KR101944194B1 - Sensing and compression rate selection with energy-allocation in solar-powered wireless sensor networks, recording medium and device for performing the method - Google Patents

Abstract

The present invention relates to a method for selecting a sensing cycle and a compression algorithm considering energy allocation in a solar energy collection type wireless sensor network. The method for selecting a sensing cycle and a compression algorithm considering energy allocation in a solar energy collection type wireless sensor network includes: a step of dividing a predetermined time into multiple slots in a wireless sensor network and allocating an energy amount which can be used in each slot; a step of transmitting data amount to descendant nodes of nodes which are at a distance of 1 hop from a sink node by nodes by calculating the data amount which the node and the descendant nodes of the node can transmit during each slot; a step of determining a motion mode of the node for selecting a data collection amount and a compression algorithm based on the estimated energy amount consumed, the data amount which can be transmitted, and the energy amount which can be used in each slot by each descendant node receiving the data amount which can be transmitted; a step of determining the sensing cycle for collecting the data in accordance with the determined motion mode of the descendant node by each descendant node; and a step of collecting as much data as the data collection amount selected in accordance with the determined motion mode of the descendant node and the sensing cycle by each descendant node and compressing and transmitting the collected data in accordance with the compression algorithm selected. Therefore, the method for selecting a sensing cycle and a compression algorithm considering energy allocation in a solar energy collection type wireless sensor network can obtain more data and can effectively suppress the generation of an interruptible node by selecting a compression technique and the data collection cycle to be suitable to a situation of each node.

Description

TECHNICAL FIELD [0001] The present invention relates to a sensing period and a compression algorithm selection method considering energy allocation in a solar energy collection type wireless sensor network, and a recording medium and a device for performing the sensing period and compression algorithm selection method. FOR PERFORMING THE METHOD}

The present invention relates to a sensing period and a compression algorithm selection method considering energy allocation in a solar energy collection type wireless sensor network, and a recording medium and an apparatus for performing the same. More particularly, the present invention relates to an energy management And to techniques for solving problems and hotspot problems and increasing data acquisition.

Since a node used in a wireless sensor network (WSN) generally operates as a battery, it has a finite life, and studies for overcoming this have been actively conducted. As a way to overcome the lifetime of the node, techniques have been proposed that use an energy collection node to collect energy from the surrounding environment.

In particular, solar energy is becoming more popular due to its higher power density (about 15 mW / cm ² ) compared to other energy sources. However, even this energy collection node consumes more energy than the energy it collects, it can become depleted and become out of order. On the other hand, if the collected energy is not utilized enough, more energy can be collected and discarded. Therefore, there is a need for a technique that utilizes the maximum amount of energy within the range where the node lives forever by adjusting the amount of consumed energy according to the collected amount.

Among the techniques for controlling the energy consumption of the nodes, the energy allocation technique which limits the amount of energy that can be used over time is effective to use evenly regardless of the change in energy collection amount. In particular, although solar energy is collected only during the day and is not collected at night, it has a large variation with time. However, since these techniques can use a relatively constant energy regardless of time, useful.

On the other hand, WSN generally transmits data in multi-hop. As a result, there is a hot spot problem in which the amount of data to be transmitted increases as the node near the sink node increases. To solve this problem, techniques for compressing and transmitting data have been studied. When compressing and transmitting data, it consumes less energy for data compression, but since the data size to be transmitted is reduced, the amount of data that the relay node must transmit is reduced, thereby reducing energy consumption. On the other hand, in the case of a node close to the sink node, compression of data may be inefficient because the number of relay nodes to transmit is small.

In other words, the prior art has the following problems.

Since the energy of the nodes near the sink node is depleted and the data of the other node can not be transmitted, a hot spot problem occurs in which a large amount of sensing data can not reach the sink node. It can be seen that as the density of the nodes decreases, the number of data arriving at the sink nodes decreases. This is because, when the density of the node is low, the transmission path of the nodes becomes long, so that when the relay node goes to the power failure state, more data is lost during transmission.

When the amount of solar energy is small, the amount of sensing data is larger than that of the proposed method. However, since the amount of solar energy is small, the number of static nodes is increased and the amount of data arriving at the sink node is smaller than that of the proposed method.

As described above, the wireless sensor node is implemented as a very small built-in system, so that the processing speed is low and the available memory is small. Since existing compression schemes are not suitable for this limited environment, a lightweight compression technique that can be used in wireless sensor nodes is needed. Also, data compression should be applied considering the energy efficiency of the data acquisition node and the relay node.

KR 10-1735369 B1

 C. M. Sadler and M. Martonosi, "Data compression algorithms for energy-constrained devices in delay tolerant networks," Proceedings of the 4th international conference on embedded networked sensor systems. ACM, pp. 265-278, Boulder, Colorado, Oct 31-Nov 3, 2006.

SUMMARY OF THE INVENTION Accordingly, the present invention has been made in view of the above problems, and it is an object of the present invention to provide a sensing period and a compression algorithm selection method considering energy allocation in a solar energy collection type wireless sensor network.

It is another object of the present invention to provide a recording medium on which a computer program for performing a sensing period and a compression algorithm selection method considering energy allocation in the solar energy collection type wireless sensor network is recorded.

It is still another object of the present invention to provide an apparatus for performing a sensing cycle and a compression algorithm selection method considering energy allocation in the solar energy collection type wireless sensor network.

