KR20230030302A - Apparatus for Providing Routing Energy Efficient of Internet of Things Based on Big Data - Google Patents

Abstract

Provided is an efficient energy routing provision device for big data-based Internet of Things for a green environment, which considers energy and traffic analysis factors, determines routing by setting neighboring nodes as relay nodes, protects big data from malicious entities, and secures network stability and scalability by reducing the traffic load of the routing path.

Description

Apparatus for Providing Routing Energy Efficient of Internet of Things Based on Big Data}

The present invention relates to an apparatus for providing routing, and more particularly, to an apparatus for providing efficient energy routing of the Internet of Things based on big data for a green environment in which routing is determined by setting a neighboring node as a relay node in consideration of energy and traffic analysis factors. it's about

Recently, Internet of Things (IoT) technology, in which objects connected to the Internet generate information on their own without human intervention and operate in conjunction with other objects, people, and systems, is attracting attention. By 2020, the number of things connected to the internet is expected to grow to about 26 billion.

Data produced in the IoT will coexist with small amounts of data and large amounts of data on the order of tens or hundreds of megabytes, such as multimedia content. In the future, various multimedia contents will be produced and consumed. It is expected to become an environment that surpasses the large amount of data traffic.

Wireless sensor networks (WSNs) have gained great popularity in the medical, military, tracking, vehicle systems and smart city areas due to their flexible and cost-effective solutions. A miniature sensor node powered by a battery is placed in the viewing area to collect environmental data, which is later transmitted to the user of the application.

A base station (BS) is treated as a gateway for end users, and all sensor data is routed through the Internet. Application users additionally perform post-analysis of sensor data according to their requirements.

The Internet of Things (IoT) provides services to the community in terms of gathering and disseminating information through integration with wireless sensors. However, the limited control of these wireless sensors poses significant research challenges due to their limited energy management, data storage and computational capabilities.

Most applications use drones and airplanes to randomly distribute nodes and interact with each other via multi-hop communication to collect vast amounts of data. However, as the size of the network increases, it becomes very difficult for sensor nodes to process environmental data more accurately and efficiently due to the limited authority of sensor nodes.

Korean Registered Patent No. 10-2054715

In order to solve this problem, the present invention provides an apparatus for providing efficient energy routing of the Internet of Things based on big data for a green environment in which routing is determined by setting neighboring nodes as relay nodes in consideration of energy and traffic analysis factors. There is a purpose.

An apparatus for providing efficient energy routing according to a feature of the present invention for achieving the above object,

a communication unit for transmitting and receiving search messages, request messages, data packets, and control packets with one or more neighboring nodes;

Transmitting a request message for information sharing to the neighboring node, receiving a control packet in response to the request message from the neighboring node, and calculating a rank value using energy information included in the control packet data routing processing unit; and

and a control unit determining a routing by setting a neighbor node having the highest rank value as a relay node based on the calculated rank value.

An apparatus for providing efficient energy routing according to a feature of the present invention,

a communication unit for transmitting and receiving search messages, request messages, data packets, and control packets with one or more neighboring nodes;

Transmitting a request message for information sharing to the neighboring node, receiving a control packet in response to the request message from the neighboring node, and calculating a rank value using energy information included in the control packet data routing processing unit;

a control unit determining routing by setting the neighbor node as a relay node in consideration of the energy information, the traffic analysis factor, and the calculated rank value; and

It includes a transmission security processing unit that encrypts and transmits sensor data based on PCBC (Propagating Cipher Block Chaining) before data transmission.

According to the configuration described above, the present invention has an effect of securing network stability and scalability by protecting big data from malicious entities and reducing the traffic load of a routing path.

The present invention has an effect of improving energy efficiency through optimal data routing by maintaining a balance between energy and traffic loads between sensor nodes.

1 is a schematic diagram showing the structure of a node of a wireless sensor network according to an embodiment of the present invention.
2 is a diagram showing the configuration of an apparatus for providing efficient energy routing for big data-based Internet of Things according to an embodiment of the present invention.
3 is a diagram showing the performance of the EBDS framework for an existing task on energy consumption according to an embodiment of the present invention.
4 is a diagram illustrating the performance of the EBDS framework along with other tasks for packet drop ratio at various data rates according to an embodiment of the present invention.
5 is a diagram illustrating end-to-end delay and various data transmission rates according to an embodiment of the present invention.
6 is a diagram illustrating network throughput and various data transmission rates according to an embodiment of the present invention.
7 is a diagram illustrating path stability and various data transmission rates according to an embodiment of the present invention.

