KR102248003B1 - Methods and apparatuses for dynamic sink relocation in wireless sensor network - Google Patents

Abstract

The present invention relates to a dynamic sink rearrangement method using fuzzy logic on a wireless sensor network and an apparatus thereof. According to one embodiment of the present invention, the dynamic sink rearrangement method using fuzzy logic on a wireless sensor network includes the following steps of: forming a cluster on a wireless sensor network and selecting a cluster head (CH) from the formed cluster; searching for a cluster head having the highest residual energy and a sensor node existing in a first area around a current sink; calculating a sink rearrangement probability of each second area based on average residual energy, with respect to the second area around the selected cluster head; and rearranging the current sink in a direction to a cluster head of an area where the calculated sink rearrangement probability is the highest.

Description

A method and apparatus for dynamic sync relocation using fuzzy logic in a wireless sensor network {METHODS AND APPARATUSES FOR DYNAMIC SINK RELOCATION IN WIRELESS SENSOR NETWORK}

The present invention relates to a method and apparatus for dynamic sync relocation using fuzzy logic in a wireless sensor network.

The wireless sensor network enables efficient data collection and transmission using a sink in an Internet of Things (IoT) environment. In this case, if a fixed sink is used, there is a problem that network performance cannot be maximized due to excessive energy consumption of the sink.

To solve this problem, a number of algorithms using more energy efficient sink relocation have been proposed. However, since the power of the sensor node of the wireless sensor network is limited, power efficiency in the process of relocating the sink is an important problem of the wireless sensor network.

Embodiments of the present invention are intended to provide a method and apparatus for dynamic sync relocation using fuzzy logic in a wireless sensor network to minimize communication overhead required for dynamic sync relocation and to relocate dynamic sync without data packet loss.

However, the problem to be solved of the present invention is not limited thereto, and may be variously expanded even in an environment within a range not departing from the spirit and scope of the present invention.

According to an embodiment of the present invention, there is provided a dynamic sync relocation method performed by a dynamic sync relocation apparatus, comprising: forming a cluster in a wireless sensor network and selecting a cluster head (CH) from the formed cluster; Searching for a sensor node present in a first region centered on a current sink and a cluster head having the highest residual energy; Calculating a sync relocation probability of each second region based on an average residual energy for a second region centered on the selected cluster head; And relocating the current sink in the direction of the cluster head of the region in which the calculated sink relocation probability is the highest. In a wireless sensor network, a dynamic sync relocation method using fuzzy logic may be provided.

In the selecting of the cluster head, a cluster head that minimizes energy consumption may be selected using a gravity search algorithm (GSA) and a fuzzy logic controller.

A cluster may be formed by dividing a plurality of parameters according to the fuzzy logic controller.

The plurality of parameters includes a first parameter obtained by dividing the number of clusters by the size of the cluster, and the first parameter may be used to minimize the number of clusters.

The plurality of parameters includes a second parameter obtained by dividing the sum of Euclidean distances between the sensor node and the cluster by the minimum Euclidean distance between the sensor node and the cluster, and the second parameter can be used to maximize communication quality. have.

The plurality of parameters includes a third parameter obtained by dividing the sum of the residual energy of the sensor nodes by the sum of the residual energy of the cluster head, and the third parameter is the total energy of all sensor nodes versus the total of all cluster heads. It can be used to calculate the percentage of energy.

The plurality of parameters includes a fourth parameter obtained by dividing the sum of Euclidean distances between the sensor node and the cluster by the number of sensor nodes belonging to the cluster, and the fourth parameter is a maximum average between the sensor node and the associated cluster head. Can be used to calculate distance.

According to the fuzzy rule of the fuzzy logic controller, which includes a value obtained by substituting the highest value among the plurality of parameters and multiplying the plurality of parameters to be used over time, a cluster is formed and the highest residual energy A sensor node having a can be selected as the cluster head.

The radius of the second area may be less than the radius of the first area.

The average residual energy of each of the first areas and the residual energy of an external node outside the first area and existing in the second area are calculated, and the calculated average residual energy of each of the first areas and the residual energy of the external node From, the sync relocation probability of the second region may be calculated.

On the other hand, according to another embodiment of the present invention, a communication module for communicating with a sensor node in a wireless sensor network; A memory storing one or more programs; And a processor executing the stored one or more programs, wherein the processor forms a cluster in the wireless sensor network, selects a cluster head (CH) from the formed cluster, A sensor node existing in an area and a cluster head having the highest residual energy are searched, and for a second area centered on the selected cluster head, the sync relocation probability of each second area is calculated based on the average residual energy. , A dynamic sync relocation apparatus using fuzzy logic in a wireless sensor network for relocating a current sink in a direction of a cluster head of an area in which the calculated sink relocation probability is the highest may be provided.

