KR20150005355A - Method for analysis of energy efficient cluster ratio and the hierarchical wireless sensor network system the method applied thereto - Google Patents

Abstract

The present invention relates to a method of calculating a cluster ratio for energy efficiency and a hierarchical sensor network system adopting the method and, more specifically, to the method of calculating a cluster ratio for energy efficiency which minimizes an overall hop count of a network system by analyzing benefits and losses between minimization of a system hop count in the hierarchical sensor network based on a multi-hop to one-hop transmission structure and maximization of a packet reception ratio (PRR) between nodes and calculating an optimal cluster ratio by considering both the minimization and maximization elements, and improves energy efficiency by reducing a network packet transmission cost and a retransmission overhead between nodes, and the hierarchical sensor network system adopting the method. The present invention relates to a method of calculating a cluster ratio of a hierarchical sensor network system based on a multi-hop to one-hop transmission structure and provides a method of calculating a cluster ratio for energy efficiency, comprising: obtaining an overall hop count of the network system; obtaining the PRR between nodes in a cluster; and calculating the cluster ratio by considering the minimization of the network system hop count and the maximization of the PRR.

Description

TECHNICAL FIELD The present invention relates to a method of calculating a cluster ratio for energy efficiency and a hierarchical sensor network system to which the method is applied,

The present invention relates to a method for calculating a cluster ratio for energy efficiency and a hierarchical sensor network system to which the method is applied. More particularly, the present invention relates to a hierarchical sensor network system based on a multi-hop to one-hop transmission structure And the maximum packet-to-node ratio (PRR) in a hierarchical sensor network, and the optimal cluster ratio considering both factors A cluster rate calculation method capable of minimizing the number of hops in a network system, reducing a network packet transmission cost and an inter-node retransmission overhead to improve energy efficiency, and a hierarchical sensor network system to which the method is applied.

Wireless sensor networks can be networked in a centralized or distributed manner on an ad hoc basis without building a backbone network or an infrastructure. Sensor networks utilize the sensing function of sensor devices and are used in areas where dangerous or impossible data collection, such as environmental detection, intrusion monitoring or battlefield, is possible. Sensor nodes, which are basic components in sensor networks, face various constraints such as limited battery capacity, CPU efficiency and complex deployment environment. These applications usually deploy hundreds or thousands of sensor devices, and they are installed in difficult-to-reach environments, so it is almost impossible to replace the device's battery. Therefore, limited battery resources are the most important constraints that determine the lifetime of the sensor network, and studies for improving the energy efficiency in the PHY layer, the MAC layer, and the routing layer are actively conducted.

In terms of network architecture, wireless sensor networks are broadly classified into a flat structure and a hierarchical structure. In a planar structure, the responsibilities and responsibilities of each sensor node are equivalent, and they communicate directly with the sink node or through multi-hop communication through the relay of neighboring nodes. In contrast, in the hierarchical structure, sensor nodes gather to form multiple clusters, and each cluster head has a cluster head (CH) and a plurality of cluster members (CM).

The clustering technique can use the hierarchical structure to efficiently reduce the power consumption for RF communication and extend the network lifetime. In the cluster, the CM sends the sensed data to the corresponding CH, and the CH transmits the collected data to the external sink through a one-hop or a multi-hop method. In addition, many application examples of sensor networks have a lot of redundancy among data collected by sensor nodes such as temperature measurement, humidity, pressure monitoring, and so on, so that CH reduces the data redundancy by processing data collected from CM. Therefore, a cluster-based sensor network with a hierarchical structure uses the data aggregation function of the CH to reduce the communication overhead in which each sensor node communicates with the sink node and the number of transmission packets in the system, Can be greatly reduced.

However, the system performance improvement obtained by building a cluster-based network depends on the number of clusters deployed. The number of clusters can be expressed by the term cluster ratio, which means the ratio of CH to CM distributed throughout the network. In order to construct a more efficient hierarchical network and improve system performance, methods of analyzing the optimal cluster ratio from various viewpoints have been introduced.

