CN113347590B - WBAN clustering routing protocol based on human body mobility and energy collection - Google Patents
WBAN clustering routing protocol based on human body mobility and energy collection Download PDFInfo
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Abstract
A WBAN clustering routing protocol based on human body mobility and energy collection, on one hand, consider the energy collection technology to supply the energy for the network; on the other hand, by utilizing the clustering technology, the proper double cluster heads are selected to forward data to reduce energy consumption. A benefit function is constructed through parameters such as residual energy of sensor nodes, link quality, distance to Sink, mobile factors and the like, and the node with the largest benefit function is selected as a cluster head for data forwarding, so that reliability and timeliness of data transmission in a network are guaranteed.
Description
Technical Field
The invention relates to the technical field of wireless body area networks, in particular to a WBAN clustering routing protocol based on human body mobility and energy collection.
Background
With the continuous progress of medical technology, the life of human beings is gradually prolonged, the development speed of aging of the world population is gradually accelerated, the chronic disease of the aged people caused by aging is rapidly increased, so that the social health problem is increasingly severe, and the problem needs to be solved by changing the existing medical mode. A Wireless Body Area Network (WBAN) is a self-organizing network with low power consumption and high reliability and taking a human body as a center, physiological characteristic data of a person is sensed by deploying sensors on the human body, the sensed data is transmitted to a medical monitoring terminal in a wireless communication mode, a doctor at the terminal can analyze the data and then diagnose the patient, and the medical monitoring mode has great potential for solving the problems of senile diseases, chronic diseases and the like.
Sensors applied to WBAN are severely limited in size and battery capacity for comfort of human body, resulting in limited energy. In order to ensure that the WBAN can complete reliable data transmission under the condition of limited energy, designing an energy-saving route plays a key role in reducing network energy consumption. In addition, changes in human body posture cause links between sensors to be disconnected, resulting in lost or delayed data transmission. However, sensors collect physiological information of patients, which generally affects their life safety, and thus, the real-time and reliability of WBAN data transmission must be improved.
The low battery capacity of the sensor leads to energy shortage, and the energy of the sensor can be exhausted under the condition of no energy supply, so that the service life of the network is short. A uniform-energy-consumption backside routing protocol is proposed by Ha et al, which mainly focuses on energy consumption and routing balance among sensor nodes deployed on the backside of the human body to ensure stable data transmission of WBAN. The method takes the M-ATTEMPT protocol as a basic protocol, improves the human body posture change mechanism in the M-ATTEMPT protocol and improves the self network adaptivity and reliability. The protocol achieves better results in terms of network stability and throughput, but changes in human posture affect the network lifetime. A new energy-saving and harvest awareness protocol is proposed by Ullah et al, which uses a clustering method to overcome the path loss problem by forming two clusters with Sink nodes as their predetermined cluster heads. To further improve energy efficiency, EH-RCB uses an energy harvesting mechanism. In order to select the best forwarding node for data transmission, the protocol calculates a cost function for each node in the network, the parameters used to calculate the cost function being the total energy (sum of the acquired energy and the remaining energy), the distance to Sink and the required transmission power, but does not take into account the effect of mobility on the network stability.
In summary, it is important to consider the influence of various parameters on the routing mechanism in the energy-starved and dynamic environment.
Disclosure of Invention
In order to solve the technical problems, the invention provides a WBAN clustering routing protocol based on human body mobility and energy collection, on one hand, energy collection technology is considered to supply energy to a network; on the other hand, the clustering technology is utilized to select proper double cluster heads to forward data so as to reduce energy consumption. A benefit function is constructed through parameters such as residual energy of sensor nodes, link quality, distance to Sink, mobile factors and the like, and the node with the largest benefit function is selected as a cluster head for data forwarding, so that reliability and timeliness of data transmission in a network are guaranteed.