The processor may select a cluster head that minimizes energy consumption by using a gravity search algorithm (GSA) and a fuzzy logic controller.

A cluster may be formed by dividing a plurality of parameters according to the fuzzy logic controller.

The plurality of parameters includes a first parameter obtained by dividing the number of clusters by the size of the cluster, and the first parameter may be used to minimize the number of clusters.

The plurality of parameters includes a second parameter obtained by dividing the sum of Euclidean distances between the sensor node and the cluster by the minimum Euclidean distance between the sensor node and the cluster, and the second parameter can be used to maximize communication quality. have.

The plurality of parameters includes a third parameter obtained by dividing the sum of the residual energy of the sensor nodes by the sum of the residual energy of the cluster head, and the third parameter is the total energy of all sensor nodes versus the total of all cluster heads. It can be used to calculate the percentage of energy.

The plurality of parameters includes a fourth parameter obtained by dividing the sum of Euclidean distances between the sensor node and the cluster by the number of sensor nodes belonging to the cluster, and the fourth parameter is a maximum average between the sensor node and the associated cluster head. Can be used to calculate distance.

According to the fuzzy rule of the fuzzy logic controller, which includes a value obtained by substituting the highest value among the plurality of parameters and multiplying the plurality of parameters to be used over time, a cluster is formed and the highest residual energy A sensor node having a can be selected as the cluster head.

The radius of the second area may be less than the radius of the first area.

The average residual energy of each of the first areas and the residual energy of an external node outside the first area and existing in the second area are calculated, and the calculated average residual energy of each of the first areas and the residual energy of the external node From, the sync relocation probability of the second region may be calculated.

Meanwhile, according to another embodiment of the present invention, as a non-transitory computer-readable storage medium including one or more programs executable by a processor, when the one or more programs are executed by the processor, the processor causes: wireless sensor A cluster is formed in the network, a cluster head (CH) is selected from the formed cluster, a sensor node existing in the first region centered on the current sink and a cluster head having the highest residual energy are searched, and the selected For the second region centered on the cluster head, the sink relocation probability of each second region is calculated based on the average residual energy, and the current sink is relocated in the direction of the cluster head of the region with the highest sync relocation probability. A non-transitory computer-readable storage medium may be provided that includes instructions for doing so.

The disclosed technology can have the following effects. However, since it does not mean that a specific embodiment should include all of the following effects or only the following effects, it should not be understood that the scope of the rights of the disclosed technology is limited thereby.

Embodiments of the present invention can minimize communication overhead required for dynamic sync relocation and relocate dynamic sync without data packet loss.

Embodiments of the present invention can provide superior effects in terms of energy efficiency, network lifetime, and throughput compared to a conventional sink relocation algorithm.

Embodiments of the present invention can be used in various application fields requiring high communication performance regardless of space constraints.

1 is a block diagram showing the configuration of a dynamic sync relocation apparatus using fuzzy logic in a wireless sensor network according to an embodiment of the present invention.
2 is a diagram illustrating a fuzzy rule of a fuzzy logic controller according to an embodiment of the present invention.
3 is a diagram illustrating operations of a sync search step and a cluster search step according to an embodiment of the present invention.
4 is a diagram illustrating a dynamic sync relocation method according to an embodiment of the present invention in the form of an algorithm.
5 is a flowchart illustrating a dynamic sync relocation method using fuzzy logic in a wireless sensor network according to an embodiment of the present invention.
6 is a diagram listing parameters of a simulation environment set in an embodiment of the present invention.
7 to 9 are graphs comparing energy consumption according to an embodiment of the present invention and a prior art while the number of sensor nodes is changed.
10 to 12 are graphs comparing the number of surviving nodes by time according to an embodiment of the present invention and the prior art.
13 to 15 are graphs comparing packet throughput according to an embodiment of the present invention and prior art.

Since the present invention can apply various transformations and have various embodiments, specific embodiments are illustrated in the drawings and will be described in detail in the detailed description. However, this is not intended to limit the present invention to a specific embodiment, it can be understood to include all conversions, equivalents, or substitutes included in the technical spirit and scope of the present invention. In describing the present invention, when it is determined that a detailed description of a related known technology may obscure the subject matter of the present invention, a detailed description thereof will be omitted.

Terms such as first and second may be used to describe various elements, but the elements are not limited by the terms. The terms are used only for the purpose of distinguishing one component from other components.