Leach (LEACH) is a clustering algorithm that ensures energy efficiency in the most popular one-hop transmission situations. HEED is a LEACH - based clustering algorithm and compensates for the uniform energy consumption of the system considering the residual energy of the sensor nodes. In LEACH and HEED, we proposed the optimal cluster ratio (5%) by setting the minimum energy consumption of the system as the target function. However, the conventional clustering ratio analysis method is based on an ideal channel condition, and the optimal cluster ratio is analyzed. The increase of the number of hops due to the cluster size change and the packet retransmission due to the instability of the radio channel are not considered.

In addition, the one-hop transmission situation assumed in LEACH and HEED is difficult to realize with IEEE 802.15.4 based low-power short-range communication module. That is, when a sensor network having a hierarchical structure in a wide field is constructed, direct communication between the CM and the CH consumes a lot of energy, and even direct communication may not be possible. In addition, a single multi-hop transmission scheme has a disadvantage in that data to be relayed to a CH close to the sink is concentrated, which causes serious energy consumption.

SUMMARY OF THE INVENTION The present invention has been made to solve the above problems of the prior art. It is an object of the present invention to minimize the hop-count of a hierarchical sensor network based on a multi-hop to one-hop transmission structure, packet reception ratio (PRR) maximization, and by calculating the optimum cluster ratio considering these two factors together, it is possible to minimize the number of hops throughout the network system, and to reduce the network packet transmission cost and the inter-node retransmission overhead And a hierarchical sensor network system to which the method is applied.

According to an aspect of the present invention, there is provided a method for calculating a cluster ratio of a hierarchical sensor network system based on a multi-hop to one-hop transmission structure, Obtaining a total number of hops of the entire system; Obtaining a packet reception ratio between nodes in a cluster; And calculating a cluster ratio considering minimization of the number of network system hops and maximization of a packet reception ratio between nodes. The present invention provides a method for calculating a cluster ratio for energy efficiency.

The present invention also provides a hierarchical sensor network system based on a multi-hop to one-hop transmission structure, the hierarchical sensor network system comprising: a hop count calculation module for obtaining a total hop count of the entire network system; A packet reception ratio calculating module for calculating a packet reception ratio between nodes in the cluster; And a cluster ratio calculating module for calculating a cluster ratio in consideration of minimizing a total number of hop counts of the network system obtained through the hop count calculating module and maximizing a packet reception ratio (PRR) between nodes in the cluster obtained through the packet reception ratio calculating module The present invention provides a sensor network system to which a cluster ratio calculation method for energy efficiency is applied.

The cluster ratio calculation method according to the present invention and the hierarchical sensor network system to which this method is applied assure the energy efficiency of the sensor network by taking into consideration the system hop count minimization and the inter-node transmission reliability maximization. By minimizing the number of network-wide hops through the derived optimal cluster ratio, essentially minimizing system-wide transmission and reception cost. In addition, by maximizing the transmission reliability within the cluster, that is, the packet reception ratio, energy overhead can be reduced by reducing the inter-node retransmission overhead in an unstable channel state.

FIG. 1 is a graph illustrating a result of comparing a minimum hop count and a cluster ratio obtained through a maximum PRR according to an exemplary embodiment of the present invention.
BACKGROUND OF THE INVENTION 1. Field of the Invention [0001] The present invention relates to a hierarchical sensor network system.
FIG. 3 is a simulation result of a situation in which one packet is generated from all the sensor nodes and transmitted to the sink node.
Figure 4 shows the energy efficiency gain results obtained when comparing the present invention with the prior art at a node distribution density of 0.05.

Hereinafter, preferred embodiments of the present invention will be described in detail with reference to the accompanying drawings.

First, the sensor nodes of the present invention are randomly arranged in a sensor field by a Poisson point process, and form a cluster with the closest CH based on a nearest-neighbor mechanism. A cluster member (hereinafter referred to as a CM) in a cluster, that is, a first layer, transmits a packet to a cluster head (CH) at a minimum transmission power through a multi-hop scheme. In the second layer, the CH processes the redundancy of the collected data and then sends the packet to the sink node in one-hop. Accordingly, the present invention makes the following five assumptions for analyzing two layers of a sensor network based on Voronoi tessellation.