In order to realize the technical purpose, the adopted technical scheme is as follows: the WBAN clustering routing protocol based on human body mobility and energy collection is realized by the following stages:
step one, building a WBAN model and initializing
The WBAN adopts a network topology structure of multi-hop transmission, and consists of N sensor nodes and 1 Sink node, wherein all the nodes collect weak energy of the surrounding environment and store the weak energy in a battery, the Sink node is deployed at the waist of a human body and divides physiological data into emergency data and common data, and the emergency data is prioritized according to the importance degree of the emergency data, and the priority of the emergency data is higher than that of the common data;
and calculating the distance D between the sensor node and the neighbor node and the Sink by using the signal receiving strength RSSI, and broadcasting the beacon message in the network by all the sensor nodes including the Sink after calculating the distance. The beacon message comprises a transmitting node ID, a distance to a neighbor node, a destination node ID and residual energy E of the sensor node res (sigma), link quality and a Mobility Factor (MF), each sensor node storing the information after receiving the beacon message;
step two, cluster head selection and cluster formation
Based on the information collected during the initialization phase, two clusters are formed according to the inter-node distance, one of which is on the upper part of the human body and the other of which is on the lower part, by the residual energy E of the sensor nodes res (sigma), distance D between nodes, link quality and mobile factor MF as decision parameters of the path to form a benefit function CF, and selecting the node with the maximum value of the benefit function as a cluster head of two clusters
After selecting a cluster head, a Sink node broadcasts a message of the selected cluster head to all nodes in the network, all sensor nodes determine which cluster head to join after receiving the broadcast message, the RSSI value of the sensor node and a certain cluster head is higher, the sensor node and the certain cluster head join, then each sensor node in the network sends a joining request to the newly selected cluster head, and based on the request message, the cluster head records the sensor node in the cluster;
step three, data transmission
When the sensor node i needs to send a data packet, if the type of the transmitted data is emergency data, the sensor node directly transmits the data to a Sink node; if the type of the transmitted data is normal data, the data is transmitted by using the cluster head selection and cluster forming process. If the distance from the source node to the cluster head is smaller than the distance from the source node to the Sink node, transmitting data by using the cluster head until the data packet is transmitted to the Sink node; and if the distance from the source node to the cluster head is greater than the distance to the Sink node, directly transmitting.
Before calculating the benefit function, whether the residual energy of the sensor node is larger than a threshold value or not and whether the link quality of the sensor node is larger than the threshold value or not are judged.
The motion factor MF is calculated as the ratio of the remaining pause time to the total pause time.
The Link quality is calculated by the method that the Link quality depends on the signal strength RSSI
Wherein, W rx Expressed as received power, W tx Denoted as transmit power.
The invention has the beneficial effects that: aiming at the problems of human body mobility and energy shortage of a wireless body area network, a WBAN clustering routing protocol based on human body mobility and energy collection is provided. The protocol not only considers the energy collection technology to supply energy for the network, but also utilizes the clustering technology to realize energy-saving transmission of data, a benefit function is constructed through the residual energy of the sensor nodes, the link quality, the distance from the sensor nodes to the Sink and the mobile factor, and the node with the largest benefit function is selected as a cluster head for forwarding the data. Simulation results show that compared with the two existing routing protocols, the MERP improves the performances of prolonging the service life of the network, improving the throughput, improving the reliability and the like.
The selection of the two cluster heads and the formation of the two clusters can effectively establish a proper routing path, ensure the timeliness and reliability of data transmission and simultaneously reduce the energy consumption of remote nodes.
The addition of the mobile factor can enable the calculation of the benefit function to meet the requirement of network dynamic characteristics and enhance the network reliability. The cluster head is selected by utilizing the benefit function, so that the data transmission reliability and timeliness of the nodes in the cluster are enhanced, and the energy efficiency of the nodes in the network is improved.
Drawings
FIG. 1 is a general flow chart of the present invention;
FIG. 2 is a schematic diagram of cluster head selection according to the present invention;
FIG. 3 is a comparison graph of network lifetime analysis of the present invention;
FIG. 4 is a comparison graph of the average residual energy analysis of the present invention;
FIG. 5 is a comparison graph of packet loss rate analysis according to the present invention;
FIG. 6 is an analysis comparison graph of throughput of the present invention.