Throughout the specification, when a certain component is said to "include", it means that it may further include other components without excluding other components unless otherwise stated.

1 is a diagram schematically showing the structure of a node of a wireless sensor network according to an embodiment of the present invention, and FIG. 2 shows the configuration of an apparatus for providing efficient energy routing of the big data-based Internet of Things according to an embodiment of the present invention. it is a drawing

The nodes 10, 20, 30, 40, 50, and 60 according to an embodiment of the present invention include a communication unit 110, a network initialization unit 120, a control unit 130, a data routing processing unit 140, and a transmission security processing unit ( 150).

The nodes 10, 20, 30, 40, 50, and 60 may be in the form of a sensor, server, or engine, and may be a smartphone, a device, an apparatus, It may be called other terms such as terminal, user equipment (UE), mobile station (MS), wireless device, handheld device, and the like.

In addition, the nodes 10, 20, 30, 40, 50, and 60 may be referred to as an energy-efficient big data-based routing providing device 100.

The communication unit 110 transmits and receives a search message, a request message, a data packet, and a control packet with one or more neighboring nodes.

The network initialization unit 120 constructs a graph in which a plurality of sensor nodes are connected using a Greedy method. Graph theory consists of vertices, nodes, and points, and they are connected by edges, that is, lines. In other words, graph theory consists of a vertex (sensor node) and an edge that connects two vertices.

를 구성한다. 센서 노드는 V로 표시되고, E는 노드 간의 연결을 나타내는 에지 세트를 나타낸다.The network initialization unit 120 is a graph connecting links (paths) between sensor nodes.

make up A sensor node is denoted by V, and E represents a set of edges representing connections between nodes.

와 관련된 순서 없는 쌍(u,v)이다. 여기서, 센서 노드 u,

이다.edge

is an unordered pair (u,v) associated with Here, the sensor node u,

am.

Edges (u, v) represent a direct connection from the sensor node u to the adjacent node v.

The number of edges in path p represents the total length.

Each sensor node can measure a weight (Cost) and create a routing table. The routing table contains information about all sensor nodes in a given subnet.

The routing table stores the distance to the sensor node and the value to go to the sensor node.

Each sensor node creates a routing table and transmits it to neighboring nodes.

In addition, each sensor node transmits information about parameters such as residual energy and location in a network field to neighboring nodes.

Each sensor node can search surrounding sensor nodes, find out the address of the connected sensor node, and measure the weight (Cost) of the connected edge.

Each sensor node generates a packet containing information about weights and connected sensor nodes and transmits it to other sensor nodes.

Therefore, sensor nodes store information about neighboring nodes in a routing table.

The data routing processing unit 140 transmits a request message for information sharing to a neighboring node, receives a control packet in response to the request message from the neighboring node, and uses the energy information included in the control packet to generate a rank value. Calculate

The control unit 130 determines routing by setting a neighbor node having the highest rank value as a relay node based on the calculated rank value.

The control unit 130 determines routing by setting neighboring nodes as relay nodes in consideration of energy information, traffic analysis factors, and the calculated rank value.

The data routing processor 140 initially gives each edge a temporary rank value based on the Euclidean distance between the sensor node pair (u, v).

The data routing processing unit 140 updates the rank value R(u, v) by Equation 1 based on the residual energy and the traffic analysis factor. A vertex having the highest rank value indicates a strong correlation between two sensor nodes. That is, the rank value represents the correlation between sensor nodes.

와

는 최적의 라우팅 결정에 중요한 역할을 한다.Weight in Equation 1

and

plays an important role in determining optimal routing.

+

= 1과 같은 에너지 및 트래픽 분석 요인에 대해 동일한 영향을 제공한다.The data routing processing unit 140

+

= 1 to give the same impact for energy and traffic analysis factors.

가 센서 노드

의 초기 에너지이고,

가 소비된 에너지이고, 잔여 에너지

를 수학식 2와 같이 계산할 수 있다.The data routing processing unit 140

Ga Sensor Node

is the initial energy of

is the energy consumed, and the remaining energy

can be calculated as in Equation 2.

는 네트워크 필드에서 모든 센서 노드에 대한 에너지 자원(Resource)의 합계이다here,

is the sum of energy resources for all sensor nodes in the network field.

The routing algorithm of the present invention uses a round time delay (RTD) time to determine traffic analysis from a source node to a neighbor node.