According to another aspect of the present invention, there is provided a sensing period and a compression algorithm selection method for energy allocation in a solar energy collection type wireless sensor network, wherein the sensing period and the compression algorithm selection method divide a predetermined time into a plurality of slots in the wireless sensor network, Allocating an amount of energy available in each slot; The nodes located one hop away from the sink node calculate the amount of data that can be transmitted by itself and its descendant nodes during each slot and transmitting the amount of data to the descendants of the node; Each descendant node receiving the amount of data that can be transmitted can calculate the data collection amount and the compression algorithm based on the amount of available energy, the amount of data that can be transmitted, and the estimated amount of energy consumed in each slot. Determining an operating mode; Each child node determining a sensing period for collecting data according to its determined operation mode; And each child node collects data according to the selected data collection amount according to the determined operation mode and the sensing period, and compresses and transmits the collected data according to the selected compression algorithm.

In an embodiment of the present invention, the step of determining the mode of operation of the self comprises calculating the amount of energy consumed to be consumed by each child node in each operation mode during the corresponding slot; Determining whether to collect additional data within a range that does not exceed the amount of data that can be transmitted by comparing the amount of available energy with the amount of consumed estimated energy and determining whether to compress or transfer the data; And selecting an operation mode of one of a normal mode, an L-mode and an H-mode depending on whether to collect additional data and whether to compress and transfer the data.

In the embodiment of the present invention, each of the child nodes collects data by a selected data collection amount in accordance with the determined operation mode and the sensing period, and compressing and transmitting the collected data according to the selected compression algorithm, In the normal mode, it is possible to collect data as much as the amount of data that can be transmitted without collecting the data, and transmit the data without compression.

In the embodiment of the present invention, each of the child nodes collects data by a selected data collection amount in accordance with the determined operation mode and the sensing period, and compressing and transmitting the collected data according to the selected compression algorithm, In the L mode, additional data may be collected in addition to the amount of data that can be transmitted, and the collected data may be compressed and transmitted.

In the embodiment of the present invention, each of the child nodes collects data by a selected data collection amount in accordance with the determined operation mode and the sensing period, and compressing and transmitting the collected data according to the selected compression algorithm, In the H mode, more data may be collected than the L mode, and the collected data may be compressed and transmitted at a higher compression ratio than the L mode.

In an embodiment of the present invention, the step of calculating the expected amount of energy consumed by each of the child nodes in each operation mode during the corresponding slot may include consuming energy, basic energy consumption, and data consumption for transmitting data during the corresponding slot Can be calculated on the basis of the energy that is generated.

In an embodiment of the present invention, the sensing period and the compression algorithm selection method considering energy allocation in the solar energy collection type wireless sensor network may include a step of selecting ones of the nodes that are one hop away from the sink node as the normal mode .

According to another aspect of the present invention, there is provided a computer-readable storage medium having a computer program for performing a sensing cycle considering energy allocation in a solar energy collecting wireless sensor network and a compression algorithm selecting method It is recorded.

According to another aspect of the present invention, there is provided a sensing period and a compression algorithm selecting apparatus considering energy allocation in a solar energy collecting wireless sensor network, A receiving unit receiving an amount of energy and a data amount that each node can transmit; An energy calculation unit for calculating an estimated energy amount consumed in each operation mode during the corresponding slot; An operation mode determination unit that determines an operation mode for selecting a data collection amount and a compression algorithm based on the amount of available energy, the amount of data that can be transferred, and the estimated amount of energy consumed; A sensing period determiner for determining a sensing period for collecting data according to the determined operation mode; And a transmission unit for collecting data for a selected data collection amount according to the determined operation mode and the sensing period, and compressing and transmitting the collected data according to the selected compression algorithm.

In the embodiment of the present invention, the operation mode determination unit may determine whether to collect additional data within a range that does not exceed the amount of data that can be transmitted by comparing the amount of energy that can be used with the amount of energy that is consumed, Depending on whether or not the data is compressed and transmitted, one of the normal mode, the L mode and the H mode can be selected.

According to the sensing cycle and the compression algorithm selection method considering the energy allocation in the solar energy collecting wireless sensor network, the node of one hop distance from the sink node determines the data transmission limit and transmits it to the other node, And other nodes select the appropriate sensing period and compression scheme to suppress the occurrence of electrostatic nodes and increase the data collection amount. Accordingly, the present invention can effectively suppress the generation of the electrostatic node and obtain a larger amount of data by selecting the data collection period and the compression technique according to the situation of the node, so that the energy of the wireless sensor network can be efficiently managed have.

1 is a schematic diagram illustrating a sensing period and a selection method of a compression algorithm considering energy allocation in a solar energy collection type wireless sensor network according to an exemplary embodiment of the present invention.
2 is a diagram showing energy and operation of a node over time during two slots.
FIG. 3 is a diagram showing stepwise determination of the node operation mode and the sensing period. FIG.
FIG. 4 is a graph illustrating the results of measurement of the number of electrostatic nodes according to the present invention and conventional techniques over a total of 7 days from 1000 slots to 1168 slots.
5 is a graph showing a result of measuring the number of electrostatic discharge nodes per hop number from a sink node in 2000 slots.
FIGS. 6 and 7 are graphs showing the results of measuring the amount of sensing data of all the nodes and the number of data arriving at the sink node according to the present invention in the present invention and the prior art, respectively.
8 and 9 are graphs showing the results of measuring the amount of sensing data according to the density change of the node and the number of data arriving at the sink node in the present invention and the related art, respectively.
10 and 11 are graphs comparing the number of sensed data with the number of extracted data according to the solar energy in the present invention and prior art, respectively.
FIG. 12 is a block diagram of a sensing period and a compression algorithm selecting apparatus considering energy allocation in a solar energy collecting wireless sensor network according to an exemplary embodiment of the present invention. Referring to FIG.

