulation set of the non-anchor node Y j , [FH] jk =0, I s and I ns are identity matrices;
(5.6)、当迭代时刻t达到设置的最大迭代时刻t*时,计算出非锚节点集中基于锚节点集表示的位置为:(5.6), when the iteration time t reaches the set maximum iteration time t * , calculate the non-anchor node set anchor node set The indicated location is:
至此,基于隐私保护策略的非锚节点集的位置定位完成。So far, the non-anchor node set based on the privacy protection policy The location positioning is completed.
本发明的发明目的是这样实现的:The purpose of the invention of the present invention is achieved in this way:
本发明一种隐私保护下的无线传感器网络分布式定位方法,假定场景中所有传感器节点都位于锚节点的凸包内,每个传感器节点可以找到三个相邻的节点作为一个三角剖分集,使其位于这些相邻节点形成的凸包中;传感器节点和相邻节点可以成对通信,同时考虑节点位置的私密性;当传感器在进行通信交互时,基于隐私保护策略对节点位置信息加入时变增量噪声,使攻击者无法窃取到节点的私有位置,从而能够在保护节点位置私密的情况下对无线传感器网络进行精确定位。The present invention is a distributed positioning method for wireless sensor network under privacy protection. It is assumed that all sensor nodes in the scene are located in the convex hull of the anchor node, and each sensor node can find three adjacent nodes as a triangulation set, so that the It is located in the convex hull formed by these adjacent nodes; sensor nodes and adjacent nodes can communicate in pairs, while considering the privacy of the node location; when the sensor is communicating and interacting, the time-varying node location information is added based on the privacy protection strategy. Incremental noise makes it impossible for attackers to steal the private location of the node, so that the wireless sensor network can be precisely located while keeping the location of the node private.
同时,本发明一种隐私保护下的无线传感器网络分布式定位方法还具有以下有益效果:At the same time, the distributed positioning method of the wireless sensor network under the privacy protection of the present invention also has the following beneficial effects:
(1)、本发明在分布式定位迭代过程中,将满足约束条件的噪声项加入到传感器节点的位置估计中,该方法不仅对传感器网络定位精度没有影响,而且在攻击者窃取邻居节点位置信息的情况下,能够有效保证节点精确位置的私密性。(1) In the distributed positioning iteration process of the present invention, the noise terms that satisfy the constraints are added to the position estimation of the sensor nodes. This method not only has no effect on the positioning accuracy of the sensor network, but also prevents the attacker from stealing the position information of the neighbor nodes. In this case, the privacy of the precise location of the node can be effectively guaranteed.
(2)、本发明考虑到在一些真实的传感器网络环境中,具有远程观察能力的攻击者可能会窃取其邻居的部分入站信息,而经典的隐私保护方法局限于攻击者只能窃取其邻居节点的出站信息、而不能窃取其邻居节点入站信息的情形。于是本发明提出了一种引入时变增量噪声的隐私保护新策略,该策略在攻击者窃取其邻居节点入站信息的情况下仍然能很好的保护节点的隐私。(2) The present invention considers that in some real sensor network environments, attackers with remote observation capabilities may steal part of the inbound information of their neighbors, while the classical privacy protection method is limited to the fact that attackers can only steal their neighbors A node's outbound information, but cannot steal the inbound information of its neighbors. Therefore, the present invention proposes a new privacy protection strategy that introduces time-varying incremental noise, which can still protect the privacy of the node well when the attacker steals the inbound information of its neighbor nodes.
附图说明Description of drawings
图1是本发明一种隐私保护下的无线传感器网络分布式定位方法流程图;1 is a flowchart of a distributed positioning method for a wireless sensor network under a privacy protection of the present invention;
图2是是实验中所设置的一组树莓派放置示意图;Figure 2 is a schematic diagram of the placement of a group of Raspberry Pis set up in the experiment;
图3是无线传感器网络中一个节点位于其相邻节点的凸包示意图;Figure 3 is a schematic diagram of the convex hull of a node in the wireless sensor network located at its adjacent node;
图4是无线传感器网络中10个传感器节点之间的交互拓扑图;Fig. 4 is the interaction topology diagram between 10 sensor nodes in the wireless sensor network;
图5是无线传感网络中7个非锚节点随机设置的初始位置;Figure 5 is the initial position randomly set by 7 non-anchor nodes in the wireless sensor network;
图6是经过40次迭代后7个非锚节点最终收敛到的精确位置。Figure 6 is the precise location to which the 7 non-anchor nodes finally converge after 40 iterations.