)에서 비콘 메시지를 플러딩한다(다른 노드로 보내는 트래픽 전달). 여기서, 플러딩은 네트워크에서 수정된 라우팅 정보를 모든 노드에 빠르게 전달하는 기능을 의미한다.The source node has a fixed time interval (

) floods beacon messages (traffic forwarding to other nodes). Here, flooding refers to a function of quickly delivering modified routing information to all nodes in the network.

는 첫 번째 비콘 메시지가 전송된 최초의 시간이라면,

는 이웃 노드로부터 수신된 마지막 데이터 패킷을 의미한다.

is the first time the first beacon message is sent,

means the last data packet received from the neighboring node.

이다.T is the total period, and T =

am.

에서 이웃 노드

까지의 트래픽 분석용 특정 전송 링크

을 수학식 3과 같이 계산한다.The data routing processing unit 140 is a source node

Neighbor Nodes in

specific transport links for traffic analysis to

is calculated as in Equation 3.

에서 이웃 노드

간의 데이터 링크가 덜 혼잡하고, 데이터 라우팅에 가장 적합함을 판단한다.Data routing processing unit 140, the higher the value of the calculated traffic analysis, the source node

Neighbor Nodes in

It determines that the data link between the two is less congested and is most suitable for data routing.

The data routing processor 140 of each sensor node calculates a rank value for all edges.

The control unit 130 generates a request message for information sharing and transmits it to a neighboring node.

Accordingly, the data routing processing unit 140 calculates a rank value by receiving a control packet from a neighboring node.

의 제어부(130)는 데이터 전송을 시작하기 위해서 포워더(Forwarder) 목록

을 설정하고, 처음에는

이

만으로 구성된다.source node

The control unit 130 of the forwarder (Forwarder) list to start data transmission

, and initially

this

consists of only

의 제어부(130)는 라우팅 테이블에서 이웃 노드에 대한 계산된 랭크 값을 결정하고, 가장 높은 랭크 값이 속한 노드를

에 배치한다.After that,

The control unit 130 determines the calculated rank value for the neighboring node in the routing table, and selects the node to which the highest rank value belongs.

be placed on

을 업데이트한다.Therefore, the control unit 130 compares the rank value of each neighboring node with respect to the next source node, and based on the highest rank value

update

This procedure continues with the identification of the weighted edge to select the optimal relay node using the highest rank value until the data from the sensors reaches the base station.

In addition, whenever any relay node consumes energy resources higher than the threshold, the routing algorithm of the present invention uses the rank value to select the selected relay node that forwards the sensor's data and source node unicast and messages to the next appropriate relay node. Exclude.

In addition, the routing algorithm of the present invention excludes message transmission of a relay node using a rank value, unicast of a source node, and data transmission of a sensor node from a selected relay node whenever a relay node consumes energy resources higher than a threshold value. .

The aforementioned control unit 130 and data routing processing unit 140 provide an efficient routing path through an optimized routing decision based on the Dijkstra algorithm (Equation 1, Equation 2, Equation 3).

The secure data transmission algorithm of the present invention protects big data from potential threats and maintains data confidentiality and authentication.

The secure data transmission algorithm uses a lightweight key distribution method based on a single network-wide key that sensor nodes preload before being deployed.

After the nodes distribute, they communicate with neighboring nodes that possess a shared network key. A single key acts as a symmetric key and is known only to successive nodes of the transmission edge.

In addition, the secure data transmission algorithm utilizes PCBC (Propagating Cipher Block Chaining) to achieve data encryption and authentication.

The transmission security processing unit 150 encrypts the sensor data based on PCBC (Propagating Cipher Block Chaining) before transmitting the data.

을 수행하여 악성 개체 존재 시 잠재적인 위협에 대한 데이터 프라이버시를 향상시킨다.The transmission security processing unit 150 divides the data of the sensor node into blocks before data transmission and performs a chain-type data encryption function.

to improve data privacy against potential threats in the presence of malicious entities.

는 대칭키

를 이용한 암호화 함수이고,

는 동일한 키

를 이용한 복호화 함수이다. 그런 다음 센서 노드

에 대한 메시지 블록

은 수학식 4와 수학식 5를 사용하여 PCBC를 기반으로 하는 각각의 암호 블록

으로 변환된다.Prior to data encryption in the transmission security processing unit 150, each block of sensor data performs an XOR operation on a previous plaintext (plaintext) block and a previous ciphertext block.

is the symmetric key

is an encryption function using

is the same key

It is a decryption function using . Then sensor node

message block for

Each cryptographic block based on PCBC using Equations 4 and 5

is converted to

은 이전 블록인

의 암호 블록이다.In Equations 4 and 5,

is the previous block

is the cipher block of

The control unit 130 transmits the data block encrypted by the transmission security processing unit 150 to the base station via the communication unit.