The following detailed description of the invention refers to the accompanying drawings, which illustrate, by way of illustration, specific embodiments in which the invention may be practiced. These embodiments are described in sufficient detail to enable those skilled in the art to practice the invention. It should be understood that the various embodiments of the present invention are different, but need not be mutually exclusive. For example, certain features, structures, and characteristics described herein may be implemented in other embodiments without departing from the spirit and scope of the invention in connection with an embodiment. It is also to be understood that the position or arrangement of the individual components within each disclosed embodiment may be varied without departing from the spirit and scope of the invention. The following detailed description is, therefore, not to be taken in a limiting sense, and the scope of the present invention is to be limited only by the appended claims, along with the full scope of equivalents to which such claims are entitled, if properly explained. In the drawings, like reference numerals refer to the same or similar functions throughout the several views.

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

The present invention proposes a data collection control method and a compression algorithm selection technique for increasing the amount of collected data in an energy-consuming wireless sensor network (WSN) using solar energy. The present invention is based on a WSN that periodically transmits sensing data to a sink node to monitor the surrounding environment.

1 is a schematic diagram illustrating a sensing period and a selection method of a compression algorithm considering energy allocation in a solar energy collection type wireless sensor network according to an exemplary embodiment of the present invention.

In the present invention, each node divides a day into N slots and allocates energy usable for each slot to uniformly use the collected solar energy regardless of time.

가 결정되면, 싱크 노드에서 1홉(hop) 거리에 있는 노드들은 현재 슬롯 동안 자신과 자신의 자손 노드들이 전송할 수 있는 데이터량

을 계산한다. 싱크 노드에서 1홉(hop) 거리에 있는 각 노드는 계산된 데이터량

을 자손 노드들에게 전송하고, 이를 받은 노드들은 해당 슬롯 동안, 해당 양 만큼의 데이터만 전송한다. Energy available in each slot

The nodes that are one hop away from the sink node are able to determine the amount of data that they and their child nodes can transmit during the current slot

. Each node that is one hop away from the sink node calculates the amount of data

To the descendant nodes, and the nodes receiving the data transmit only the corresponding amount of data during the corresponding slot.

를 고려하여, 자신의 동작 모드를 결정하고, 해당 동작 모드에서 사용하는 압축 알고리즘을 이용하여 데이터를 압축한다. 이때, 압축된 데이터의 크기가 데이터량

가 되도록 데이터 수집량을 조절하여, 제한된 범위 안에서 최대한 많은 데이터를 전송하도록 한다. In this case, each node can use energy

, Determines its own operation mode, and compresses the data using the compression algorithm used in the operation mode. At this time, if the size of the compressed data is the data amount

So as to transmit as much data as possible within a limited range.

Since the nodes perform multi-hop transmission, a node that is one hop away from the sink node generally transmits a larger amount of data than other nodes that transmit data to the sink node. In this case, when the outer node collects and transmits a lot of data, all nodes in the path from it to the sink node consume more energy.

Therefore, in the present invention, a node of 1-hop distance calculates its own available data amount and informs nodes transmitting data to itself, thereby limiting the amount of the node's transmission. To do this, we first need to predict how much data a node can transmit.

에 한 노드가

주기로 한번에

만큼의 데이터를 수집한다고 할 때, 이 슬롯 동안 전송해야 하는 데이터량

은, 아래의 수학식 1에 의해 도출된다.slot

One node in

Once in a cycle

, The amount of data to be transmitted during this slot

Is derived by the following equation (1).

은 한 슬롯의 길이다. 이를 전송하기 위해 패킷화 했을 때, 한 번에 전송할 수 있는 최대 데이터 크기는

이고, 패킷에 추가되는 헤더와 푸터의 크기는

라고 하면, 패킷의 크기는 다음의 수학식 2와 같이

에 관한 함수로 나타낼 수 있다.here,

Is the path of one slot. When packetized for transmission, the maximum data size that can be transmitted at one time is

, The size of the header and footer added to the packet is

, The size of the packet is expressed by the following equation (2)

Can be expressed as a function of.

개 있고, 모든 노드가 공평하게 데이터를 전송할 경우, 이 슬롯 동안 전송해야 하는, 릴레이 데이터를 포함한, 데이터의 총량은 다음의 수학식 3과 같다.The descendant node of this node

And all nodes transmit data fairly, the total amount of data, including relay data, to be transmitted during this slot is given by Equation 3 below.

에 할당된 에너지량이

일 때, 이 슬롯 동안 데이터 전송에 사용할 수 있는 에너지

는 다음의 수학식 4로 나타낼 수 있다.Meanwhile,

The amount of energy allocated to

, The energy available for data transmission during this slot

Can be expressed by the following equation (4).

는 이 슬롯 동안의 전송 에너지를 제외한 기본 소모 에너지이다.