Detailed Description
1. Network model
The WBAN consists of N sensor nodes and 1 Sink node. Because the energy collection technology is adopted to supplement energy for the network, each sensor node has the energy collection capacity, and the sensor nodes are converted into electric energy by collecting weak energy of the surrounding environment (such as kinetic energy generated by human body movement) and are stored in the battery. The Sink node is arranged on the waist of a human body, and information from each sensor node is received conveniently.
The model assumes that:
(1) And constructing the wireless body area network by adopting a 2-hop expanded star topology structure.
(2) All sensor nodes possess a specific ID and have the same initial energy and transmission range.
(3) The Sink node only receives data from the sensor, does not generate data, and does not consider the energy of the Sink.
As the physiological data sensed by the sensor nodes have heterogeneity and different importance degrees, in order to ensure the real-time effectiveness of important data transmission, the physiological data are divided into emergency data and common data, and the priority of the emergency data is higher than that of the common data according to the importance degrees of the emergency data and the common data.
2. Energy consumption and collection calculations
The energy consumption of the sensor node for data transmission is the largest, and this section mainly calculates the energy consumption of data transmission, as shown in the following formula.
E Tx ＝E Tx-elec ×N+E Amp ×N×c×l 2 (1)
E Rx ＝E Rx-elec ×N (2)
Where N is the size of the data packet and l is the data transmission distance. E Tx Indicating the energy consumed by the transmitted data, the energy consumption E of the circuit when the data is transmitted by the node Tx-elec And energy E consumed by the amplifying circuit Amp In this case, the WBAN may not transmit the data, but may transmit the data through the WBAN. E Rx Representing the energy consumed by the received data, E by the energy consumption of the circuit when receiving the data Rx-elec And (4) forming.
Total energy consumption E consumed during transmission T From E Tx And E Rx The formula is as follows:
E T ＝E Tx +E Rx (3)
in order to calculate the real-time energy consumption of the sensor, the total energy E consumed by the nodes for data transmission after the sigma wheel is assumed to be collected at the moment t T (σ) is represented by the following formula.
Γ represents the time consumed by a node to transmit data within one communication cycle.
Aiming at the problems that the energy of a sensor node is deficient and the battery of an implanted sensor is not easy to replace, an energy collection technology is introduced to supply power to the sensor, so that the service life of a network is prolonged. The energy harvesting source and its mechanism of use are shown in table 1.
Through the analysis of various energy collection sources in the table 1, the kinetic energy is found to be easily obtained compared with other natural energy sources, and the energy conversion rate is high, so that the protocol assumes that the sensor completes the charging of the battery by converting the kinetic energy generated by the motion of the human body into electric energy. When the human body is in a motion state, energy begins to be collected; and does not collect energy when the body is at rest (sitting or sleeping). The calculation formula for the collected energy is as follows:
E H ＝θ i Γ (5)
E H representing the energy collected, theta i Representing the conversion of the energy collected by node i over time Γ.
Assuming that the total energy E collected by the node after sigma-round data transmission at the time t H (σ) is represented by the following formula.
The maximum value of the energy collected by the protocol by using the energy collection technology cannot exceed the capacity of the battery.
TABLE 1 energy harvesting sources and mechanism of use thereof
3. Merp routing (WBAN clustering routing based on human mobility and energy collection) design the routing protocol proposed herein is mainly divided into three stages, initialization, cluster head selection and cluster formation, data transmission, etc. Fig. 1 is a general flow chart of the protocol.
3.1 initialization procedure
In the initialization stage, the distances between the sensor node and the neighbor nodes and the Sink node are calculated by utilizing the signal received strength (RSSI). After the distance is calculated, all sensor nodes including the Sink node broadcast beacon messages in the network. The beacon message contains parameters such as the ID of a transmitting node, the distance to a neighbor node, the ID of a destination node, the residual energy of a source node, the link quality, the mobility factor and the like. Each sensor node saves this information after receiving the beacon message.