Accordingly, the control unit 130 transmits the data block of the relay node set to the base station through the communication unit, and finally decrypts all encrypted data based on the symmetric key as shown in Equation 6.

(performance evaluation)

The performance of the Energy-Efficient Big Data-Based Secure (EBDS) framework is evaluated for efficient data collection methods of Sca-PBDA and sensor networks.

Performance is evaluated using NS-3 in terms of various data rates. In the simulation, the network field is considered squared in size, and the layout is of size 300 × 300 m ² .

IoT-based sensors and malicious nodes are 200 and 20, respectively. The location of the base station is set outside the network field and remains static. The data transfer rate in bit units is set to 50 to 250.

와

의 값들은 0.5 및 0.5로 고정된다. 센서 노드의 잔류 에너지는 2j 내지 5j 범위에 있다. 표 1은 시뮬레이션 매개변수의 값을 나열한다.weight factors

and

The values of are fixed to 0.5 and 0.5. The residual energy of the sensor node is in the range of 2j to 5j. Table 1 lists the values of simulation parameters.

The simulation is run for 1000 iterations, and the data size of each block is 32 bits.

3 is a diagram showing the performance of the EBDS framework for existing tasks on energy consumption according to an embodiment of the present invention.

This section presents the experimental results along with a discussion of energy consumption, network throughput, packet drop rate, end-to-end delay and path stability.

The EBDS framework was observed to reduce the energy consumption rate by 13% and 18%, respectively, at various data rates. This is because the energy level consumed in further work is reduced by judging the surrounding environment of the node. The EBDS framework also optimizes relay node selection based on the rank value and increases the path lifetime level. Unlike other tasks, the EBDS framework explicitly minimizes additional load on nodes and reduces additional path discovery packets improving energy efficiency.

Additionally, the EBDS framework uses multi-hop transport instead of single-hop and balances the load distribution between source and relay nodes. Also, due to the multi-hop paradigm, energy consumption per node is reduced while transmitting sensor data to the base station.

The EBDS framework provides a more secure path with lightweight cryptographic operations, thus balancing the processing overhead.

Figure 4 is a diagram showing the performance of the EBDS framework along with other tasks for packet drop ratio at various data rates according to an embodiment of the present invention.

According to the experimental results, the EBDS framework reduced the data loss rate by 26% and 39%, respectively.

This is because a more energy-efficient, traffic wear relay node is selected in consideration of the limited resources of the sensor node side.

The EBDS framework keeps track of network and node up-to-date parameters when calculating routing decisions. Unlike other tasks that are prone to failure and have poor path consistency in various network traffic, the EBDS framework of the present invention provides a more reliable and secure method that does not degrade network performance in terms of disconnection.

In addition, the EBDS framework periodically evaluates the remaining energy of relay nodes to exclude energy inefficient nodes from the existing routing path, ultimately increasing the data transfer rate.

5 is a diagram illustrating end-to-end delay and various data transmission rates according to an embodiment of the present invention.

The performance of the EBDS framework on existing tasks is shown. The EBDS framework has been shown to reduce end-to-end latency by 12% and 19% at various data rates.

The reason is that the EBDS framework reduces the transmission distance from the sensor node to the base station by using multi-hop communication.

It also participates in routing decisions by selecting the most energy aware and least congested relay node. This routing method improves the efficiency of delivering data in a timely manner. In addition, the EBDS framework provides a more realistic and delay-efficient routing path through optimized routing decisions based on the Dijkstra algorithm, reducing frequent retransmission and route rediscovery messages.

Unlike other solutions that incur high overhead between sensor nodes to find a routing path with high network latency, the EBDS framework provides stable and reliable relay nodes, reduces control messages between neighboring nodes, and improves timely data delivery performance. improve

In addition, the EBDS framework includes neighbor traffic awareness information to evaluate the source node's routing metric, which helps avoid congestion in transmission links for data routing and reduces end-to-end delay measurements.

6 is a diagram illustrating network throughput and various data transmission rates according to an embodiment of the present invention.