로 전송할 수 있는 데이터량을 구하기 위해 다음의 수학식 5와 같은 에너지 모델을 이용한다.here,

Is the basic energy consumed excluding the transmission energy during this slot.

The energy model as shown in Equation (5) is used.

는 전송 데이터의 크기,

는 데이터 1바이트를 1m전송하기 위한 단위 에너지,

는 전송거리,

는 경로 손실을 나타낸다. 이를 이용하여 한 슬롯 동안 전송할 수 있는 패킷의 총량

를 계산하면, 다음의 수학식 6과 같다.here,

The size of the transmission data,

Is a unit energy for transferring 1 byte of data 1 m,

The transmission distance,

Represents the path loss. Using this, the total amount of packets that can be transmitted during one slot

The following equation (6) is obtained.

동안 전송할 수 있는 실제 데이터량

을 구할 수 있다. 이 노드는 이를 슬롯

시작 시, 자손 노드에게 전송하여, 모든 자손 노드가 슬롯

동안 해당 데이터량만큼의 데이터만을 전송할 수 있게 한다.When the equation (3) is substituted into the equation (6)

Amount of data that can be transferred during

Can be obtained. This node

At the start, it is sent to the child nodes,

Only data corresponding to the amount of data can be transmitted.

슬롯에서 위에서 결정된 데이터량

만큼만 전송할 수 있기 때문에, 할당된 에너지가 남을 경우, 추가 데이터를 수집하고 이를 압축함으로써,

를 초과하지 않는 범위 내에서 최대한 많은 데이터를 수집할 수 있게 한다. 이때, 다음과 같은 세 가지 모드를 이용하여 데이터 수집량과 압축 기법을 결정할 수 있다.The nodes

The amount of data determined above in the slot

, So that if the allocated energy remains, by collecting additional data and compressing it,

To the maximum extent possible. At this time, data collection and compression techniques can be determined using the following three modes.

동안

만큼의 데이터를 수집하여 그대로 전송한다. 한편, 싱크 노드로부터 1홉 거리에 있는 노드들은 에너지 소모가 가장 크고, 데이터를 압축하여 전송하더라도 중계 노드의 에너지를 절약할 수 없기 때문에, 언제나 일반 모드로 동작한다.Normal mode: When the allocated energy is not enough to collect additional data and compress it, the node operates in normal mode, transferring the collected data intact without compressing the data. Since the data is not compressed in the normal mode,

During

And transmits the data as it is. On the other hand, the nodes that are one hop away from the sink node have the highest energy consumption and can not save the energy of the relay node even if the data is compressed and transmitted.

가 될 수 있도록 추가 데이터를 수집하고, 이를 압축하여 전송한다. 그 결과, 데이터를 추가로 수집하고 압축하기 위한 에너지가 더 소모된다.L mode: If the allocated energy is sufficient to compress and deliver the data, the node collects the additional data and operates in L mode to compress and transmit it. The node in this mode is the size of the compressed data

, And compresses and transmits the additional data. As a result, more energy is consumed to further collect and compress the data.

가 될 수 있도록 추가 데이터를 수집하고, 이를 압축률이 더 좋은 알고리즘으로 압축하여 전송한다. 그 결과, L 모드에 비해 데이터를 더 많이 수집하고 압축에 더 많은 에너지를 소모한다. H mode: If the allocated energy is compressed and transmitted, then the node will collect more data than the L mode and compress it using energy-intensive compression techniques And then operates in the H mode for transmission. The node in this mode also has the size of the compressed data

, And compresses and transmits the additional data to an algorithm with a better compression ratio. As a result, it collects more data and consumes more energy for compression than L mode.

를 전달받으면, 슬롯에 할당된 에너지

를 초과하지 않는 범위 내에서 최대한 많은 데이터를 전송할 수 있는 모드를 선택해야 한다. 이를 위해, 노드는 슬롯

동안 각 모드에서 소모되는 에너지를 계산해야 한다. 슬롯

동안 노드의 소모 에너지는 다음의 수학식 7과 같이 나타낼 수 있다.Each node has its own parent node

, The energy allocated to the slot

To the maximum extent possible, within a range that does not exceed the maximum transmission rate. To this end,

The energy consumed in each mode must be calculated. slot

The consumed energy of the node can be expressed by the following Equation (7).

는

슬롯 동안 데이터를 압축하는데 소모되는 에너지이다. 노드는

슬롯 동안

만큼 데이터를 전송하기 때문에

슬롯 동안 소모되는 전송 에너지

는 식 수학식 3과 수학식 6에 의해 다음의 수학식 8과 같이 나타낼 수 있다.here,

The

It is the energy consumed to compress the data during the slot. The node

During the slot

Because it transmits as much data as

Transmission energy consumed during slot

Can be represented by Equation (3) and Equation (6) as follows.

이고,

byte를 압축할 때 소모되는 에너지가

일 때, 압축하기 전의 데이터 크기

는

이기 때문에, 슬롯

동안 노드의 소모 에너지는 다음의 수학식 9와 같다.When a node compresses and transmits data, the size of the compressed data is

ego,

The energy consumed when compressing a byte is

, The data size before compression

The

Therefore,

The consumed energy of the node is given by Equation (9).

는 압축률이고,

로 나타낸다. 위의 수학식 9를 이용하여 H 모드의 소모 에너지

와 L 모드에서의 소모 에너지

를 각각 구하면, 다음의 수학식 10 및 수학식 11과 같다.here,

Is a compressibility,

Respectively. Using the above equation (9), the consumption energy of the H mode

And the consumption energy in L mode

Are obtained by the following equations (10) and (11).