具体实施方式Detailed ways
下面结合附图对本发明的具体实施方式进行描述,以便本领域的技术人员更好地理解本发明。需要特别提醒注意的是,在以下的描述中,当已知功能和设计的详细描述也许会淡化本发明的主要内容时,这些描述在这里将被忽略。The specific embodiments of the present invention are described below with reference to the accompanying drawings, so that those skilled in the art can better understand the present invention. It should be noted that, in the following description, when the detailed description of known functions and designs may dilute the main content of the present invention, these descriptions will be omitted here.
实施例Example
图1是本发明一种隐私保护下的无线传感器网络分布式定位方法流程图。FIG. 1 is a flowchart of a distributed positioning method for a wireless sensor network under privacy protection according to the present invention.
在本实施例中,如图1所示,本发明一种隐私保护下的无线传感器网络分布式定位方法,包含以下步骤:In this embodiment, as shown in FIG. 1 , a distributed positioning method for a wireless sensor network under privacy protection of the present invention includes the following steps:
S1、设置无线传感器网络;S1. Set up the wireless sensor network;
在本实施例中,如图2所示,通过一组树莓派以分布式的方式进行无线传感器网络的定位,其二维空间中共计n=10个节点组成,每个节点代表一个无线传感器,无线传感器网络中的节点又分为锚节点集和非锚节点集锚节点的位置是静态已知的。在本实施例中,锚节点集由3个锚节点Xi组成,记为非锚节点集由7个非锚节点Yj组成,记为 In this embodiment, as shown in Fig. 2, the wireless sensor network is located in a distributed manner through a group of Raspberry Pi, which consists of a total of n=10 nodes in the two-dimensional space, and each node represents a wireless sensor , the nodes in the wireless sensor network are further divided into anchor node sets and non-anchor node sets The location of the anchor node is known statically. In this embodiment, the anchor node set It consists of 3 anchor nodes X i , denoted as non-anchor node set It consists of 7 non-anchor nodes Y j , denoted as
S2、记录锚节点及非锚节点的坐标;S2, record the coordinates of anchor nodes and non-anchor nodes;
记录锚节点集中各锚节点的坐标,记为Pa=[p1,p2,p3]T;record anchor node set The coordinates of each anchor node in , denoted as P a =[p 1 ,p 2 ,p 3 ] T ;
将非锚节点集中这些未知坐标的非锚节点的坐标表示为Pb=[p4,...,p3+j,...,p10]T,p3+j表示第j个非锚节点Yj的坐标;set non-anchor nodes The coordinates of these non-anchor nodes with unknown coordinates in are expressed as P b =[p 4 ,...,p 3+j ,...,p 10 ] T , where p 3+j represents the jth non-anchor node Y j coordinate of;
S3、设置非锚节点的相邻节点集;S3. Set the adjacent node set of the non-anchor node;
定义非锚节点Yj的相邻节点集其中,Kj由距离非锚节点Yj最近的3个节点dj1,dj2,dj3构成;Define the adjacent node set of non-anchor node Y j Among them, K j consists of three nodes d j1 , d j2 , and d j3 closest to the non-anchor node Y j ;
S4、建立非锚节点位置的分布式定位模型;S4. Establish a distributed positioning model for the location of non-anchor nodes;
在本实施例中,图4为无线传感器网络中各传感器的交互拓扑图。无线传感器网络存在3个锚节点,用Anchori(i=1,2,3)表示;网络中存在7个非锚节点,用nodej(j=4,5,...,10)表示。假设非锚节点集中所有非锚节点都位于的锚节点的凸包内,遍历非锚节点集在每个迭代时刻t,更新非锚节点Yj的位置;In this embodiment, FIG. 4 is an interaction topology diagram of each sensor in the wireless sensor network. There are 3 anchor nodes in the wireless sensor network, which are represented by Anchori(i=1,2,3); there are 7 non-anchor nodes in the network, which are represented by nodej(j=4,5,...,10). Assuming a non-anchor node set All non-anchor nodes in Within the convex hull of the anchor node, traverse the set of non-anchor nodes At each iteration time t, update the position of the non-anchor node Y j ;
其中,pj(t)表示第j个非锚节点Yj在时刻t时的坐标,γ为增益系数,pk为t时刻非锚节点Yj相邻节点djk的位置坐标,ajk为非锚节点Yj相对于其相邻节点djk的重心坐标;。Among them, p j (t) represents the coordinate of the jth non-anchor node Y j at time t, γ is the gain coefficient, p k is the position coordinate of the adjacent node d jk of the non-anchor node Y j at time t, and a jk is The barycentric coordinates of the non-anchor node Y j relative to its adjacent node d jk ; .