에 의하여 센싱 필드 안에 포아송 포인트 프로세서에 따라 랜덤 분포된다.First, the sensor node has a distribution density

0.0 > Poisson < / RTI > point processor in the sensing field.

이며, CH의 수

가 전체 노드 수

에서 차지하는 비율을 의미한다.Second,

And the number of CHs

Is the total number of nodes

.

였을 때,

이며,

는 센서 노드를 분포한 필드의 면적이다.Third, the distribution density of CH

When it was,

Lt;

Is the area of the field where sensor nodes are distributed.

로 계산된다.Fourth, the distribution density of CM

.

이다.
Finally, within the cluster, the transmission radius of the CM is

to be.

는 클러스터 내 CM와 CH 사이 거리가

일 때의 경로손실을 의미하고,

는 경로손실 지수를 의미하며,

는 경로손실 측정을 위한 기준거리이다.In the present invention, an outdoor LoS (line-of-sight) environment is assumed for reliability analysis of inter-node communication. Through such prerequisites, the propagation model of the radio signal is based on the path loss model defined in Equation (1) below. In the following expression (1)

Is the distance between the CM and CH in the cluster

The path loss in the case of < RTI ID = 0.0 >

Means the path loss index,

Is the reference distance for path loss measurements.

In order to analyze the random characteristics of the number of nodes, the link length and the total number of hops in one cluster, there is the following equation (2) in one cluster.

는 함수

의 누적 합을 의미하여,

이다. 여기서, 함수

가 클러스터 한 노드로부터 CH까지의 홉 수로 정의된다면, 즉

(

은 CM와 CH 사이 거리를 의미한다)이 되며, 하기의 [수학식 3]을 통해 한 클러스터 내 총 홉수의 기대치를 구할 수 있게 된다. In Equation (2)

Function

Which is a cumulative sum of "

to be. Here,

Is defined as the number of hops from one node of the cluster to the CH, that is,

(

Is the distance between the CM and the CH), and the expected value of the total number of hops in one cluster can be obtained through the following equation (3).

을 정수로 바꾸기 위하여 파라미터

를 도입하여,

를 얻는다. 이로서, 한 클러스터 내 전체 홉수의 기대치를 하기의 [수학식 4]와 같이 구할 수 있다.In the above equation (3)

To an integer.

Lt; / RTI >

. Thus, the expectation of the total number of hops in one cluster can be obtained as shown in the following equation (4).

이다. 네트워크 전반에서 총 홉 수는 모든 클러스터를 포함한 첫번째와 두 번째 계층에서의 홉 수의 총합이므로 하기의 [수학식 5]에 의해 구할 수 있다.In the present invention, it is assumed that the CH transmits the collected data to the sink node by one-hop, and the number of hops in the second layer is

to be. Since the total number of hops in the entire network is the sum of the number of hops in the first and second layers including all the clusters, it can be obtained by the following equation (5).

Assuming that CH can guarantee reliable one-hop communication up to sink, the packet reception ratio between nodes is analyzed in the cluster. In the cluster, the CM is transmitted using the minimum transmission power for energy efficiency. The neighboring nodes relay the received packet to the CH through the multi-hop. Accordingly, if the transmission reliability of the one-hop link from the CM to the CH is guaranteed, the packet reception ratio (PRR) between the nodes in the first cluster can be guaranteed.

이다. 이 결과를 이용하여 클러스터의 평균 반경은 하기의 [수학식 6]에 의해 얻을 수 있다.For the analysis of PRR, we analyze path loss of wireless signal in the cluster. First, the total number of CMs in the cluster and the sum of the link lengths from the CM to the CH are calculated based on Equation (2)

to be. Using this result, the average radius of the cluster can be obtained by the following equation (6).

이고, 는 파장이며,

이다.Substituting Equation (6) into Equation (1), Equation (7), which can obtain an average path loss in a cluster as follows, is obtained. At this time,

ego, Is a wavelength,

to be.

를 정의한다. 패킷이 성공적으로 수신되었으면

=1이고 아니면

=0이다.

는 iid 분포를 따르므로 대수 약 법칙(weak law of large number)에 의하여 PRR는 패킷을 성공적으로 수신하는 확률과 근사함으로 하기의 [수학식 8]을 통해 얻을 수 있다.Since the packet transmitted from the next CM is transmitted in a bit unit, the bernoulli random variable

. If the packet is successfully received

= 1 < / RTI >

= 0.