The terms used in the present invention are used only to describe specific embodiments, and are not intended to limit the present invention. The terms used in the present invention have been selected from general terms that are currently widely used as possible while considering functions in the present invention, but this may vary according to the intention of a technician working in the art, precedent, or the emergence of new technologies. In addition, in certain cases, there are terms arbitrarily selected by the applicant, and in this case, the meaning of the terms will be described in detail in the description of the corresponding invention. Therefore, the terms used in the present invention should be defined based on the meaning of the term and the overall contents of the present invention, not a simple name of the term.

Singular expressions include plural expressions unless the context clearly indicates otherwise. In the present invention, terms such as "comprise" or "have" are intended to designate the presence of features, numbers, steps, actions, components, parts, or combinations thereof described in the specification, but one or more other features. It is to be understood that the presence or addition of elements or numbers, steps, actions, components, parts, or combinations thereof does not preclude in advance.

Hereinafter, embodiments of the present invention will be described in detail with reference to the accompanying drawings, and in the description with reference to the accompanying drawings, the same or corresponding components are assigned the same reference numbers, and redundant descriptions thereof will be omitted. do.

1 is a block diagram showing the configuration of a dynamic sync relocation apparatus using fuzzy logic in a wireless sensor network according to an embodiment of the present invention.

As shown in FIG. 1, a dynamic sync relocation apparatus 100 using a fuzzy logic in a wireless sensor network according to an embodiment of the present invention includes a communication module 110, a memory 120, and a processor 130. .

Includes. However, not all of the illustrated components are essential components. The dynamic sync relocation apparatus 100 may be implemented by more components than the illustrated components, and the dynamic sync relocation apparatus 100 may be implemented by fewer components than the illustrated components.

Hereinafter, a detailed configuration and operation of each component of the dynamic sync relocation apparatus 100 of FIG. 1 will be described.

The communication module 110 communicates with a sensor node in a wireless sensor network.

The memory 120 stores one or more programs.

The processor executes one or more programs stored in the memory 120. The processor 130 forms a cluster using a Gravitational Search Algorithm (GSA) and a fuzzy logic controller in a wireless sensor network, and selects a cluster head (CH) from the formed cluster. And, the sensor node existing in the first region centered on the current sink and the cluster head having the highest residual energy are searched, and for the second region centering on the selected cluster head, the sync relocation of each second region The probability is calculated based on the average residual energy, and the current sink is rearranged in the direction of the cluster head of the region in which the calculated sink rearrangement probability is the highest.

According to embodiments, a gravity search algorithm may be used to select a cluster head that minimizes energy consumption.

According to embodiments, a cluster may be formed by dividing a plurality of parameters according to a fuzzy logic controller.

According to embodiments, the plurality of parameters includes a first parameter obtained by dividing the number of clusters by the size of the cluster, and the first parameter may be used to minimize the number of clusters.

According to embodiments, the plurality of parameters includes a second parameter obtained by dividing the sum of the Euclidean distances between the sensor node and the cluster by the minimum Euclidean distance between the sensor node and the cluster, and the second parameter maximizes communication quality. Can be used to

According to embodiments, the plurality of parameters includes a third parameter obtained by dividing the sum of the residual energy of the sensor nodes by the sum of the residual energy of the cluster head, and the third parameter is the total energy of all sensor nodes versus all clusters. It can be used to calculate the percentage of the total energy of the head.

According to embodiments, the plurality of parameters includes a fourth parameter obtained by dividing the sum of Euclidean distances between the sensor node and the cluster by the number of sensor nodes belonging to the cluster, and the fourth parameter is between the sensor node and the associated cluster head. Can be used to calculate the maximum average distance of.

According to embodiments, a cluster is formed according to a fuzzy rule of a fuzzy logic controller including a value obtained by substituting the highest value among a plurality of parameters and multiplying a plurality of parameters to be used over time. The sensor node with the highest residual energy can be selected as the cluster head.

According to embodiments, the radius of the second area may be less than the radius of the first area.

According to embodiments, the average residual energy of each of the first regions and the residual energy of the external nodes that are outside the first region and exist in the second region are calculated, and the calculated average residual energy of each of the first regions and the external nodes The sync relocation probability of the second region may be calculated from the residual energy.

Meanwhile, the dynamic sync relocation apparatus 100 according to an embodiment of the present invention may minimize communication overhead required for sync relocation and relocate the sync without data packet loss by using the dynamic sync relocation method.

The dynamic sink relocation method using fuzzy logic consists of two steps. In the first step, the search step, the cluster is reconfigured including the cluster head, parameter data is collected in real time, and in the second step, a new sink location is selected based on the collected data, and the sink is relocated to the selected location. The dynamic sync relocation apparatus 100 according to an embodiment of the present invention reconfigures a cluster including a cluster head for energy efficiency through continuous repetition of the dynamic sync relocation method. In this case, the improved GSA is used with a fuzzy logic controller.