在本实施例中,如图3所示,无线传感器网络中非锚节点Yj的一个三角剖分集,非锚节点Yj相对于相邻三个节点r、s、t的重心坐标为ajr、ajs、ajt,非锚节点Yj的位置坐标pj满足:In this embodiment, as shown in FIG. 3 , in a triangulation set of non-anchor node Y j in the wireless sensor network, the barycentric coordinate of non-anchor node Y j relative to three adjacent nodes r, s, and t is a jr , a js , a jt , the position coordinate p j of the non-anchor node Y j satisfies :
pj=ajrpr+ajsps+ajtpt (2)p j =a jr p r +a js p s +a jt p t (2)
其中,ajr+ajs+ajt=1;Among them, a jr +a js +a jt =1;
非锚节点Yj的重心坐标可以通过指定三角形之间的带符号面积的比例来计算:The barycentric coordinates of the non-anchor nodes Y j can be calculated by specifying the ratio of the signed areas between the triangles:
其中,SΔjst、SΔjrt、SΔjrs、SΔrst可通过节点之间的相对距离测量得到,利用Cayley-Menger行列式计算,以SΔjst为例:Among them, S Δjst , S Δjrt , S Δjrs , S Δrst can be obtained by measuring the relative distance between nodes, and calculated by the Cayley-Menger determinant, taking S Δjst as an example:
S5、隐私保护下同步迭代定位非锚节点的位置;S5. Synchronously iteratively locate the position of the non-anchor node under privacy protection;
S5.1、设置的最大迭代时刻t*;随机设置锚节点Xi和非锚节点Yj的初始位置,其中,锚节点Xi的初始位置设置为pi(0)=pi,随机设置非锚节点Yj的初始位置为pj(0);S5.1, the maximum iteration time t * set; randomly set the initial positions of the anchor node X i and the non-anchor node Y j , wherein, the initial position of the anchor node X i is set to p i (0)=p i , set randomly The initial position of the non-anchor node Y j is p j (0);
如图4所示,无线传感器网络各节点之间存在频繁的通信交互。在节点进行信息交换的过程中,为了防止攻击者窃取信息,引入时变增量噪声的隐私保护策略。As shown in Figure 4, there are frequent communication interactions among the nodes of the wireless sensor network. In the process of information exchange between nodes, in order to prevent attackers from stealing information, a privacy protection strategy of time-varying incremental noise is introduced.
设置无线传感器网络中各节点时变增量噪声其中锚节点Xi的噪声参数δi=1;非锚节点集Yj的噪声参数δj满足约束 Setting time-varying incremental noise of each node in wireless sensor network where the noise parameter δ i =1 of the anchor node X i ; the noise parameter δ j of the non-anchor node set Y j satisfies the constraint
S5.2、对每个节点的位置估计加入时变增量噪声那么在迭代时刻t,对每个节点的位置估计增加时变增量噪声σw(t)为:S5.2. Add time-varying incremental noise to the position estimation of each node Then at the iteration time t, the time-varying incremental noise σ w (t) is added to the position estimate of each node as:
其中,0<ζ<1为随机设置的常值参数,可以发现加入的噪声随着迭代时刻的推移而递增。Among them, 0<ζ<1 is a constant value parameter set randomly, and it can be found that the added noise increases with the passage of the iteration time.
S5.3、在迭代时刻t,分别计算锚节点Xi和非锚节点集Yj在引入时变增量噪声后的位置估计为:S5.3. At the iteration time t, calculate the position estimates of the anchor node X i and the non-anchor node set Y j respectively after introducing the time-varying incremental noise as:
其中, in,
S5.4、通过公式(6)的隐私保护操作后,各节点将自身当前时刻的位置估计发送给相邻节点,进一步得到下一时刻各节点的位置估计;S5.4. After passing the privacy protection operation of formula (6), each node sends its current position estimate to adjacent nodes, and further obtains the position estimate of each node at the next moment;
S5.5、在本实施例中,将7个非锚节点相对于其相邻节点集Kj的重心坐标写成矩阵-向量形式为:S5.5. In this embodiment, the barycentric coordinates of 7 non-anchor nodes relative to their adjacent node set K j are written in matrix-vector form as:
其中,F、H均为次随机矩阵,[F H]为行随机矩阵,当相邻节点djk属于非锚节点Yj的三角剖分集时,[F H]jk=ajk,当相邻节点djk不属于非锚节点Yj的三角剖分集时,[F H]jk=0,Is和In-s为单位矩阵;Among them, F and H are sub-random matrices, [FH] is a row random matrix, when the adjacent node d jk belongs to the triangulation set of the non-anchor node Y j , [FH] jk =a jk , when the adjacent node d When jk does not belong to the triangulation set of the non-anchor node Y j , [FH] jk =0, I s and I ns are identity matrices;
S5.6、当迭代时刻t达到设置的最大迭代时刻t*时,计算出非锚节点集中基于锚节点集表示的位置为:S5.6. When the iteration time t reaches the set maximum iteration time t * , calculate the non-anchor node set anchor node set The indicated location is:
至此,基于隐私保护策略下的非锚节点集的位置定位完成。So far, based on the non-anchor node set under the privacy protection policy The location positioning is completed.