3.2 Cluster head selection and Cluster formation Process
The cluster head selection and cluster formation can effectively establish a proper routing path, ensure the timeliness and reliability of data transmission, and simultaneously reduce the energy consumption of remote nodes.
3.2.1 Cluster head selection
After the initialization phase is completed, two clusters (one on the upper part of the human body and the other on the lower part) are formed according to the inter-node distance based on the information collected in the initialization phase. The protocol proposed herein selects a cluster head for two clusters as shown in fig. 2. The purpose of creating clusters is to simplify the network convergence and data transfer process, since only defined cluster members can communicate within a cluster.
The parameters mainly considered herein are the remaining energy of the node, the distance from the sensor node to the Sink node, the link quality and the mobility factor, which are collectively used as the basis for selecting the cluster head, and are described in detail below.
Residual energy E res (σ): the residual energy in the protocol comprises the addition of energy collection, and the calculation formula is as follows.
E res (σ)＝E o -E T (σ)+E H (σ) (7)
Wherein, E o Representing the initial energy of the node.
The distance D between the sensor node and the Sink node is as follows: the distance between the node and the Sink node is calculated by using the signal receiving strength, and the calculation is as follows.
Wherein RSSI (d) 0 ) Is a transmitting end d 0 RSSI value of (d) represents the receiving end, X σ Is a zero mean gaussian random variable.
Link quality Link: the link quality depends on the signal strength (RSSI), which is calculated as follows.
Wherein, W rx Expressed as received power, W tx Denoted as transmit power.
The mobile factor MF: the mobility parameter considered by the protocol is the remaining suspension time of the node, which represents the difference between the total time of the node staying at a fixed position and the staying time, so as to embody the dynamic characteristics of the network. If the remaining pause time of the node is longer than the required data transmission time, the data transmission cannot cause loss and retransmission; if the remaining pause time is less than the transmission time, it is not suitable for data transmission and retransmission may occur. The mobility factor is calculated as the ratio of the remaining pause time to the total pause time, and represents the probability value of finding the existence of the node at a certain fixed position, and the reliability of the data received by the node is judged by using the probability value, and the formula is as follows.
From the above analysis, the residual energy of the nodes, the inter-node distance, the link quality and the mobility factor are considered herein as decision parameters of the path to constitute a benefit function (CF), with the goal of selecting the node with the maximum value of the benefit function as a cluster head for transmitting data. The addition of the mobile factor can enable the calculation of the benefit function to meet the requirement of network dynamic characteristics and enhance the network reliability. The cluster head is selected by utilizing the benefit function, so that the data transmission reliability and timeliness of the nodes in the cluster are enhanced, and the energy efficiency of the nodes in the network is improved. The formula is calculated as follows.
Before calculating the benefit function, whether the residual energy of the sensor node is larger than a threshold value and whether the link quality of the sensor node is larger than the threshold value are judged. Otherwise, the cluster head can not be used as the cluster head, and by utilizing the judgment, the calculation times of the benefit function can be reduced, and the cluster head can be quickly selected.
3.2.2 Cluster formation
After cluster head selection, the Sink node broadcasts a message of the selected cluster head to all nodes in the network. After receiving the broadcast message, all sensor nodes decide which cluster head to join. And if the RSSI value of the sensor node and a certain cluster head is higher, adding the sensor node and the certain cluster head. Each sensor node in the network then sends a join request to the newly selected cluster head. Based on the request message, the cluster head records the sensor node in its cluster.
3.3 data Transmission Process
When a sensor node i needs to send a data packet at a certain time, if the type of the transmitted data is emergency data, the node directly transmits the data to a Sink node; if the type of data to be transmitted is normal data, the data is transmitted using cluster formation and cluster head selection procedures. If the distance from the source node to the cluster head is smaller than that from the source node to the Sink node, the cluster head is used for transmitting data until the data packet is transmitted to the Sink node; and if the distance from the source node to the cluster head is greater than that to the Sink node, directly transmitting.