On the other hand, it will be described from the search stage.

는 노드_p에서 노드_q로 N 비트의 데이터를 전송할 때 필요한 에너지를 나타낸다. Looking at the energy model, first, in an embodiment of the present invention, communication is performed based on an energy model typically used in a wireless sensor network. At this time, most of the energy of the sensor node is consumed in the process of transmitting and receiving data. The energy required when each node transmits N-bit data is as shown in [Equation 1] below.

Denotes energy required when transmitting N-bit data from node_p to node_q.

는 아래의 [수학식 2]와 같다. In addition, energy for receiving N bits of data at each node

Is as shown in [Equation 2] below.

및

팩터이다. 소스 노드로부터 거리 d에 위치한 목적지까지 N 비트를 전송하기 위한 총 에너지는 아래의 [수학식 3]과 같다. However, the energy consumed by a node for data transmission depends on the distance to the target node. The energy consumption for short and long distance data transmission is respectively

And

It's a factor. The total energy for transmitting N bits from the source node to the destination located at the distance d is as shown in [Equation 3] below.

Next, clustering will be described.

When the cluster is reconfigured, the cluster head (CH) is selected before the search phase, and is selected using an improved GSA based on a fuzzy logic controller. The GSA is used to determine an appropriate number of cluster heads that minimize energy consumption, and is formed based on the following [Equation 4] when the dynamic sync relocation device 100 forms a cluster after the cluster head is selected. .

Here, s is the number of clusters and c is the cluster size. In order to maximize the communication quality in each cluster, it is necessary to decide to minimize the sum of the transmission distances between sensor nodes in the cluster. Therefore, it is obtained based on the following [Equation 5].

는 센서 노드

와 CH

사이의 유클리드 거리이다. [수학식 4]로 나타난

의 목적은 CH의 수를 최소화하는 것이며, [수학식 5]로 나타난

는 통신 품질을 최대화하는 것이다. 동적 싱크 재배치 장치(100)는 각 클러스터에서 노드의 최대 잔여 에너지를 기반으로 다음 [수학식 6] 및 [수학식 7]을 통하여 CH를 선정한다.here

The sensor node

And CH

Is the Euclidean distance between. Represented by [Equation 4]

The purpose of is to minimize the number of CH, represented by [Equation 5]

Is to maximize communication quality. The dynamic sync relocation apparatus 100 selects CH through the following [Equation 6] and [Equation 7] based on the maximum residual energy of a node in each cluster.

및

은 각각

및

의 나머지 에너지이다. 또한

은

에 속하는 센서 노드의 수이다. [수학식 6]으로 나타난

은 모든 센서 노드의 총 에너지 대 모든 CH의 에너지의 비율을 계산하기 위한 것이며, [수학식 7]로 나타난

는 노드와 관련 CH 사이의 최대 평균 거리에 대한 것이다. 동적 싱크 재배치 장치(100)는 개선된 GSA를 통해 위의 [수학식 4] 내지 [수학식 7]로 나타난 4가지의 식을 기반으로 얻은 각 매개 변수를 퍼지 로직 컨트롤러에 따라 나누어 클러스터를 형성하고 CH를 선택한다. Where T is the total number of sensor nodes,

And

Is each

And

Is the rest of the energy. Also

silver

This is the number of sensor nodes belonging to. Represented by [Equation 6]

Is for calculating the ratio of the total energy of all sensor nodes to the energy of all CHs, and is represented by [Equation 7].

Is for the maximum average distance between the node and the associated CH. The dynamic sync relocation device 100 divides each parameter obtained based on the four equations represented by [Equation 4] to [Equation 7] above through the improved GSA according to the fuzzy logic controller to form a cluster. Select CH.

2 is a diagram illustrating a fuzzy rule of a fuzzy logic controller according to an embodiment of the present invention.

In addition, in [Equation 8] above, ITER is obtained by substituting the highest Max_t value among the four parameters obtained using the improved GSA. Here, Max_t represents the maximum number of iterations repeated to determine the _{four parameters, h 1} , h ₂ , h ₃ and h _{4 in GSA.} Therefore, the lower the value of ITER, the shorter the time required to obtain CH using the fuzzy logic controller.

In [Equation 9], IMP(t) is used over time by multiplying the four parameters of GSA. According to the rule of the fuzzy logic controller shown in FIG. 2, a new cluster is formed based on a(t), and a cluster member having the largest residual energy is selected as a CH.

3 is a diagram illustrating operations of a sync search step and a cluster search step according to an embodiment of the present invention.