Since PRR follows the iid distribution, the PRR is approximated to the probability of successfully receiving a packet by a weak law of large number, and can be obtained by the following equation (8).

는 각각 모듈레이션 기법의 에러 함수에 의하여 결정된다. 그러므로 본 발명의 분석 과정은 모듈레이션 기법에 무관하기 때문에 여러 모듈레이션 기법에 적용할 수 있다. 본 발명의 실시예에서는 저전력 지그비(ZigBee) 모듈로 많이 사용하고 있는 CC1110을 고려하였음으로 FSK 모듈레이션 기법을 예로 든다. FSK 모듈레이션 기법에서

는 하기의 [수학식 9]와 같이 정의된다.In Equation (8), F denotes a frame size and a unit is a byte. Bit error probability

Are determined by the error function of the modulation technique, respectively. Therefore, since the analysis process of the present invention is independent of the modulation technique, it can be applied to various modulation techniques. In the embodiment of the present invention, considering the CC1110, which is widely used as a low power ZigBee module, the FSK modulation technique is taken as an example. In the FSK modulation technique

Is defined as follows. &Quot; (9) "

이며 잡음전력밀도(

)에 대한 비트에너지의 비율을 의미한다.

와 SNR(signal to noise ratio) 사이 관계는 등식

로 정의할 수 있다. 여기서

은 데이터 전송 속도를 의미하고,

은 잡음 대역폭이다. 이로서, 상기 [수학식 8]은 하기 [수학식 10]으로 다시 표현할 수 있다.In Equation (9)

And the noise power density (

) ≪ / RTI >

And SNR (signal to noise ratio)

. here

Means the data transmission rate,

Is the noise bandwidth. Thus, Equation (8) can be rewritten as Equation (10).

와 잡음플로어

로

와 같이 얻을 수 있다. 송신된 신호가 전파과정에서 경로손실을 갖게 되므로, 신뢰성 있는 수신을 위하여 등식

을 만족 시켜야 한다. 이때,

는 송신 파워를 의미하며,

은 경로손실이다. 위에서 유도한 클러스터 내 평균 경로손실을 대입하면

이고,

이다. 이를 상기 [수학식 10]에 대입하면 하기의 [수학식 11]과 같이 패킷 수신율에 대한 클러스터 비율의 함수를 얻을 수 있게 된다.Also, at the receiver angle, SNR is the receiver sensitivity

And noise floor

in

Can be obtained as follows. Since the transmitted signal has path loss in the propagation process,

. At this time,

Quot; means transmission power,

Is the path loss. By assigning the average path loss in the cluster derived above

ego,

to be. Substituting this into Equation (10), a function of the cluster ratio with respect to the packet reception ratio can be obtained as in Equation (11) below.

FIG. 1 shows the results of comparing the optimum cluster ratios obtained using the above-mentioned equations (5) and (11). In this case, the parameters referred to are shown in Table 1 below.

parameter Justice

19.2 kbps

30 kHz

-115dBm

-25dBm

1, 0.125 m

50 bytes

As shown in FIG. 1, since the PRR is only 90% at point A which can provide the minimum number of hops, the number of retransmissions between nodes increases. In addition, it can be seen that the hop count increases by 13% at the optimal point B to guarantee a PRR of 99%. In this way, the reliable minimum transmission / reception environment can not be guaranteed only by the technique for the minimum number of hops, and if the smaller and larger clusters are installed for the PRR guarantee, the overhead of packet transmission increases.

Because of such a trade-off relationship, it is difficult to obtain an optimal cluster ratio for ensuring energy efficiency through the results obtained by Equations (5) and (11) We propose an objective function. The target function defined by the following Equation (12) comprehensively considers the minimization of the total number of system hops that can be obtained from Equation (5) and the maximization of PRR in the cluster obtained from Equation (11) Respectively. The optimal cluster ratio satisfying the proposed objective function minimizes the cost for packet transmission in the network and minimizes the retransmission caused by unstable radio channels in the cluster, thereby further securing system energy efficiency.