과

는 각각 H 모드와 L 모드에서 사용된 압축 기법의 소모 에너지,

과

는 각각 H 모드와 L 모드에서 사용된 압축 기법의 압축률을 나타낸다. 위의 각 모드에서 소모되는 예상 에너지가 슬롯

에 할당된 에너지보다 적을 경우, 해당 모드로 동작하는데 충분한 에너지가 확보된 것을 의미하기 때문에 노드는 그에 맞는 모드를 선택해야 한다. here,

and

Is the consumption energy of the compression technique used in the H and L modes, respectively,

and

Represents the compression ratio of the compression technique used in the H mode and the L mode, respectively. In each of the above modes,

If the energy is less than the energy allocated to the node, it means that enough energy is available to operate in that mode, so the node must select the mode that corresponds to it.

If Equation (12) is satisfied, the node chooses the H mode because it is expected that there will be sufficient energy to operate in the H mode. If there is not enough energy to select the H mode and if Equation (13) is satisfied, the node chooses the L mode because it means that sufficient energy is allocated to operate in the L mode although it is insufficient to operate in the H mode.

If the above equations (12) and (13) are not satisfied, the node operates in the normal mode since there is not enough energy to consume compression.

byte의 데이터를 전송하기 위한 적합한 센싱 주기를 결정해야 한다. 1슬롯 동안

byte를 수집하기 위한 센싱 주기

는 아래의 수학식 14와 같은 함수로 나타낼 수 있다.After the node has determined the mode,

it is necessary to determine an appropriate sensing period for transmitting data of a byte. During one slot

Sensing cycle for collecting byte

Can be represented by a function expressed by Equation (14) below.

동안 노드의 센싱 데이터가

bytes 만큼 전송되어야 하기 때문에, H와 L 모드일 때의 노드가 수집해야 하는 압축하기 전의 데이터 크기는 각각

,

가 된다. 따라서, H 모드, L 모드, 일반 모드에서의

byte의 데이터를 전송하기 위한 데이터 수집 주기

,

,

는 다음의 수학식 15, 수학식 16 및 수학식 17로 나타낼 수 있다.slot

The sensing data of the node

bytes, the data size before compression that the node should collect in the H and L modes is

,

. Therefore, in the H mode, the L mode, and the normal mode

Data collection period for transmitting data of byte

,

,

Can be expressed by the following equations (15), (16), and (17).

동안의 데이터 전송량

을 전달받고, 할당된 에너지 내에서 최대한 효율이 좋은 모드를 선택한다. 그 후

를 만족시키는 양의 데이터를 수집하고 압축하여 전송함으로써, 중계 노드에 전혀 부담을 주지 않으면서 에너지 효율을 높일 수 있다.As described above, in the method proposed by the present invention,

Data throughput during

And selects a mode that is as efficient as possible within the assigned energy. After that

Is collected, compressed, and transmitted, it is possible to increase the energy efficiency without imposing any burden on the relay node.

2 is a diagram showing energy and operation of a node over time during two slots.

를 구하고, 그 센싱 주기에 따라 데이터를 수집한다.Referring to FIG. 2, the node selects the L mode for the i slot when it is smaller than the energy consumption estimated in the H mode than the energy amount allocated in the i slot, and is larger than the energy consumption expected in the L mode. In addition, the sensing period according to the L mode

And collects data according to the sensing period.

를 구하고, 그 센싱 주기에 따라 데이터를 수집한다.Then, the node selects the H mode for the (i + 1) -th slot when the amount of energy allocated in the (i + 1) th slot is larger than the expected energy in the H mode. Further, the sensing period according to the H mode

And collects data according to the sensing period.

FIG. 3 is a diagram showing stepwise determination of the node operation mode and the sensing period. FIG.

Referring to FIG. 3, a sensing period and a compression algorithm selection method considering energy allocation in a solar energy collecting wireless sensor network first perform routing and determination of child nodes.

The sink node sends a routing message and sends an answer message to the n ^D child nodes that received the routing message.

Thereafter, the nodes that are one hop away from the sink node calculate the amount of data that can be transmitted by itself and its child nodes during each slot (using Equations 3 to 6) Lt; / RTI >

Each descendant node receiving the amount of data that can be transmitted determines its own operation mode and sensing period using Equations (12), (13), (15), and (17). At this time, a node that is one hop away from the sink node can determine itself as a normal node.

Each node senses data according to a determined sensing period, compresses data according to each operation mode to a sink node, and transmits the sensed data. In addition, the nodes repeat the above steps for each slot.

The present invention proposes a data collection method and a compression algorithm selection method for solving the hot energy problem and the hotspot problem of the node mentioned above in the solar energy collection WSN and increasing the data acquisition amount. In the method proposed in the present invention, a node allocates energy usage to be collected over time, and determines the limit of data that can be transmitted within the allocated energy range.

To collect more data within this limited transmission rate, excess data is collected and compressed to a limited capacity. Accordingly, the node selects a compression algorithm considering the amount of transmittable data and the energy consumed, compresses and transmits the amount of the further collected data according to the limited transmission amount, The amount can be increased.