Next, the search step for sink relocation begins. The search phase consists of two steps. In the first search step, the dynamic sink relocation apparatus 100 searches for a sensor node 330 in an area and a cluster head having the largest residual energy around the current sink 310. This is called the'sync search step'. In the second step, the dynamic sync relocation apparatus 100 performs another circular search with a slightly smaller radius around the selected cluster head 320, which is referred to as a'CH search step'. This two-step search method maximizes energy efficiency while minimizing the sink relocation distance by finding a node at a location where the sink 310 is to be relocated.

For example, as shown in FIG. 3, in the case of the'sync search step', a circular search range having a radius of 40 m of the first area 311 is set as the center of the sync, and the radius is the same as the communication range of the sync.

Next, the searched circle is divided into 8 areas, and one CH is selected for each area. The residual energy of all nodes in the domain is collected and the average is obtained using the following [Equation 10].

,

및 b는 각각 영역 j인 sector_j의 평균 잔여 에너지, 영역 j인 sector_j의 센서 노드 i인 node_i의 잔여 에너지 및 영역 j인 sector_j의 노드 수이다. 그런 다음 싱크 검색 범위를 중심으로 선택한 CH를 사용하여 CH 검색 범위에 대해 제2 영역(321)인 반경 20m의 원이 형성된다. CH 검색 범위에서 나머지 노드를 제외한 노드의 잔여 에너지는 다음 [수학식 11]에 따라 구해진다.here

,

And b is an average residual energy of sector_j, which is an area j, a residual energy of node_i, which is a sensor node i, of sector_j, which is an area j, and the number of nodes of sector_j, which is an area j. Then, a circle having a radius of 20 m, which is the second region 321 for the CH search range, is formed using the CH selected as the center of the sync search range. The residual energy of the node excluding the remaining nodes in the CH search range is obtained according to the following [Equation 11].

는 N 비트 데이터를 노드 t인 node_t에서 노드 q인 node_q로 전송하는 데 필요한 에너지다. 각 영역의 평균 잔여 에너지 및 외부 노드의 잔여 에너지도 계산된다. 그런 다음 싱크 재배치에 대한 각 영역의 확률

는 다음 [수학식 12]와 같이 평균 잔여 에너지를 사용하여 계산된다.here

Is the energy required to transmit N-bit data from node_t, node t, to node_q, node q. The average residual energy of each region and the residual energy of external nodes are also calculated. Then the probability of each region for sink relocation

Is calculated using the average residual energy as shown in [Equation 12] below.

Next, the selection step will be described.

가 계산되고, 동적 싱크 재배치 장치(100)는 확률

가 최고인 영역의 클러스터 헤드를 선택한다. 싱크는 확률

가 가장 높은 영역의 클러스터 헤드 방향으로 이동한다. 또한, 통신 과정에서 일부 CH의 에너지가 특정 임계 값 아래로 떨어지면 싱크는 다시 본 발명의 일실시예에 따른 동적 싱크 재배치 방법의 반복을 통해 새 위치로 재배치될 수 있다.At the end of the search phase, the probability of each region for sink relocation

Is calculated, and the dynamic sync relocation device 100 has a probability

Select the cluster head of the region where is the highest. Sinking odds

Moves in the direction of the cluster head in the highest area. In addition, when the energy of some CHs falls below a specific threshold value during the communication process, the sink may be relocated to a new location through repetition of the dynamic sink relocation method according to an embodiment of the present invention.

4 is a diagram illustrating a dynamic sync relocation method according to an embodiment of the present invention in the form of an algorithm.

The procedure of the dynamic sync relocation method according to an embodiment of the present invention is shown in FIG. 4.

As described above, the dynamic sync relocation method according to an embodiment of the present invention relates to an efficient sync relocation algorithm that considers dynamic sync relocation and node clustering together to minimize communication sync overhead and maximize network life.

5 is a flowchart illustrating a dynamic sync relocation method using fuzzy logic in a wireless sensor network according to an embodiment of the present invention.

An embodiment of the present invention relates to a dynamic sink relocation algorithm using fuzzy logic to solve a sensor node power limitation in a process of moving a sink in a wireless sensor network (WSN).

In step S101, the dynamic sync relocation apparatus 100 forms a cluster using a gravity search algorithm (GSA) and a fuzzy logic controller in a wireless sensor network.

In step S102, the dynamic sync relocation apparatus 100 selects a cluster head (CH) from the formed cluster.

In step S103, the dynamic sync relocation apparatus 100 searches for a sensor node existing in the first region 311 centered on the current sync and a cluster head having the highest residual energy.

In step S104, the dynamic sync relocation apparatus 100 calculates the sync relocation probability of each second region 321 with respect to the second region 321 centered on the selected cluster head based on the average residual energy. .