4. Simulation and performance evaluation
4.1 simulation Environment and parameters
In order to verify the performance of the MERP protocol, MATLAB software is used for simulation, and the network service life, the energy consumption, the packet loss rate and the throughput are used as performance indexes to perform performance comparison analysis with the existing ELR-W and EECBSR protocols. The maximum communication range of the common node is set to be 45cm, and the sink node is set to be 80cm. Table 3 shows the simulation parameters set for this protocol.
TABLE 2 simulation parameters
4.2 simulation results analysis
4.2.1, network lifetime is measured in terms of the number of rounds performed before a node dies, and a smaller number of dead nodes in a certain time period indicates a longer network lifetime for the protocol. Fig. 3 is a network lifetime comparison of three protocols.
It can be seen from the figure that the first dead node of the EECBSR protocol occurs in 3000 rounds, being the earliest of the three protocols. Whereas the ELR-W and merp protocols occurred at 4200 and 5000 rounds, respectively, with the merp protocol occurring the latest. With the increase of the number of rounds, the growth speed of the dead nodes of the EECBSR and ELR-W protocols is higher, the last dead node respectively appears in 7500 rounds and 9800 rounds, the death speed of the nodes of the MEHRP protocol is relatively uniform, all the nodes die in 11600 rounds, and the network life of the nodes is longest in the comparison protocol. Since the EECBSR considers aspects such as human body posture change and parent node screening child node limit according to priority, although the reliability of the protocol is improved, these processes increase network overhead. The ELR-W comprehensively considers parameters such as residual energy and link quality of nodes, and the network attribute is static, so that the network service life is longer than that of EECBSR. The MEHRP protocol provided by the invention adopts an energy collection technology to supply energy to the sensor, the service life of the network is longer than that of the EECBSR and ELR-W protocol, and the stability of the network is higher.
4.2.2, average remaining energy
The energy consumption in the network reflects the service life and the performance of the whole network, and the average residual energy is used for measuring the energy consumption of the network. Fig. 4 is a comparison of the remaining energy of the three protocols.
It can be seen from the figure that the mean remaining energy of the merp protocol decreases more slowly than the EECBSR protocol and the ELR-W protocol. The EECBSR is fully depleted of energy at 7500 rounds because it does not take into account link efficiency and therefore causes data retransmission. The MEHRP protocol utilizes an energy collection technology to supplement energy for the sensor nodes in the network, and the integral residual energy of the network is slow in descending speed. It can be seen from the figure that the remaining energy of the merp is low when the number of the rounds is about 1000, mainly because the information of each sensor node is processed in the early stage of the network, and thus the energy is consumed. By the middle of the network, the energy consumption of the network gradually becomes stable.
4.2.3 packet loss Rate
The packet loss rate is a ratio of the number of lost packets in data transmission to the number of transmitted packets, and may reflect the reliability of the network. Fig. 5 shows packet loss rates of three protocols. The packet loss rate of the ELR-W protocol is lower than that of the EECBSR protocol, and the main reason is that the ELR-W protocol uses link quality parameters to select appropriate forwarding nodes to transmit data and construct an appropriate route, which guarantees link efficiency, and thus the packet loss rate is lower. The packet loss rate of the MERP protocol is higher before 3000 rounds and is close to that of the EECBSR protocol, the two protocols consider the dynamic topology change of the network, the stability of data transmission is influenced, the number of dead nodes of the EECBSR protocol is increased continuously along with the increase of the number of rounds, the effective path is reduced, and the packet loss rate is obviously increased. In addition, the MERP protocol considers link quality prediction, meanwhile, an energy collection technology is utilized to supply energy to the network, the increase speed of dead nodes is controlled to prolong the service life of the network and improve the reliability of data transmission, and the packet loss rate after 3000 rounds is better than that of an ELR-W protocol and an EECBSR protocol. It can be seen from the figure that as the number of rounds increases, the packet loss rate of the merp protocol increases to a small extent, which fully indicates that the reliability of the protocol is strong.
4.2.4, throughput
Throughput, which represents the number of successful transmissions of data to a destination per unit time, represents the overall performance of the network.
Fig. 6 shows the variation trend of the number of received data packets at the Sink node.