图5是无线传感器网络中7个非锚节点随机设置的初始位置,其中Node j(j=4,5,...,10)为给出的非锚节点的初始位置估计,可以看到初始估计与实际位置误差较大。利用本发明隐私保护下的迭代定位算法,非锚节点的估计位置逐渐靠近实际位置。图6是40次迭代后传感网络器中7个非锚节点收敛到的准确位置,可以看到非锚节点Node j(j=4,5,...,10)都能收敛到传感器节点的实际位置。Figure 5 is the initial position randomly set by 7 non-anchor nodes in the wireless sensor network, where Node j (j=4, 5,..., 10) is the given initial position estimate of the non-anchor node, it can be seen that the initial position There is a large error between the estimate and the actual position. Using the iterative positioning algorithm under the privacy protection of the present invention, the estimated position of the non-anchor node gradually approaches the actual position. Figure 6 is the exact location of the 7 non-anchor nodes in the sensor network after 40 iterations. It can be seen that the non-anchor nodes Node j (j=4, 5,..., 10) can all converge to the sensor nodes actual location.
尽管上面对本发明说明性的具体实施方式进行了描述,以便于本技术领域的技术人员理解本发明,但应该清楚,本发明不限于具体实施方式的范围,对本技术领域的普通技术人员来讲,只要各种变化在所附的权利要求限定和确定的本发明的精神和范围内,这些变化是显而易见的,一切利用本发明构思的发明创造均在保护之列。Although the illustrative specific embodiments of the present invention have been described above to facilitate the understanding of the present invention by those skilled in the art, it should be clear that the present invention is not limited to the scope of the specific embodiments. For those skilled in the art, As long as various changes are within the spirit and scope of the present invention as defined and determined by the appended claims, these changes are obvious, and all inventions and creations utilizing the inventive concept are included in the protection list.
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Citations (4)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US20140047242A1 (en) * | 2011-04-21 | 2014-02-13 | Tata Consultancy Services Limited | Method and system for preserving privacy during data aggregation in a wireless sensor network |
CN109511149A (en) * | 2018-12-22 | 2019-03-22 | 山西财经大学 | A kind of wireless sensor network routing method based on pseudo- spiral |
CN113453143A (en) * | 2021-05-14 | 2021-09-28 | 浙江工业大学 | Source position privacy protection method of dynamic phantom node strategy |
CN113891244A (en) * | 2021-11-16 | 2022-01-04 | 电子科技大学 | Wireless sensor network positioning method under DoS attack |
-
2022
- 2022-06-07 CN CN202210634055.2A patent/CN115103351B/en active Active
Patent Citations (4)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US20140047242A1 (en) * | 2011-04-21 | 2014-02-13 | Tata Consultancy Services Limited | Method and system for preserving privacy during data aggregation in a wireless sensor network |
CN109511149A (en) * | 2018-12-22 | 2019-03-22 | 山西财经大学 | A kind of wireless sensor network routing method based on pseudo- spiral |
CN113453143A (en) * | 2021-05-14 | 2021-09-28 | 浙江工业大学 | Source position privacy protection method of dynamic phantom node strategy |
CN113891244A (en) * | 2021-11-16 | 2022-01-04 | 电子科技大学 | Wireless sensor network positioning method under DoS attack |
Non-Patent Citations (3)
Title |
---|
FRANCESCO BUCCAFURRI ECT.: "A Privacy-Preserving Localization Service for Assisted Living Facilities", 《IEEE TRANSACTIONS ON SERVICES COMPUTING》, 29 December 2016 (2016-12-29) * |
YUNKAI LV ECT.: "Distributed Localization of Multiagent Systems With Imperfect Channels Based on Iterative Learning", 《IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS》, 27 October 2021 (2021-10-27) * |
任鹏飞;谷灵康;: "基于粒子群进化的输电网络WSN节点定位算法", 沈阳工业大学学报, no. 05, 29 August 2018 (2018-08-29) * |
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