In step S105, the dynamic sync relocation apparatus 100 relocates the current sink in the direction of the cluster head of the region in which the calculated sync relocation probability is the highest.

6 is a diagram listing parameters of a simulation environment set in an embodiment of the present invention.

In order to verify the results of an embodiment of the present invention, the performance of the dynamic sync relocation method was evaluated by computer simulation using a wireless sensor network having a maximum of 200 sensor nodes randomly located in a 1000m×1000m area. 6 lists parameters of a simulation environment set in an embodiment of the present invention. The parameters include N representing the number of nodes, L representing the length of the network, W representing the width of the network, and initial energy of each node. Ei representing each node, Etrans representing Energy for transmitting one bit, Erec representing Energy for receiving one bit, and Data aggregation energy. Eagg representing the aggregation energy) and Efs representing the energy of the free space model amplifier are included.

7 to 9 are graphs comparing energy consumption according to an embodiment of the present invention and a prior art while the number of sensor nodes is changed.

In order to investigate the relative effect of the dynamic sync rearrangement method according to an embodiment of the present invention, the prior art LEACH (Low-Energy Adaptive Clustering Hierarchy), random walk, rendezvous, EASR (Efficient and Accurate Scene). Text Detector) and QHBM (Queen Honey Bee Migration) algorithm. LEACH is one of the most widely used algorithms that use static sinks, and the random walk algorithm randomly moves the sink to collect data from nodes.

First, the energy consumed by the sensor per hour is the most important factor in determining the network lifetime when compared by algorithm. Then, the lifetime and packet throughput of the wireless sensor network improved by the algorithm were compared.

7 to 9 show the total energy dissipated of the sensor nodes over time when the number of sensor nodes is 100 (FIG. 7), 150 (FIG. 8), and 200 (FIG. 9). Show. It can be seen that the dynamic sync relocation method according to an embodiment of the present invention continuously consumes less energy than other conventional algorithms. Therefore, more residual energy remains in the sensor node, extending the life of the network. According to the simulation results, it can be seen that the dynamic sync relocation method according to an embodiment of the present invention is advantageous for communication between sensor nodes distributed at high density in a limited space. The dynamic sync relocation method according to an embodiment of the present invention can also be effectively utilized in a wide range of wireless sensor networks. In addition, the dynamic sync relocation method according to an embodiment of the present invention can be used in various application fields requiring high communication performance regardless of space constraints.

10 to 12 are graphs comparing the number of surviving nodes by time according to an embodiment of the present invention and the prior art.

10 to 12 are graphs comparing the number of life time of sensor nodes according to algorithms over time. The surviving sensor nodes gradually deplete the energy required for operation and communication, which decreases over time. The longer the network runs, the more surviving nodes appear in the graph. By relocating the sink, the energy of the node can be consumed more evenly, so the number of surviving sensor nodes per hour is the highest.

13 to 15 are graphs comparing packet throughput according to an embodiment of the present invention and prior art.

13 to 15 show packet throughput according to an embodiment of the present invention and prior art over time when the number of sensor nodes is 100 (FIG. 13), 150 (FIG. 14), and 200 (FIG. 15) This is a comparison of (Throughput). It can be seen that the dynamic sync relocation method according to an embodiment of the present invention can always process more packets per hour. This makes communication smooth and continuous by sync relocation, and consequently shortens the communication time with the node. This also reduces energy costs and, in turn, extends the life of the wireless sensor network.

Meanwhile, as a non-transitory computer-readable storage medium including at least one program executable by a processor, when the at least one program is executed by the processor, the processor causes: a gravity search algorithm (GSA) in a wireless sensor network. , Gravitational Search Algorithm) and a fuzzy logic controller to form a cluster, select a cluster head (CH) from the formed cluster, and in the first region 311 centered on the current sink Search for an existing sensor node and a cluster head having the highest residual energy, and for a second area centered on the selected cluster head, a sink relocation probability of each second area is calculated based on an average residual energy, and the A non-transitory computer-readable storage medium including instructions for relocating a current sink in a direction of a cluster head of an area in which the calculated sink relocation probability is highest may be provided.

Meanwhile, according to an embodiment of the present invention, the various embodiments described above are implemented as software including instructions stored in a machine-readable storage media (machine-readable storage media). Can be. The device is a device capable of calling a stored command from a storage medium and operating according to the called command, and may include an electronic device (eg, electronic device A) according to the disclosed embodiments. When an instruction is executed by a processor, the processor may perform a function corresponding to the instruction directly or by using other components under the control of the processor. Instructions may include code generated or executed by a compiler or interpreter. A storage medium that can be read by a device may be provided in the form of a non-transitory storage medium. Here,'non-transient' means that the storage medium does not contain a signal and is tangible, but does not distinguish between semi-permanent or temporary storage of data in the storage medium.