The EECBSR protocol has the maximum throughput in the network life, and the most important reason is that the EECBSR protocol has a large number of deployed nodes and a large number of paths to Sink. The throughput of the merp protocol is similar to that of the ELR-W protocol before 3000 rounds because the merp protocol and the ELR-W protocol deploy the same number of sensors in the network. With the increase of the number of rounds, the throughput of the MERP protocol gradually exceeds the ELR-W protocol, the data transmission efficiency is improved mainly by using an energy collection routing mode, and the service life of the network is prolonged, so that the network throughput is improved, and the throughput of the MERP protocol is the highest and exceeds the EECBSR protocol.
Claims (2)
1. WBAN clustering routing protocol based on human mobility and energy collection is characterized in that: the implementation of the routing protocol comprises the following phases:
step one, building a WBAN model and initializing
The WBAN adopts a network topology structure of multi-hop transmission, and consists of N sensor nodes and 1 Sink node, wherein all the nodes collect weak energy of the surrounding environment and store the weak energy in a battery, the Sink node is deployed at the waist of a human body and divides physiological data into emergency data and common data, and the emergency data is prioritized according to the importance degree of the emergency data, and the priority of the emergency data is higher than that of the common data;
calculating the distance D between the sensor node and the neighbor node and the Sink by using the signal receiving strength RSSI, and broadcasting a beacon message in the network by all the sensor nodes including the Sink after calculating the distance; the beacon message comprises a sending node ID, the distance to a neighbor node, a destination node ID and the residual energy E of the sensor node res (sigma), link quality Link and mobility factor MF, each sensor node saves these information after receiving the beacon message;
the distance D between the sensor node and the Sink node is calculated as follows:
wherein RSSI (d) 0 ) Is a transmitting end d 0 RSSI value of (d) represents the receiving end, X σ Is a zero mean gaussian random variable;
the calculation method of the movement factor MF is the ratio of the remaining pause time to the total pause time;
step two, cluster head selection and cluster formation
Based on the information collected during the initialization phase, two clusters are formed according to the inter-node distance, one of which is on the upper part of the human body and the other of which is on the lower part, by the residual energy E of the sensor nodes res (sigma), distance D between nodes, link quality and mobile factor MF as decision parameters of the path to form a benefit function CF, and selecting the node with the maximum value of the benefit function as a cluster head of two clusters
The Link quality is calculated by the method that the Link quality depends on the signal strength RSSI
Wherein, W rx Expressed as received power, W tx Expressed as transmit power;
after selecting a cluster head, a Sink node broadcasts a message of the selected cluster head to all nodes in the network, all sensor nodes determine which cluster head to join after receiving the broadcast message, the RSSI value of the sensor node and a certain cluster head is higher, the sensor node and the certain cluster head join, then each sensor node in the network sends a joining request to the newly selected cluster head, and based on the request message, the cluster head records the sensor node in the cluster;
step three, data transmission
When a sensor node i needs to send a data packet, if the type of the transmitted data is emergency data, the sensor node directly transmits the data to a Sink node; if the transmitted data type is common data, the data is transmitted by utilizing the cluster head selection and the cluster forming process; if the distance from the source node to the cluster head is smaller than the distance from the source node to the Sink node, transmitting data by using the cluster head until the data packet is transmitted to the Sink node; and if the distance from the source node to the cluster head is greater than the distance to the Sink node, directly transmitting.
2. The WBAN clustering routing protocol based on human mobility and energy harvesting according to claim 1, wherein: before calculating the benefit function, whether the residual energy of the sensor node is larger than a threshold value or not and whether the link quality of the sensor node is larger than the threshold value or not are judged.
Priority Applications (1)
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Application publication date: 20210903 Assignee: CARSEN TECHNOLOGY Co.,Ltd. Assignor: HENAN University OF SCIENCE AND TECHNOLOGY Contract record no.: X2023980049317 Denomination of invention: WBAN Clustering Routing Protocol Based on Human Mobility and Energy Collection Granted publication date: 20230131 License type: Common License Record date: 20231206 |