Hereinafter, in order to evaluate the performance of the method proposed in the present invention, SolarCastalia [J. M. Yi, M. J. Kang, and D. K. Noh, "Solarcastalia: solar energy harvesting wireless sensor network simulator," International Journal of Distributed Sensor Networks, vol. 11, no. 6, pp. 1-10, January 2015.]. (S-LZW), which compresses and transmits only the S-LZW compression algorithm, is used for the performance comparison. (S-LZW-BWT), which compresses and transmits only the S-LZW-BWT compression algorithm, and 4) the selective compression technique (A-COMP). Yoon, J. M. Yi. S. Jeong, J. Jeon, and D. K. Noh, "Dynamic Sensing-Rate Control Scheme Using a Selective Data-Compression for Energy-Harvesting Wireless Sensor Networks," Journal of Embedded Systems and Applications, vol. 11, no. 2, pp. 79-86, April 2016.], the amount of sensed data, and the amount of data that reached the sink node.

For the simulation, 200 energy collection nodes were randomly arranged for a given density, and the energy collected was [J. M. Yi, M. J. Kang, and D. K. Noh, "Solarcastalia: solar energy harvesting wireless sensor network simulator," International Journal of Distributed Sensor Networks, vol. 11, no. 6, pp. 1-10, January 2015.] was used to measure the solar energy change over time. All simulations averaged over 30 measurements. Table 1 below shows the main factors used in the simulation.

Parameter Value Number of nodes 200 Node topology Random Routing algorithm MDT Transmission Range 10 m Battery capacity 100 J

1 h

10-60 s

102 bytes

31 bytes

61 bytes alpha 4 beta 8-10 J

FIG. 4 shows the results of measurement of the number of electrostatic nodes according to the time of each technique from 1000 slots to 1168 slots for a total of 7 days. In other techniques than the method proposed in the present invention, the number of electrostatic nodes is changed according to the variation of the solar energy collection amount. However, it can be confirmed that the method proposed in the present invention hardly generates electrostatic nodes. This is because the burden on the relay node is reduced by limiting the data transmission amount.

FIG. 5 shows a result of measuring the number of electrostatic discharge nodes per hop number from a sink node in 2000 slots. In the conventional techniques, it can be seen that the number of power failure of the one-hop distance from the sink node is greatest due to the hot spot problem. On the other hand, the method proposed by the present invention shows that almost no static nodes occur as shown in FIG.

FIGS. 6 and 7 show the results of measuring the amount of sensing data of all the nodes over time and the number of times the data reaches the sink node. Referring to FIG. 6, it can be seen that the amount of sensed data is higher than that of the method proposed in the present invention and that of the A-COMP technique. Meanwhile, as shown in FIG. 4, since the electrostatic node is generated according to the amount of energy collected, the A-COMP technique shows that the amount of sensed data changes accordingly.

On the other hand, since the method proposed in the present invention determines the amount of dynamically collected according to the allocated energy, the amount of sensed data is substantially constant.

Referring to FIG. 7, it is shown how much the collected data reaches the sink node. As shown in FIG. 5, since the energy of nodes close to the sink node is exhausted and data of another node can not be transmitted, It can be seen that the data did not reach the sink node.

On the other hand, in the method proposed in the present invention, most of the sensed data has arrived at the sink node since almost no static nodes are generated.

8 and 9 show the amount of sensing data according to the density change of the node and the number of data arriving at the sink node, respectively. Referring to FIG. 8, it can be seen that other techniques except for the method proposed in the present invention collect a predetermined amount of data at all times, so that a similar amount of data is collected regardless of the density change.

However, in FIG. 9, it can be seen that as the density of the node decreases, the number of data reaching the sink node decreases. This is because, when the density of the node is low, the transmission path of the nodes becomes long, so that when the relay node goes to the power failure state, more data is lost during transmission.

에 따라 데이터 전송량을 결정하기 때문에 밀도가 낮아 전송 경로가 길어질 경우, 데이터를 적게 수집하고, 밀도가 높아서 전송 경로가 짧아질 경우 데이터를 많이 수집하는 것을 알 수 있다. 또한, 전송 데이터량을 조절하여 정전 노드의 발생을 억제했기 때문에, 수집된 데이터가 대부분 싱크 노드에 도달한 것을 알 수 있다. On the other hand, the method proposed by the present invention is applied to a 1-hop node

It is understood that when the transmission path is long due to the low density, data is collected in a small amount, and when the transmission path is short due to high density, a lot of data is collected. In addition, since the generation of the electrostatic node is suppressed by adjusting the amount of data to be transmitted, it can be seen that most of the collected data reaches the sink node.

10 and 11 show the amount of sensing data according to the change of the solar energy and the number of data arriving at the sink node, respectively. The smaller the amount of solar energy, the smaller the amount of sensing data. This is because the allocated energy varies with the amount of solar energy. At this time, the amount of sensing data of other conventional techniques is larger than that of the method proposed in the present invention. However, since the amount of solar energy is small, a large number of electrostatic nodes are generated, .

When the amount of solar energy is large, the method proposed by the present invention increases the allocated energy and adjusts the sensing period accordingly, so that the amount of data to be sensed and the amount of data to reach the sink node become larger than those of other techniques.

In the present invention, when collecting data periodically using a WSN for collecting solar energy, the collection amount of data is increased by selecting a sensing period and a compression technique. In the method according to the present invention, a node 1-hop distance from a sink node determines a data transmission limit and transmits it to another node to limit the amount of data to be transmitted. Other nodes select a sensing period and a compression scheme corresponding thereto, Suppresses the occurrence, and increases the data collection amount.