In addition, according to an embodiment of the present invention, the method according to various embodiments described above may be provided by being included in a computer program product. Computer program products can be traded between sellers and buyers as commodities. The computer program product may be distributed online in the form of a device-readable storage medium (eg, compact disc read only memory (CD-ROM)) or through an application store (eg, Play StoreTM). In the case of online distribution, at least some of the computer program products may be temporarily stored or temporarily generated in a storage medium such as a server of a manufacturer, a server of an application store, or a memory of a relay server.

In addition, according to an embodiment of the present invention, the various embodiments described above are in a recording medium that can be read by a computer or a similar device using software, hardware, or a combination thereof. Can be implemented in In some cases, the embodiments described herein may be implemented by the processor itself. According to software implementation, embodiments such as procedures and functions described herein may be implemented as separate software modules. Each of the software modules may perform one or more functions and operations described herein.

Meanwhile, computer instructions for performing a processing operation of a device according to the various embodiments described above may be stored in a non-transitory computer-readable medium. When the computer instructions stored in the non-transitory computer-readable medium are executed by the processor of the specific device, the specific device causes the specific device to perform processing operations in the device according to the various embodiments described above. The non-transitory computer-readable medium refers to a medium that stores data semi-permanently and can be read by a device, rather than a medium that stores data for a short moment, such as registers, caches, and memory. Specific examples of non-transitory computer-readable media may include CD, DVD, hard disk, Blu-ray disk, USB, memory card, ROM, and the like.

In addition, each of the constituent elements (eg, a module or a program) according to the various embodiments described above may be composed of a singular or a plurality of entities, and some sub-elements of the above-described sub-elements are omitted, or Sub-elements may be further included in various embodiments. Alternatively or additionally, some constituent elements (eg, a module or a program) may be integrated into a single entity, and functions performed by each corresponding constituent element prior to the consolidation may be performed identically or similarly. Operations performed by modules, programs, or other components according to various embodiments are sequentially, parallel, repetitively or heuristically executed, at least some operations are executed in a different order, omitted, or other operations are added. Can be.

In the above, preferred embodiments of the present invention have been illustrated and described, but the present invention is not limited to the specific embodiments described above, and is not departing from the gist of the present invention claimed in the claims. Various modifications are possible by those skilled in the art of course, and these modifications should not be understood individually from the technical idea or perspective of the present invention.

100: dynamic sink relocation device
110: communication module
120: memory
130: processor
310: sink
311: first area, sync search range
320: cluster head
321: second area, cluster head search range
330: sensor node

Claims (21)