2 is an internal configuration diagram of a hierarchical sensor network system to which the cluster ratio calculating method of the present invention is applied.

2, the hierarchical sensor network system of the present invention includes a hop count calculation module 110 for calculating a total hop count of the entire sensor network system, a packet reception ratio calculation module 120 for calculating a packet reception ratio between nodes in the cluster, And an optimal cluster ratio considering the minimization of the total number of hops of the system obtained through the HOPS calculation module 110 and the maximization of the packet reception ratio (PRR) between nodes in the cluster obtained through the packet reception ratio calculation module 120 And a cluster ratio calculating module 130 for calculating the cluster ratio.

을 이용한다. 이때,

는 함수

의 누적 합을 의미하여,

이다. 여기서, 함수

가 클러스터 한 노드로부터 CH까지의 홉 수로 정의된다면, 즉

(

은 CM와 CH 사이 거리를 의미한다)이 되며, 한 클러스터 내 총 홉수의 기대치를

을 통해 구할 수 있게 된다.The HOPS calculation module 110 obtains the total number of hops in the entire network system. To analyze the random number of nodes, link length and total number of hops in a cluster

. At this time,

Function

Which is a cumulative sum of "

to be. Here,

Is defined as the number of hops from one node of the cluster to the CH, that is,

(

Is the distance between CM and CH), and the expectation of the total number of hops in one cluster

.

을 정수로 바꾸기 위하여 파라미터

를 도입하여,

를 얻는다. 이로서, 한 클러스터 내 전체 홉수의 기대치를 하기의 [수학식 13]과 같이 구할 수 있다.At this time,

To an integer.

Lt; / RTI >

. Thus, the expected value of the total number of hops in one cluster can be obtained as shown in the following equation (13).

이되며, 결국 네트워크 시스템 전반에서의 총 홉수는 모든 클러스터를 포함한 첫 번째와 두 번째 계층에서의 홉 수의 총 합이므로 하기의 [수학식 14]을 통해 구할 수 있다.In the present invention, the CH transmits the collected data to the sink node by one-hop, so that the number of hops in the second layer is

The total number of hops in the entire network system is the sum of the number of hops in the first and second layers including all the clusters, so that it can be obtained through the following equation (14).

The packet reception ratio calculating module 120 calculates a packet reception ratio between nodes in a cluster. In the present invention, since it is assumed that CH can guarantee reliable one-hop communication until the sink, the packet reception rate between nodes is analyzed in the cluster. In the cluster, the CM is transmitted using the minimum transmission power for energy efficiency. The neighboring nodes relay the received packet to the CH through the multi-hop. Thus, if the reliability of the one-hop link from the CM to the CH is guaranteed, PRR between the nodes in the first cluster can be guaranteed. Accordingly, the packet reception ratio calculating module 120 of the present invention calculates the cluster ratio with respect to the packet reception rate through the following equation (15), which is a function obtained by substituting the intra-cluster average path loss into the inter-node packet reception ratio (PRR) .

The cluster ratio calculation module 130 obtains an optimal cluster ratio considering minimization of the total number of system hops and maximization of the packet reception ratio (PRR) between nodes in the cluster. That is, the cluster ratio calculation module 130 minimizes the total number of system hops derived through the hop count calculation module 110 and maximizes the packet reception ratio (PRR) in the cluster derived through the packet reception ratio calculation module 120 The optimum cluster ratio satisfying the target function expressed by the following expression (16) is calculated.

Accordingly, the sensor network system of the present invention minimizes the cost for packet transmission in the network by obtaining an optimal cluster ratio satisfying the target function, and minimizes the retransmission caused by unstable wireless channels in the cluster, The efficiency can be further secured.

In order to verify that the optimal cluster ratio obtained through the proposed function of the present invention shows an improvement in energy efficiency, it is compared with a conventional clustering technique to guarantee the minimum number of hops through simulation.