Figure 6 shows the performance of the EBDS framework compared to other solutions in terms of data transfer rate. Based on simulated experiments, the EBDS framework has been shown to improve data delivery performance by 10% and 15% for different data rates. The reason for this improvement is that relay nodes are selected using elements of energy and traffic analysis. These elements reduce additional energy consumption between sensor nodes and strengthen routing paths for transmitting large amounts of big data.

In addition, since data packets are routed to the base station through multi-hop transmission based on multiple criteria using the Dijkstra algorithm, the number of packets transmitted to the base station is higher than other solutions. Additionally, the EBDS framework increases the threshold for data security along the routing path and ignores potential threats affecting message delivery.

7 is a diagram illustrating path stability and various data transmission rates according to an embodiment of the present invention.

Figure 7 shows the performance of the EBDS framework in comparison to existing work. In the simulation experiment, it was observed that the EBDS framework increased the route stability by 13% and 19% for various data transmission rates due to the least number of control messages and flooding of route rescan packets on the sensor node side.

In addition, the EBDS framework incorporates secure and certified algorithms based on PCBC mode to increase the performance of path stability. Since this method performs encryption and decryption functions in the form of a chain, the security level is balanced between data transmission and reception nodes with the least communication overhead in a low-power sensor node. Thus, the EBDS framework reduces the possibility of sensor data being compromised and is ultimately more robust against malicious threats to data collection and routing.

Although the embodiments of the present invention have been described in detail above, the scope of the present invention is not limited thereto, and various modifications and improvements made by those skilled in the art using the basic concept of the present invention defined in the following claims are also included in the scope of the present invention. that fall within the scope of the right.

100: Routing provider
110: communication department
120: network initialization unit
130: control unit
140: data routing processing unit
150: transmission security processing unit

Claims (7)

a communication unit for transmitting and receiving search messages, request messages, data packets, and control packets with one or more neighboring nodes;
Transmitting a request message for information sharing to the neighboring node, receiving a control packet in response to the request message from the neighboring node, and calculating a rank value using energy information included in the control packet data routing processing unit; and
and a control unit determining a routing by setting a neighbor node having the highest rank value as a relay node based on the calculated rank value. a communication unit for transmitting and receiving search messages, request messages, data packets, and control packets with one or more neighboring nodes;
Transmitting a request message for information sharing to the neighboring node, receiving a control packet in response to the request message from the neighboring node, and calculating a rank value using energy information included in the control packet data routing processing unit;
a control unit determining routing by setting the neighbor node as a relay node in consideration of the energy information, the traffic analysis factor, and the calculated rank value; and
An efficient energy routing providing device including a transmission security processing unit that encrypts and transmits sensor data based on PCBC (Propagating Cipher Block Chaining) prior to data transmission. According to claim 1 or claim 2,
The data routing processor updates the rank value R(u, v) by Equation 1 below based on residual energy and traffic analysis factors, and calculates the residual energy by Equation 2 below. Efficient energy routing provision device.
[Equation 1]

where u is a sensor node, v is a neighboring node,

and

is a preset weight, E is residual energy, and Tri is a specific transmission link for traffic analysis.
[Equation 2]

here,

Ga Sensor Node

is the initial energy of

is the energy consumed,

is the sum of energy resources for all sensor nodes in the network field. The method of claim 3,
The data routing processing unit is a source node

Neighbor Nodes in

specific transport links for traffic analysis to

Calculated by Equation 3 below, and the higher the value of the calculated specific transmission link for traffic analysis, the higher the source node

at the neighbor node

A device that provides efficient energy routing that is determined to be most suitable for data routing between
[Equation 3]

here,

is the first time the first beacon message is sent,

is the last data packet received from the neighbor node, T is the total period

lim. According to claim 1 or claim 2,
The control unit updates a node having the highest rank value to a forwarder list based on the calculated rank value. According to claim 1 or claim 2,
A data encryption function in the form of a chain by splitting the sensor data into blocks before data transmission

, XOR operation of the previous plaintext (plaintext) block and the previous ciphertext block, and sensor node

message block for

Each cipher block based on PCBC (Propagating Cipher Block Chaining) using Equation 4 and Equation 5 below.

An apparatus for providing efficient energy routing, further comprising a transmission security processing unit that converts
[Equation 4]

[Equation 5]

here,

is the symmetric key

is an encryption function using

is the same key

is a decryption function using

is the previous block

is the cipher block of . According to claim 1 or claim 2,
A graph that connects links (paths) between sensor nodes

An apparatus for providing efficient energy routing, further comprising a network initialization unit configured of -V is the sensor node and E is a connection between nodes.

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