As a result of the simulation, it was found that the method proposed by the present invention effectively suppresses generation of electrostatic nodes and obtains a larger amount of data than other techniques by selecting a data collection period and a compression method depending on the situation.

In such a solar energy-collecting wireless sensor network, the sensing period and the compression algorithm selection method considering energy allocation are implemented in the form of program instructions that can be implemented in an application or through various computer components, Lt; / RTI > The computer-readable recording medium may include program commands, data files, data structures, and the like, alone or in combination.

The program instructions recorded on the computer-readable recording medium may be ones that are specially designed and configured for the present invention and are known and available to those skilled in the art of computer software.

Examples of computer-readable recording media include magnetic media such as hard disks, floppy disks and magnetic tape, optical recording media such as CD-ROMs and DVDs, magneto-optical media such as floptical disks, media, and hardware devices specifically configured to store and execute program instructions such as ROM, RAM, flash memory, and the like.

Examples of program instructions include machine language code such as those generated by a compiler, as well as high-level language code that can be executed by a computer using an interpreter or the like. The hardware device may be configured to operate as one or more software modules for performing the processing according to the present invention, and vice versa.

FIG. 12 is a block diagram of a sensing period and a compression algorithm selecting apparatus considering energy allocation in a solar energy collecting wireless sensor network according to an exemplary embodiment of the present invention. Referring to FIG.

In the solar energy collecting wireless sensor network according to the present invention, a sensing period and a compression algorithm selecting apparatus (hereinafter referred to as a device) 10 that considers energy allocation periodically calculate the amount of data collected based on a WSN that periodically transmits sensing data to a sink node We propose a data collection algorithm and a compression algorithm selection method.

12, the apparatus 10 according to the present invention includes a receiving unit 110, an energy calculating unit 130, an operation mode determining unit 150, a sensing period determining unit 170, and a transmitting unit 190 do.

The apparatus 10 of the present invention may be implemented with a sensing period in consideration of energy allocation in a solar energy collection type wireless sensor network and software (application) for performing a compression algorithm selection. The receiving unit 110, The configuration of the calculation unit 130, the operation mode determination unit 150, the sensing period determination unit 170 and the transmission unit 190 may be configured such that the energy of the energy in the solar energy collection type wireless sensor network Can be controlled by the software for performing the sensing period considering the allocation and the compression algorithm selection.

The device 10 may be a separate terminal installed at each node of the WSN or some module of the terminal. The configuration of the reception unit 110, the energy calculation unit 130, the operation mode determination unit 150, the sensing period determination unit 170, and the transmission unit 190 may be formed as an integrated module, Or more. However, conversely, each configuration may be a separate module.

The device 10 may be mobile or stationary. The device 10 may be in the form of a socket, a server or an engine and may be a terminal, a device, an apparatus, a user equipment (UE), a mobile station station, a wireless device, a handheld device, and the like.

The device 10 may execute or produce various software based on an operating system (OS), i.e., a system. The operating system is a system program for allowing software to use the hardware of a device. The operating system includes a mobile computer operating system such as Android OS, iOS, Windows Mobile OS, Sea OS, Symbian OS, Blackberry OS, MAC, AIX, and HP-UX.

The receiving unit 110 receives an amount of energy that can be used in each slot divided into a plurality of slots and an amount of data that each node can transmit.

The energy calculation unit 130 calculates an estimated energy amount consumed in each operation mode during the corresponding slot. The expected amount of energy consumed in the mode may be calculated as the sum of the energy consumed in transmitting the data during the slot, the basic consumed energy, and the energy consumed in compressing the data.

The operation mode determination unit 150 determines an operation mode for selecting a data collection amount and a compression algorithm based on the amount of available energy, the amount of data that can be transmitted, and the amount of energy consumed to be consumed. At this time, the nodes located one hop away from the sink node select themselves as the normal mode.

The operation mode determination unit 150 compares the amount of energy that can be used with the amount of energy that is consumed and determines whether to collect additional data within a range that does not exceed the amount of data that can be transmitted, The operation mode of one of the normal mode, the L mode and the H mode is selected.

When the corresponding node is in the normal mode, it collects data corresponding to the amount of data that can be transmitted without collecting the data, and transmits the collected data without compression. When the node is in the L mode, additional data is collected in addition to the amount of data that can be transmitted, and the collected data is compressed and transmitted. When the node is in the H mode, it collects more additional data than the L mode, compresses the collected data to a higher compression ratio than the L mode, and transmits the compressed data.

The sensing period determiner 170 determines a sensing period for collecting data according to the determined operation mode.

The transmission unit 190 collects data according to the selected data collection amount according to the determined operation mode and the sensing period, and compresses and transmits the collected data according to the selected compression algorithm.

Accordingly, the node selects a compression algorithm in consideration of the amount of transmittable data, the energy allocated and the energy consumed, compresses and transmits the amount of data collected further using the limited amount of data using the compressed algorithm, The amount of data can be increased.

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 present invention as defined by the following claims. You will understand.

The present invention proposes a data collection and compression algorithm selection technique for solving the problem of efficient energy management and hot spot of a node in the solar energy collection WSN and increasing the amount of data acquisition and thus is useful in the field of solar energy based wireless sensor network .