필드에 분포밀도 0.03, 0.05, 0.07에 의하여 각각 30000, 50000, 70000개의 센서노드를 랜덤 배치한다. RF모듈은 CC1110을 이용하고, 915MHz 주파수 대역을 사용하며, 클러스터 내에서 센서노드는 최소 전송파워 -25dBm을 이용하여 송신한다. 센서 노드들에서는 FSK 모듈레이션 기법을 사용하며, 한 프레임 크기는 50byte이다. 경로 손실 모델은 상기 [수학식 7]에서 정의한 모델을 사용하며, 음영페이딩(shadow fading)과 다중경로 페이딩(multi-path fading)은 고려되지 않는다. 기타 시뮬레이션에 참조된 파라미터들은 상기 [표 1]과 동일하다.
In the simulation of the present invention

30,000, 50,000, and 70,000 sensor nodes are randomly arranged in the field by distribution densities of 0.03, 0.05 and 0.07, respectively. The RF module uses the CC1110, uses the 915MHz frequency band, and transmits the sensor node using the minimum transmission power of -25dBm in the cluster. In the sensor nodes, the FSK modulation technique is used, and one frame size is 50 bytes. The path loss model uses the model defined in Equation (7), and shadow fading and multi-path fading are not considered. The parameters referred to in the other simulations are the same as those in Table 1 above.

FIG. 3 is a simulation result of a situation where one sensor node generates one packet and transmits it to a sink node. As shown in FIG. 3, (a), (b) and (c) are the results when the sensor nodes are randomly distributed by the distribution density of 0.03, 0.05 and 0.07, respectively. In (a), (b) and (c), the average PRR within clusters guaranteed by the minimum hop clustering technique is 90%, 95%, and 97%, respectively. This is because the smaller the distribution density of the sensor node is, the more the distance from the adjacent relay node becomes, and the more path loss occurs. Although the existing minimum hop count clustering scheme can optimize the number of hops required for transmission throughout the system, it does not guarantee the transmission / reception reliability between the nodes that changes according to the distribution density of sensor nodes. Therefore, the number of transmissions throughout the system is larger than that proposed in the present invention, and the energy consumption for transmission is also increased.

When the random distribution density of the sensor nodes was 0.03, 0.05, and 0.07, the optimal cluster ratio (CR) obtained through the objective function proposed by the present invention was 2%, 0.8%, and 0.3% %. This is because the present invention comprehensively considers the number of hops of system packet transmission and the PRR of inter-node communication so that it is more efficient in extending the life of the network than the existing scheme, and in particular, the smaller the distribution density of the sensor node, .

FIG. 4 shows the energy efficiency gain results obtained when the present invention is compared with the conventional minimum hop number clustering technique at a node distribution density of 0.05. As shown in FIG. 4, the path loss indexes are set to 3.0, 3.5, 4.0, and 4.5, respectively, in order to consider various path loss environments. In the case of the most ideal path loss (path loss index is 3.0), the optimal cluster ratio scheme proposed by the present invention achieves a gain of 0.1% and 16.25% when the path loss is the most severe (path loss index 4.5) . It can be seen that the present invention achieves more energy efficiency through the optimal cluster ratio since the PRR maximization in the cluster is considered in the target function.

It will be apparent to those skilled in the art that various modifications and variations can be made in the present invention without departing from the spirit or scope of the invention. Therefore, it is intended that the present invention cover the modifications and variations of this invention provided they come within the scope of the appended claims and their equivalents. It will be obvious to those of ordinary skill in the art.

110: HOP number calculation module 120: Packet reception ratio calculation module
130: Cluster Rate Calculation Module

Claims (14)

A method for calculating a cluster ratio of a hierarchical sensor network system based on a multi-hop to one-hop transmission structure,
Obtaining a total number of hops of the entire network system;
Obtaining a packet reception ratio between nodes in a cluster; And
Calculating a cluster ratio considering minimization of the number of network system hops and maximization of a packet reception ratio between nodes;
And calculating a cluster ratio for energy efficiency.
The method according to claim 1,
In the step of obtaining the total number of hops in the network system,
Wherein the total number of hops in the first and second layers including all the clusters is obtained.
3. The method of claim 2,
The total number of the hop numbers
And calculating the cluster ratio for energy efficiency based on the following formula (1).
[Equation 1]