In the dynamic sync relocation method performed by the dynamic sync relocation device,
Forming a cluster in a wireless sensor network and selecting a cluster head (CH) from the formed cluster;
Searching for a sensor node present in a first region centered on a current sink and a cluster head having the highest residual energy;
Calculating a sync relocation probability of each second region based on an average residual energy for a second region centered on the selected cluster head; And
Relocating the current sink in the direction of the cluster head of the region in which the calculated sink relocation probability is the highest,
A cluster is formed by dividing a plurality of parameters according to the fuzzy logic controller,
The plurality of parameters includes a second parameter obtained by dividing the sum of Euclidean distances between the sensor node and the cluster by the minimum Euclidean distance between the sensor node and the cluster, and the second parameter is used to maximize communication quality. , Dynamic sink relocation method using fuzzy logic in wireless sensor network. The method of claim 1,
Selecting the cluster head,
A dynamic sync relocation method using fuzzy logic in a wireless sensor network to select a cluster head that minimizes energy consumption by using a gravity search algorithm (GSA) and a fuzzy logic controller. delete The method of claim 1,
The plurality of parameters,
And a first parameter obtained by dividing the number of clusters by the size of the cluster, wherein the first parameter is used to minimize the number of clusters. delete The method of claim 1,
The plurality of parameters,
Includes a third parameter obtained by dividing the sum of the residual energy of the sensor nodes by the sum of the residual energy of the cluster head, and the third parameter is used to calculate the ratio of the total energy of all sensor nodes to the total energy of all cluster heads. The dynamic sink relocation method using fuzzy logic in a wireless sensor network. The method of claim 1,
The plurality of parameters,
A fourth parameter obtained by dividing the sum of the Euclidean distances between the sensor node and the cluster by the number of sensor nodes belonging to the cluster, wherein the fourth parameter is used to calculate a maximum average distance between the sensor node and the associated cluster head, Dynamic sink relocation method using fuzzy logic in wireless sensor network. The method of claim 1,
According to the fuzzy rule of the fuzzy logic controller, which includes a value obtained by substituting the highest value among the plurality of parameters and multiplying the plurality of parameters to be used over time, a cluster is formed and the highest residual energy A dynamic sync relocation method using fuzzy logic in a wireless sensor network, in which a sensor node having a is selected as a cluster head. The method of claim 1,
The radius of the second area is less than the radius of the first area, dynamic sync relocation method using fuzzy logic in a wireless sensor network. The method of claim 1,
The average residual energy of each of the first areas and the residual energy of an external node outside the first area and existing in the second area are calculated, and the calculated average residual energy of each of the first areas and the residual energy of the external node A dynamic sync relocation method using fuzzy logic in a wireless sensor network, wherein the sync relocation probability of the second region is calculated from. A communication module for communicating with a sensor node in a wireless sensor network;
A memory storing one or more programs; And
And a processor that executes the stored one or more programs,
The processor,
Form a cluster in the wireless sensor network, select a cluster head (CH, Cluster Head) from the formed cluster,
A sensor node present in the first region centered on the current sink and a cluster head having the highest residual energy are searched,
For a second region centered on the selected cluster head, a sync relocation probability of each second region is calculated based on an average residual energy,
Relocating the current sink in the direction of the cluster head of the region in which the calculated sink relocation probability is the highest,
A cluster is formed by dividing a plurality of parameters according to the fuzzy logic controller,
The plurality of parameters includes a second parameter obtained by dividing the sum of Euclidean distances between the sensor node and the cluster by the minimum Euclidean distance between the sensor node and the cluster, and the second parameter is used to maximize communication quality. , Dynamic sink relocation device using fuzzy logic in wireless sensor network. The method of claim 11,
The processor,
A dynamic sync relocation device using fuzzy logic in a wireless sensor network that selects a cluster head that minimizes energy consumption by using a gravity search algorithm (GSA) and a fuzzy logic controller. delete The method of claim 11,
The plurality of parameters,
A dynamic sync relocation apparatus using fuzzy logic in a wireless sensor network, comprising: a first parameter obtained by dividing the number of clusters by the size of the cluster, wherein the first parameter is used to minimize the number of clusters. delete The method of claim 11,
The plurality of parameters,
Includes a third parameter obtained by dividing the sum of the residual energy of the sensor nodes by the sum of the residual energy of the cluster head, and the third parameter is used to calculate the ratio of the total energy of all sensor nodes to the total energy of all cluster heads. A dynamic sink relocation device using fuzzy logic in a wireless sensor network. The method of claim 11,
The plurality of parameters,
A fourth parameter obtained by dividing the sum of the Euclidean distances between the sensor node and the cluster by the number of sensor nodes belonging to the cluster, wherein the fourth parameter is used to calculate a maximum average distance between the sensor node and the associated cluster head, Dynamic sink relocation device using fuzzy logic in wireless sensor network. The method of claim 11,
According to the fuzzy rule of the fuzzy logic controller, which includes a value obtained by substituting the highest value among the plurality of parameters and multiplying the plurality of parameters to be used over time, a cluster is formed and the highest residual energy A dynamic sink relocation apparatus using fuzzy logic in a wireless sensor network, in which a sensor node having a is selected as a cluster head. The method of claim 11,
A dynamic sync relocation apparatus using fuzzy logic in a wireless sensor network, wherein the radius of the second area is less than the radius of the first area. The method of claim 11,
The average residual energy of each of the first areas and the residual energy of an external node outside the first area and existing in the second area are calculated, and the calculated average residual energy of each of the first areas and the residual energy of the external node A dynamic sync relocation apparatus using fuzzy logic in a wireless sensor network, from which the sync relocation probability of the second region is calculated from. A non-transitory computer-readable storage medium comprising one or more programs executable by a processor, wherein the one or more programs, when executed by the processor, cause the processor to:
Form a cluster in the wireless sensor network, select a cluster head (CH, Cluster Head) from the formed cluster,
A sensor node present in the first region centered on the current sink and a cluster head having the highest residual energy are searched,
For a second region centered on the selected cluster head, a sync relocation probability of each second region is calculated based on an average residual energy,
Relocating the current sink in the direction of the cluster head of the region in which the calculated sink relocation probability is the highest,
A cluster is formed by dividing a plurality of parameters according to the fuzzy logic controller,
The plurality of parameters includes a second parameter obtained by dividing a sum of Euclidean distances between a sensor node and a cluster by a minimum Euclidean distance between a sensor node and a cluster, and the second parameter is used to maximize communication quality. A non-transitory computer-readable storage medium containing instructions to do so.

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