10: Selection of sensing period and compression algorithm considering energy allocation
110:
130: Energy calculation unit
150: Operation mode determination unit
170: sensing period determination unit
190:

Claims (10)

In a sensing cycle and a compression algorithm selection method considering energy allocation in a solar energy collecting wireless sensor network,
Dividing a predetermined time into a plurality of slots in the wireless sensor network and allocating an amount of energy usable in each slot;
The nodes located one hop away from the sink node calculate the amount of data that can be transmitted by itself and its child nodes during each slot to limit the amount of transmission of the node and transmit the amount of data to the child nodes of the node itself;
Each descendant node receiving the amount of data that can be transmitted can calculate the data collection amount and the compression algorithm based on the amount of available energy, the amount of data that can be transmitted, and the estimated amount of energy consumed in each slot. Determining an operating mode;
Each child node determining a sensing period for collecting data according to its determined operation mode; And
Each child node collects data for a selected data collection amount according to its determined operation mode and sensing period, compresses and transmits the collected data according to the selected compression algorithm,
The amount of data,
Calculating a base total amount of data in proportion to the length of one of the plurality of slots and the amount of data collected by one sensor at a time and inversely proportional to a cycle in which one node collects data ;
Calculating a size of a packet necessary for one node to transmit in consideration of the basic total data amount, the maximum data size that can be transmitted at one time, and the size of a header and a footer necessary for data transmission; And
Calculating an actual total amount of data to be transmitted during one slot from a value proportional to the number of the self and its child node to the size of the packet; Sensing Cycle and Compression Algorithm Selection Method.
The method of claim 1, wherein the determining of the mode of operation comprises:
Each child node calculating the consumed estimated energy amount in each operation mode during the corresponding slot;
Determining whether to collect additional data within a range that does not exceed the amount of data that can be transmitted by comparing the amount of available energy with the amount of consumed estimated energy and determining whether to compress or transfer the data; And
Selecting an operation mode of one of a normal mode, an L-mode and an H-mode depending on whether to collect additional data and whether to compress and transmit the data. How to choose the cycle and compression algorithm.
3. The method of claim 2, wherein each of the child nodes collects data by a selected data collection amount according to the determined operation mode and the sensing period, compresses and transmits the collected data according to the selected compression algorithm,
When the node is in the normal mode, it collects data of the amount of data that can be transmitted without collecting the data, and transmits the data without compressing it. In the solar energy collecting wireless sensor network, .
3. The method of claim 2, wherein each of the child nodes collects data by a selected data collection amount according to the determined operation mode and the sensing period, compresses and transmits the collected data according to the selected compression algorithm,
Wherein the sensor node collects additional data in addition to the amount of data that can be transmitted when the node is in the L mode, and compresses and transmits the collected data.
3. The method of claim 2, wherein each of the child nodes collects data by a selected data collection amount according to the determined operation mode and the sensing period, compresses and transmits the collected data according to the selected compression algorithm,
Wherein the node is in the H mode and collects more data than the L mode and compresses the collected data to a higher compression ratio than the L mode and transmits the compressed data. How to choose the cycle and compression algorithm.
3. The method of claim 2, wherein calculating the estimated energy amount consumed by each child node in each operation mode during the corresponding slot comprises:
A sensing cycle and a compression algorithm selection method in consideration of energy allocation in a solar energy collection type wireless sensor network, wherein the energy consumption is calculated on the basis of energy consumed in transmitting data during the corresponding slot, basic consumption energy and energy consumed in compressing data.
3. The method of claim 2,
Further comprising selecting ones of the nodes that are one hop away from the sink node to be in the normal mode.
A computer-readable recording medium having recorded thereon a computer program for performing a sensing cycle and a compression algorithm selection method considering energy allocation in a solar energy collection type wireless sensor network according to any one of claims 1 to 7.
A sensing period and a compression algorithm selecting apparatus considering energy allocation in a solar energy collecting wireless sensor network,
A receiving unit for receiving an amount of energy that can be used in each slot in which a predetermined time is divided into a plurality of slots and an amount of data that each node can transmit;
An energy calculation unit for calculating an estimated energy amount consumed in each operation mode during the corresponding slot;
An operation mode determination unit that determines an operation mode for selecting a data collection amount and a compression algorithm based on the amount of available energy, the amount of data that can be transferred, and the estimated amount of energy consumed;
A sensing period determiner for determining a sensing period for collecting data according to the determined operation mode; And
Collecting data for a selected data collection amount according to the determined operation mode and the sensing period, and compressing and transmitting the collected data according to the selected compression algorithm,
The amount of data,
A node that is one hop away from the sink node is proportional to the length of one of the plurality of slots and the amount of data collected by one sensor at a time, The amount of basic total data in inverse proportion is calculated, and a single node transmits the basic total data amount, the maximum data size that can be transmitted at one time, and the size of a header and a footer necessary for data transmission, Which is a value obtained by calculating an actual total amount of data to be transmitted during one slot from a value proportional to the number of itself and its child nodes in the size of the packet, Sensing Cycle and Compression Algorithm Considering Energy Allocation in Sensor Networks.
10. The apparatus according to claim 9,
The energy amount that can be used is compared with the estimated energy amount consumed to determine whether to collect additional data within a range that does not exceed the amount of data that can be transmitted, And an H mode, wherein the sensing cycle and the compression algorithm selection unit considers energy allocation in a solar energy collection wireless sensor network.

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