here,

,

,

: Number of cluster heads,

: The total number of nodes,

: Distance between cluster member and cluster head,

: The transfer radius of cluster members within the cluster,

,

: Area of field distributed by sensor node.
The method according to claim 1,
In the step of obtaining the inter-node packet reception ratio in the cluster,
Wherein the cluster rate is calculated through a function of the cluster ratio according to the packet reception ratio.
5. The method of claim 4,
The function of the cluster ratio according to the packet reception ratio is,
Wherein a mean path loss in a cluster is substituted for a packet reception ratio (PRR).
6. The method of claim 5,
The average path loss in the above-
And calculating a cluster ratio for energy efficiency according to the following formula (2).
&Quot; (2) "

here,

,

: Number of cluster heads,

: The total number of nodes,

: Area of sensor node distributed field,

,

: wavelength,
,

Path loss index.
6. The method of claim 5,
The packet reception ratio (PRR)
And calculating the cluster ratio for energy efficiency according to the following formula (3).
&Quot; (3) "

here,

,

: Ratio of bit energy,

: Data transmission speed,

: Noise power density,

: Noise bandwidth,

: Frame size.
6. The method of claim 5,
The function of the cluster ratio with respect to the packet reception ratio,
And calculating a cluster ratio for energy efficiency according to Equation (4).
&Quot; (4) "

here,

: Transmission power,

: Noise floor,

: Noise bandwidth,

: Data transmission speed,

: wavelength,

: Path loss index,

: The total number of nodes,

,

: Number of cluster heads,

: Area of sensor node distributed field,

: Frame size.
The method according to claim 1,
Wherein the step of calculating the cluster ratio considering the minimization of the number of network system hops and the maximization of the inter-
And calculating a cluster ratio for energy efficiency based on the following formula (5).
&Quot; (5) "

here,

: The total number of nodes,

,

: Number of cluster heads,

: The transfer radius of cluster members within the cluster,

: Distribution density,

: Transmission power,

: Noise floor,

: Noise bandwidth,

: Data transmission speed,

: wavelength,

: Path loss index,

,

: Area of sensor node distributed field,

: Frame size.
In a hierarchical sensor network system based on a multi-hop to one-hop transmission structure,
A hop count calculating module for calculating a total hop count of the entire network system;
A packet reception ratio calculating module for calculating a packet reception ratio between nodes in the cluster; And
A cluster ratio calculating module for calculating a cluster ratio in consideration of minimizing a total number of network system hops obtained through the hop count calculating module and maximizing a packet reception ratio (PRR) between nodes in the cluster obtained through the packet reception ratio calculating module;
A sensor network system to which a cluster ratio calculation method for energy efficiency is applied.
11. The method of claim 10,
The total number of hops is
And the number of hops in the first and second layers including all the clusters. The sensor network system to which the cluster ratio calculation method for energy efficiency is applied.
12. The method of claim 11,
The total number of hops is
And calculating a cluster ratio for energy efficiency according to Equation (6) below.
&Quot; (6) "

here,

,

,

: Number of cluster heads,

: The total number of nodes,

: Distance between cluster member and cluster head,

: The transfer radius of cluster members within the cluster,

,

: Area of field distributed by sensor node.
11. The method of claim 10,
The packet reception ratio calculating module calculates,
And the average path loss in a cluster is substituted for the packet reception ratio (PRR), which is a function obtained by the following formula (7). ≪ EMI ID = 7.0 >
&Quot; (7) "

here,

: Transmission power,

: Noise floor,

: Noise bandwidth,

: Data transmission speed,

: wavelength,

: Path loss index,

: The total number of nodes,

,

: Number of cluster heads,

: Area of sensor node distributed field,

: Frame size.
11. The method of claim 10,
The cluster ratio calculating module calculates,
Wherein a cluster ratio satisfying a target function expressed by Equation (8) below is calculated. A sensor network system to which a cluster ratio calculating method for energy efficiency is applied.
&Quot; (8) "

here,

: The total number of nodes,

,

: Number of cluster heads,

: The transfer radius of cluster members within the cluster,

: Distribution density,

: Transmission power,

: Noise floor,

: Noise bandwidth,

: Data transmission speed,

: wavelength,

: Path loss index,

,

: Area of sensor node distributed field,

: Frame size.

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